EX-99.1 2 exh991.htm

NI 43-101 Technical Report

Mineral Resources

Bongará Zinc Project

Amazonas Department, Peru

Effective Date: June 05, 2014

Report Date: June 18, 2014

Report Prepared for

Solitario Exploration and Royalty Corp. – Minera Bongará S.A.

4251 Kipling Street. Suite 390

Wheat Ridge, Colorado 80033

Report Prepared by

SRK Consulting (U.S.), Inc.

5250 Neil Road, Suite 300

Reno, Nevada 89502

SRK Project Number: 181700.090

Signed by Qualified Persons:

J. B. Pennington, CPG

Chris Sheerin, R-SME

Brooke J. Miller, CPG

Walter Hunt, CPG

James Gilbertson, CGeol

Reviewed by:

Allan V. Moran, CPG

Summary (Item 1)

This report was prepared in accordance with the Canadian Institute of Mining, Metallurgy and Petroleum Definition Standards for Mineral Resources and Mineral Reserves reporting: CIM Definition Standards, November 27, 2010 (CIM), as a National Instrument 43-101 (NI 43-101) compliant Technical Report on Resources for Solitario Exploration and Royalty Corp. (Solitario) by SRK Consulting (U.S.), Inc. (SRK). It provides the first NI 43-101 Mineral Resource Statement for the Bongará Zinc Project, located in Amazonas Department, Peru. Bongará is a Mississippi Valley Type (MVT) base metal deposit characterized by high-grade zinc and associated lead and silver mineralization potentially amenable to underground mining methods. The Project is controlled by Minera Bongará S.A., the Joint Venture (JV) company owned by Solitario and established in 2006. Votorantim is currently the operating partner of the JV, and has the right to earn 70% control of the shares of Minera Bongará.

Mineral Resource estimation for the Bongará deposit was conducted by Votorantim in August, 2013 and reported by Mineral Resources Management (MRM), an internal resource modeling group of Votorantim, in December of 2013 (Votorantim, 2013b). In April of 2014, SRK was contracted by Solitario to audit the MRM resource estimate and prepare a Technical Report on Resources compliant with the guidance of NI 43-101. SRK has relied on the MRM report for technical information related to the construction of the resource model and has taken the necessary steps to validate the estimation methods and results. SRK’s validation included an independent analysis of the project database, geostatistical analysis of the data, and reconstruction of the resource model using 3-D modeling software. SRK visited the Project site on May 5 to 7, 2014.

Property Description and Ownership

The Bongará Zinc Project (the Project) is controlled by Minera Bongará S.A., a subsidiary of Solitario, and is subject to a joint venture agreement with Votorantim since 2006. The Project is a mineral exploration project comprised of sixteen contiguous mining concessions, covering approximately 12,600 hectares. The concession titles are in the names of Minera Bongará and Votorantim Metais and are subject to the Minera Bongará joint venture agreement between Solitario and Votorantim.

The Project is located in the Eastern Cordillera of Peru at the sub-Andean front in the upper Amazon River Basin. It is within the boundary of the Shipasbamba community, 680 km north-northeast of Lima and and 245 km northeast of Chiclayo, Peru, in the District of Shipasbamba, Bongará Province, Amazonas Department. The Project area can be reached from the coastal city of Chiclayo by the paved Carretera Marginal road. The central point coordinates of the Project are approximately 825,248 East and, 9,352,626 North (UTM Zone 17S, Datum WGS 84). Elevation ranges from 1,800 meters above sea level (masl) to approximately 3,200 masl. The climate is classified as high altitude tropical jungle in the upper regions of the Amazon basin. The annual rainfall average exceeds 1 m with up to 2 m in the cloud forest at higher elevations.

All of the Project mineral concessions are granted by the Peruvian government. According to Peruvian law, concessions may be held indefinitely, subject only to payment of annual fees to the government. Annual concession fees as required by law are paid annually to the Peruvian

government. When this study was initiated, concession payments were current, with 2013 fees of $98,600 paid on May 31, 2013.

Votorantim, as operator of the joint venture company Minera Bongará, has entered into a surface rights agreement with the local community of Shipasbamba which controls the surface rights of the Project. This agreement provides for an annual payments and funding for mutually agreed upon social development programs in return for the right to perform exploration work including road building and drilling. From time to time, Votorantim also enters into surface rights agreements with individual private landowners within the community to provide access for exploration work.

History

Prior to the discovery of mineral occurrences by Solitario in 1994, no mineral prospecting had been done on the Property and no concessions had been historically recorded. In 1995 and later, Solitario staked the current mineral concessions in the Project area.

In 1996, Cominco Ltd. formed a joint venture partnership (JV) with Solitario. This agreement was terminated in 2000 and Solitario retained ownership of the property. Between 1997 and 1999, Cominco completed geologic mapping, geophysical surveys, surface sampling, and 82 diamond drill holes.

In 2006, Votorantim and Solitario formed a JV for the exploration and possible development of the property. As the operator of the JV company, Votorantim has initiated surface diamond core drilling, geologic mapping, surface outcrop sampling, underground exploration drifting and underground drilling programs. As of August 15, 2013, Votorantim had completed 404 diamond drillholes which, when combined with the previous drilling of Cominco, totals 117,260 m.

There has not been any commercial mining in the Project area. The only underground excavation has been 700 m of underground drifting by Votorantim to provide drill platforms at the San Jorge area. A subsidiary of Hochschild Mining PLC tested open pit mining for a short time at the Mina Grande deposit near the village of Yambrasbamba, 18 km northeast of Florida Canyon, where Solitario had previously defined an oxidized zinc resource by pitting.

Environmental Studies and Permitting

Environmental permits for mineral exploration programs are divided into two classes. Class I permits allow construction and drilling for up to 20 platforms with a maximum disturbance of 10 hectares. A Class II permit provides for more than 20 drill locations or for a disturbance area of greater than 10 hectares. Votorantim has filed applications for and received Class II permits for various phases of the Project and has filed and received the required associated permits. The Project is in compliance with all permitting requirements necessary for undertaking planned activities relating to exploration.

Permitting requirements for mining include an Estudio de Impacto Ambiental (EIA) that describes in detail the mining plan and evaluates the impacts of the plan on environmental and social attributes of the property. Baseline studies include air quality, surface and groundwater quality, flora and fauna surveys, archeological surveys and a study of the social conditions of the immediate property and an area of interest that includes local communities. Public meetings are required in order that local community members can learn about and comment on the proposed operation. Many of the baseline studies required for mining have been completed by Votorantim.

Development and Operations

Road access to the Bongará region is provided primarily by the Carretera Marginal paved highway connecting the port city of Chiclayo to Pedro Ruiz (inland). Travel time to Pedro Ruiz takes on average 6 hours by car. It is a regional commerce center with hotels, restaurants, communication and a population estimated to be 10,000. The immediate Project area is not populated but there are several small villages nearby, which are supported by subsistence farming.

Current access to the Project is by foot, mule or helicopter. A road is under construction from the community of Shipasbamba and planned to be completed in 2014. The Project area has little existing infrastructure with only an access road under construction and a number of primitive camps and drill pads. Drilling has been accomplished using helicopter support from the village of Shipasbamba which lies 10 km to the southeast. The Project core shed and sample storage facility is located in Shipasbamba.

Geology and Mineralization

The Project is located within an extensive belt of Mesozoic carbonate rocks belonging to the Upper Triassic to Lower Jurassic Pucará Group and equivalents. This belt extends through the central and eastern extent of the Peruvian Andes for nearly 1000 km and is the host for many polymetallic and base metal vein and replacement deposits in the Peruvian Mineral Belt. Among these is the San Vicente Mississippi Valley Type (MVT) zinc-lead deposit that has many similarities to the Florida Canyon deposit and other MVT occurrences in the Project area.

Known zinc, lead and silver mineralization in the Project area is hosted in dolomitized limestone of the Chambara Formation subunit 2 in the Pucará Group. The structure at Florida Canyon is dominated by a N50º-60ºW trending domal anticline cut on the west by the Sam Fault and to the east by the Tesoro-Florida Fault. In the Project area, the three prospective corridors for economic mineralization studied in detail are San Jorge, Karen-Milagros, and Sam. In these areas, dolomitization and karsting is best developed in proximity to faulting and fracturing associated with each structural zone. In turn, these structures provided access for the altering fluids to bleed laterally into stratigraphic horizons with more permeable sedimentary characteristics.

The primary zinc-lead-silver mineralization of the Bongará deposit occurs as sphalerite and galena. At shallow depths, these sulfide minerals are altered to smithsonite, hemimorphite, and cerussite by meteoric water. These minerals are collectively referred to as “oxides” in this deposit, and are important to the mineral resource. About one third of the estimated resource is oxide.

Exploration Status

The focus of Votorantim’s recent exploration work at the Project has been resource definition drilling with HQ-diameter core in the San Jorge and Karen-Milagros areas. Drilling in the San Jorge area was completed underground from a new adit, while drilling in the Karen-Milagros area was completed from surface.

Future exploration work will focus on infill drilling between the Karen-Milagros, San Jorge and Sam areas. Mineralization is open to the north and south and remains largely untested to the east of the Tesoro fault and west of the Sam fault where greater target depths have lowered the near term drilling priority.

A total of 486 core holes for a combined 117,280 m of drilling have been completed, and are the basis for initial resource estimation.

Mineral Processing and Metallurgical Testing

Votorantim retained a metallurgical consultant, Smallvill S.A.C. (Smallvill) to perform metallurgical studies on Bongará mineralization types in 2010 and 2011. In 2013, AMEC was contracted to evaluate the project at scoping level. SRK has relied heavily on these two studies for recovery and cost forecasting to develop cut-off grades for resource reporting.

The Bongará sulfide resource consists of zinc and lead sulfides in a limestone matrix where zinc is in higher proportions than lead. The recovery testing focused on conventional lead-zinc flotation. The oxide resource contains zinc in much higher proportion than lead, and consists of zinc carbonates and silicates in a dolomitic limestone matrix. The zinc oxide material is predominately smithsonite and hemimorphite, and lead oxide material is cerussite. The oxide recovery process Smallvill investigated focused on a combination of heavy media separation (HMS) followed by conventional zinc oxide flotation. The two concentrates are then upgraded to marketable products through calcination and Waelz roasting processes.

The recovery estimates for Bongará are based on preliminary metallurgical testing utilizing conventional sulfide and oxide flotation processes. Table 1 provides the recovery estimates by material type.

Table 1: Bongará Metal Recoveries by Material Type

Item	Material	Zinc	Lead	Silver
Item	Type	Rec.%	Rec.%	Rec.%
1	Sulfide	93.1	84.8	55.6
2	Mixed	84.9	50.0	32.8
3	Oxide	73.0	n/a	n/a

Source: SRK, 2014

For the sulfide, the conventional selective lead-zinc flotation process and treatment of the concentrate in lead and zinc smelters was utilized to estimate metal recovery, concentrate grades and processing costs. Oxide recovery, concentrate grade and operating costs were based on conventional zinc oxide flotation, calcining the flotation concentrate and treating the calcined concentrate at a zinc smelter. Recovery and processing costs for the mixed material was based on a tonnes weighted average; 59: 41 percent sulfide to oxide ratio.

Other processing options were investigated by Votorantim/Smallvill for the oxide material, but were not utilized due to process un-conventionality and higher operating costs.

Anticipated concentrate grades used in cut-off grade calculations are provided in Table 2 by material type.

Table 2: Bongará Predicted Concentrate Grades by Material Type

Item	Material	Conc.	Conc.	Conc.
Item	Type	Zn%	Pb%	Ag g/t
1	Sulfide	55.2	52.6	7.3
2	Mixed	52.0	52.6	7.3
3	Oxide	47.5	n/a	n/a

Source: SRK, 2014

Mineral Resource Estimate

In preparing the current resource statement, SRK has used engineering experience and informed assumptions to define the appropriate cut-off grade to reflect the mining and processing methods and costs anticipated as the project advances. This report provides a mineral resource estimate and a classification of resources and reserves reported in accordance with the Canadian Institute of Mining, Metallurgy and Petroleum Standards on Mineral Resources and Reserves: Definitions and Guidelines, November 27, 2010 (CIM). The resource estimate and related geologic model auditing were conducted by, or under the supervision of, J. B. Pennington, M.Sc., C.P.G., of SRK Consulting in Reno, Nevada, who is a Certified Professional Geologist as recognized by the American Institute of Professional Geologists and a Qualified Person as defined by NI 43-101.

The Resource Estimate was based on a 3-D geological model of major structural features and stratigraphically controlled alteration and mineralization completed by Votorantim. A total of 23 mineral domains, defined above a 0.5% zinc cut-off, were interpreted from mineralized drill intercepts, comprised mostly of 1m core samples. The resource estimate was based on 23,863 zinc analyses from 117,280 m of drilling in 486 diamond drill holes. The block size of the model is 10 m x 10 m x 1 m. Zinc, lead and silver were estimated into model blocks by Ordinary Kriging using three nested search passes. Oxide, Sulfide and Mixed material types were estimated by Indicator Kriging (IK). Density was determined from a large percentage (n= 1,576, 54%) of direct density measurements, which were used to develop equations for density assignment based on material type and kriged metal content.

Resources were reported to Measured, Indicated and Inferred classification compliant with CIM definitions according to NI 43-101 guidance. Measured resources were supported by estimates of 5 or more composites within a 25 m search radius. Indicated resources were supported by estimates of 3 or more composites within a 50 m radius. Inferred resources had no composite restrictions and were estimated by kriging or nearest neighbor outside the largest kriging search radius.

The Mineral Resource Statement for the Bongará zinc-lead-silver deposit is presented in Table 3. Cut-off grades were based on zinc-equivalency of lead and silver normalized to a Net Smelter Return (NSR) base value. The cut-off grades are defined in the notes of the resource table.

Table 3: Mineral Resource Statement for the Bongará Zn-Pb-Ag Deposit, Amazonas Department, Peru, SRK Consulting (U.S.), Inc., June 5, 2014

Category	Mass	Grade				Contained Metal (millions)
Category	Mass	Zn	Pb	Ag	ZnEq	Zn	Pb	Ag	ZnEq
	Mt	%	%	g/t	%	(lbs)	(lbs)	(oz)	tonnes	(lbs)
Measured	1.43	13.02	1.85	19.3	15.45	410.0	58.3	0.884	0.221	486.5
Indicated	1.35	12.51	1.71	17.1	14.74	372.6	50.9	0.744	0.199	438.8
Measured + Indicated	2.78	12.77	1.78	18.2	15.10	782.5	109.2	1.628	0.420	925.3
Inferred	9.07	10.87	1.21	12.2	12.44	2,173.0	241.5	3.554	1.130	2,487.6

Source: SRK, 2014

Notes:

Mineral Resources are not Mineral Reserves and do not have demonstrated economic viability. There is no certainty that all or any part of the Mineral Resources estimated will be converted into Mineral Reserves;

Mineral resources are reported to an NSR zinc-equivalent (ZnEq%) cut-off grade based on metal price assumptions*, metallurgical recovery assumptions**, mining costs, processing costs, general and administrative (G&A) costs, and NSR factors***. Mining costs, processing, G&A, and transportation costs total US$51.30/t.

i. *Metal price assumptions considered for the calculation of metal equivalent grades are: Zinc (US$/lb 0.95), Lead (US$/lb 0.95) and Silver (US$/oz 20.00),

ii. **Cut-off grade calculations assume variable metallurgical recoveries as a function of grade and relative metal distribution. Average metallurgical recoveries for sulfide and oxide respectively are: Zinc (93.1%, 73%), Lead (84.8, 0%) and Silver (55.6%, 0%)

iii. *** NSR factors for calculating cutoff grades were: ZnEq% = Zn% * 1 + Pb% * 0.74 + Ag g/t * 0.02

Resulting cutoff grades used in this resource statement were 4.1% ZnEq for sulfide, 5.0% ZnEq for oxide, and 4.5% ZnEq for mixed material types.

Zinc equivalency for reporting in situ resources was calculated using:

ZnEq (%) = Zn (%) + 1.0 * PB (%) + 0.03 * Ag (g/t)

Density was calculated based on material types and metal grades. The average density in the mineralized zone was 2.91 g/cm³ as a function of the zinc and lead sulfide mineral content.

Mineral Resources as reported are undiluted.

Mineral resource tonnage and contained metal have been rounded to reflect the precision of the estimate, and numbers may not add due to rounding.

The resource is comprised of 63% sulfide, 28% oxide and 9% mixed material types by contained zinc above cut-off. The cut-off grade was established based on an NSR zinc-equivalent (ZnEq%) for each material. The cut-offs were as follows: 4.1% ZnEq for sulfide, 5.0% ZnEq for oxide, and 4.5% ZnEq for mixed material types. Cut-off grades account for recovery and treatment/smelting charges.

The zinc-equivalent for reporting in situ resources in Table 3 was calculated based on metal price ratios of lead and silver relative to zinc as follows: ZnEq (%) = Zn (%) +1.0 * PB (%) + 0.03 * Ag (g/t).

Conclusions

The Bongará Zinc Project is a significant greenfields potentially underground mineable high-grade zinc deposit containing associated lead and silver. The Project has a large land position and strong technical and financial backing through Solitario’s earn-in JV partner Votorantim Metais. While this document represents the first formal Mineral Resource Statement for the Project, Votorantim and Cominco report having previously spent over US$60M on drilling, test work and strategic planning for development (Solitario, 2014). Current projections in the zinc metal market suggest a near-term reduction in zinc supply as current major producers exhaust reserves.

SRK’s exposure to the project on the ground in northern Peru found it to be a well-organized facility, with current QA/QC protocols in place for drilling data verification and validation. Material handling, core storage and security were all at or above industry standards.

SRK used a number of methods to validate the Votorantim resource block model starting with a face-to-face meeting with the modeler and following on with a thorough audit of the model source data, geologic modeling techniques, grade and tonnage estimation methods and classification protocols. SRK found these to be in line with industry standards, having been produced with recognized mining software, defensible data and reasonable assumptions. SRK was able to independently validate the model results.

A significant component of the SRK input to the Mineral Resource Statement involved the determination of the cut-off grade for which the resource was reported. As with other poly-metallic base-metal deposits, the value of the in situ mineralization is materially affected by the potential future processing, transportation and smelting costs. These costs vary by material type (e.g. oxide or sulfide) in which the mineralization occurs. Specifically, unit costs for processing and transport are directly affected by material type. These material types were quantified in the block model and SRK used a combination of engineering experience and a review of Votorantim’s research and test work as the basis for cost estimates to define the appropriate cut-off grades for the reported resource.

SRK is unaware of any environmental, permitting, legal, title, taxation or marketing factors that could limit or affect the resource stated in this document. The project will benefit from additional infill and exploration drilling, additional process-metallurgical test work, engineering studies for infrastructure and tailings management and forward planning to clearly define concentrate transport and smelter costs.

Exploration

The current exploration model for the Project has been applied successfully in drillhole planning and resource definition. There is low risk to the Project if no additional exploration is completed. However, additional drilling for resource definition has a strong potential to expand the known resource extent and upgrade Inferred resources to Measured and Indicated.

At present, the deposit is open laterally to the north and south as well as to the west and east on the downthrown sides of the graben that defines the limits of exploration to date. Gaps in the drill pattern within the footprint of the existing drilling provide another opportunity to increase resources where drill spacing limits the continuity of stratigraphically controlled mineralization. A constraint on effective exploration and delineation drilling in these areas is the access to drilling stations due to the rugged terrain. The completion of a road into the area will help to expedite future drilling and development programs by providing increased access and lowering costs.

The discovery of the high-angle, high-grade San Jorge zone has prompted more emphasis on angled drilling, where most of the historic drilling is vertical to near-vertical and is therefore ineffective at locating and defining near-vertical structures. These “break-through” structures have been mapped on surface in several locations, but due to logistical constraints, have not been adequately drill tested for their down-dip continuity. Similarly, there appear to be additional drill targets at the intersection of the high-angle structures and the flat manto zones, where grades are locally enhanced. These concentrations may be present within the existing drilling footprint, but

require additional drilling to delineate. The high grade and potential tonnage of such targets provide an incentive to locate and further define resources of this geometry.

Mineral Resource Estimate

The Mineral Resource was constrained by mineral domains and reported conservatively with respect to search range. Measured and Indicated resources are defined by recent Votorantim drilling using active quality controls. Zinc, in the form of sphalerite is the primary metal with a secondary contribution of lead-sulfide (galena) and associated silver. Due to the variable processing costs associated with oxide compared to sulfide (and mixed) material types, the modeling of these materials or “mineralization types” is particularly important. At present this item represents the highest level of risk in the resource model. Part of the challenge in quantifying oxide is related to drill coverage and part is due to host rock variability as a function of alteration intensity, fracture permeability and degree of karst dissolution. Votorantim is experimenting with quantitative (e.g. sulfur assays) and semi-quantitative methods to refine oxide/sulfide modeling.

In SRK’s opinion, there is immediate potential to upgrade the resource with step-out drilling beyond the radius of the current Votorantim footprint and into the areas containing only lower-confidence Cominco drilling. All mineralization defined solely by Cominco drilling is categorized as Inferred because current QA/QC sampling standards were not industry practice when Cominco conducted its drilling, Twin and infill drill holes in these areas could provide the verification that Cominco drilling results can be considered compliant with CIM and NI 43-101 standards in future resource estimates.

Metallurgy and Processing

Processing of sulfide mineralization (zinc-lead-silver) from the Bongará deposit is straight forward using conventional flotation to a concentrate followed by offsite smelting. There are several potential processing scenarios under consideration to optimize zinc extraction from oxide. Cut-off grades applied in this report were based on conventional flotation of zinc in oxide followed by on-site calcining and offsite smelting. Other oxide process options include Heavy Media Separation and on-site leaching of flotation products with solvent extraction to produce zinc cathode on site. The operators are currently planning test work to delineate the most cost effective processing methods for oxide-hosted zinc. There exists an opportunity to reduce costs for transportation of concentrate to the treatment facility. At present, SRK has assumed overland transport; however, routing concentrate to the coast and sea-freighting to a port destination offers potential cost savings.

Projected Economic Outcomes

Economic projections are beyond the scope of this report. However, the high in situ grades of the zinc mineralization and low impurities in sulfide at Bongará should generate a premium concentrate and a highly saleable product in a market where strong future demand is forecasted. The challenge to Project development lies in its remote location, which raises capital costs for construction and operating costs for concentrate delivery among other things. Road access construction to the site is still underway and is seen as a key component to Project advancement. High-relief terrain and high annual rainfall are conditions affecting development, especially in the area of infrastructure construction and process/tailings containment and stability. Politically and socially, however, the development of a mining operation at this location is considered low risk as many of the local residents are already employed or seeking employment with Votorantim.

Recommendations

SRK acknowledges, after examination of the Project data set, that there have been a significant number of technical studies completed by Votorantim, many of which are beyond scoping level (preliminary economic assessment or PEA), and some of which would satisfy Feasibility Study criteria. Therefore, the work elements listed in Table 4 represent mostly Prefeasibility- and Feasibility-level engineering and drilling to support those studies.

Votorantim is a private company and does not have an obligation to produce NI 43-101 compliant reporting; however, the Project would benefit by having future reporting prepared by Votorantim, who are directly involved in the specifications of the test-work and studies and are therefore most qualified to interpret and apply the results. At the juncture where Prefeasibility-level engineering has been completed, the Project will likely warrant further public reporting to an international standard (JORC, or NI 43-101) and this will be best addressed by Votorantim. Technical information required to achieve this level of project development are listed in Table 4. A cost estimate for these work elements is included in the table.

Table 4: Summary of Costs for Recommended Work

Work Program	Estimated	Assumptions/Comments
Engineering Studies	Cost US$
Advanced Prefeasibility Study (PFS)	600,000	Votorantim or consultant engineer
Subtotal Studies	600,000
Drilling		salaried new hire or contract PM
Exploration Drilling	2,100,000	20 holes to 350 m @ $300/m
Resource Conversion Drilling	2,100,000	20 holes to 350 m @ $300/m
Metallurgical Drilling for Flotation and Comminution	1,225,000	10 PQ holes to 350 m @ $350/m
Geotechical Drilling for Mining	500,000	10 holes oriented to 100m @ $500/m
Geotechnical Drilling for Foundation Stability	225,000	50 holes to 30m @ $150/m
Hydrogeological Drilling	600,000	4 holes to 300m @ $500/m
Subtotal Drilling	6,750,000
Studies + Drilling	7,350,000
Contingency @15%	1,102,500
Total	8,452,500

Source: SRK, 2014

Table of Contents

Summary (Item 1)	i
Property Description and Ownership	i
History	ii
Environmental Studies and Permitting	ii
Development and Operations	iii
Geology and Mineralization	iii
Exploration Status	iii
Mineral Processing and Metallurgical Testing	iv
Mineral Resource Estimate	v
Conclusions	vi
1 Introduction (Item 2)	1
1.1 Terms of Reference and Purpose of the Report	1
1.2 Qualifications of Consultants (SRK)	1
1.3 Details of Inspection	2
1.4 Sources of Information	2
1.5 Reliance on Other Experts (Item 3)	2
1.6 Effective Date	2
1.7 Units of Measure	2
2 Property Description and Location (Item 4)	3
2.1 Property Location	3
2.2 Mineral Titles	5
2.2.1 Nature and Extent of Issuer’s Interest	7
2.2.2 Property and Title in Peru	7
2.3 Royalties, Agreements and Encumbrances	8
2.4 Environmental Liabilities and Permitting	8
2.4.1 Required Permits and Status	8
2.5 Other Significant Factors and Risks	9
3 Accessibility, Climate, Local Resources, Infrastructure and Physiography (Item 5)	10
3.1 Topography, Elevation and Vegetation	10
3.2 Climate and Length of Operating Season	10
3.3 Sufficiency of Surface Rights	10
3.4 Accessibility and Transportation to the Property	10
3.5 Infrastructure Availability and Sources	12
3.5.1 Proximity to Population Center	12
3.5.2 Power	12

3.5.3 Water	12
3.5.4 Mining Personnel	15
3.5.5 Potential Mine Infrastructure Areas	15
4 History (Item 6)	17
4.1 Prior Ownership and Ownership Changes	17
4.2 Previous Exploration and Development Results	17
4.3 Historical Mineral Resource and Reserve Estimates	17
4.4 Historical Production	18
5 Geological Setting and Mineralization (Item 7)	21
5.1 Regional Geology	21
5.2 Local Geology	21
5.2.1 Lithology and Stratigraphy	21
5.2.2 Structure	24
5.2.3 Alteration	26
5.2.4 Mineralization	30
5.3 Property Geology	35
5.4 Significant Mineralized Zones	37
6 Deposit Type (Item 8)	39
6.1 Mineral Deposit	39
6.2 Geological Model	39
7 Exploration (Item 9)	41
7.1 Relevant Exploration Work	41
7.2 Surveys and Investigations	41
7.3 Sampling Methods and Sample Quality	41
7.4 Significant Results and Interpretation	41
8 Drilling (Item 10)	43
8.1 Type and Extent	43
8.2 Procedures	45
8.3 Interpretation and Relevant Results	49
9 Sample Preparation, Analysis and Security (Item 11)	50
9.1 Sampling Methods	50
9.1.1 Sampling for Geochemical Analysis	50
9.1.2 Sampling for Density Measurement	50
9.2 Security Measures	50
9.3 Sample Preparation	51
9.4 QA/QC Procedures	53

9.4.1 Standards	53
9.4.2 Blanks	54
9.4.3 Duplicates	54
9.4.4 Actions	55
9.5 Opinion on Adequacy	55
10 Data Verification (Item 12)	56
10.1 Procedures	56
10.2 Limitations	56
10.3 Opinion on Data Adequacy	56
11 Mineral Processing and Metallurgical Testing (Item 13)	58
11.1 Testing and Procedures	58
11.2 Relevant Results	58
11.2.1 Sulfide Material	58
11.2.2 Oxide Material	65
11.3 Recovery Estimate Assumptions	71
11.4 Sample Representation	71
11.4.1 Sample Location	71
11.4.2 Material Types	71
11.5 Significant Factors for Processing and Costs	72
11.5.1 Sample Representation	72
11.5.2 Material Processing	72
11.5.3 Operating Costs	73
12 Mineral Resource Estimate (Item 14)	74
12.1 Geology and Mineral Domain Modeling	75
12.2 Drillhole Database	81
12.2.1 Database	81
12.2.2 Analytical Data Collation	81
12.2.3 Topography and Sample Locations	81
12.2.4 Oxide Classification in Drillhole Logging	82
12.3 Drilling Data Analysis	85
12.3.1 Capping	89
12.3.2 Compositing	91
12.4 Density	92
12.5 Variogram Analysis and Modeling	93
12.6 Block Model	97
12.6.1 Model Specifications	97
12.6.2 Model Construction	97

12.6.3 Special Handling of Voids	98
12.7 Grade Estimation	100
12.8 Model Validation	105
12.8.1 Visual Comparison	105
12.8.2 Comparative Statistics	110
12.8.3 Swath Plots	110
12.9 Resource Classification	117
12.10 Mineral Resource Statement	121
12.11 Cut-off Grade Determination	121
12.12 Mineral Resource Sensitivity	122
12.13 Relevant Factors	124
12.13.1 Equivalency	124
13 Mineral Reserve Estimate (Item 15)	125
14 Mining Methods (Item 16)	126
15 Recovery Methods (Item 17)	127
16 Project Infrastructure (Item 18)	128
17 Market Studies and Contracts (Item 19)	129
18 Environmental Studies, Permitting and Social or Community Impact (Item 20)	130
19 Capital and Operating Costs (Item 21)	131
20 Economic Analysis (Item 22)	132
21 Adjacent Properties (Item 23)	133
22 Other Relevant Data and Information (Item 24)	134
23 Interpretation and Conclusions (Item 25)	135
23.1 Exploration	135
23.2 Mineral Resource Estimate	136
23.3 Metallurgy and Processing	136
23.4 Projected Economic Outcomes	137
24 Recommendations (Item 26)	138
24.1 Recommended Work Programs and Costs	138
24.1.1 Work Programs	138
24.1.2 Costs	139
25 References (Item 27)	140
26 Glossary	141
26.1 Mineral Resources	141
26.2 Mineral Reserves	141

26.3 Definition of Terms	142
26.4 Abbreviations	143

List of Tables

Table 1: Bongará Metal Recoveries by Material Type	iv
Table 2: Bongará Predicted Concentrate Grades by Material Type	v
Table 3: Mineral Resource Statement for the Bongará Zn-Pb-Ag Deposit, Amazonas Department, Peru, SRK Consulting (U.S.), Inc., June 5, 2014	vi
Table 4: Summary of Costs for Recommended Work	ix
Table 2.2.1: List of Mineral Claims	5
Table 3.4.1: Distance and Travel Time to Bongará Project from Lima, Peru	10
Table 8.2.1: Downhole Survey Data Point Spacing	45
Table 9.3.1: Analytical Codes and Methods	51
Table 9.4.1.1: Summary of SRM Statistics for Lead	53
Table 9.4.1.2: Summary of SRM Statistics for Zinc	53
Table 11.2.1.1: Head Grade of Sulfide Composite	59
Table 11.2.1.2: Multi-Element Composition of Sulfide Composite	59
Table 11.2.1.3: Mineralogy of Sulfide Composite	59
Table 11.2.1.4: Comparison of Bond Work Index for Sulfide Materials	60
Table 11.2.1.5: Effect of Grind Size on Lead and Silver Flotation	61
Table 11.2.1.6: Effect of Grind Size on Zinc Flotation	61
Table 11.2.1.7: Optimized Lead Sulfide Flotation Parameters	62
Table 11.2.1.8: Optimized Zinc Sulfide Flotation Parameters	63
Table 11.2.1.9: Metallurgical Balance for Sulfide Flotation	65
Table 11.2.2.1: Head Grade of Oxide Composite	65
Table 11.2.2.2: Multi-Element Analysis of Oxide Composite	65
Table 11.2.2.4: Variation of Work Index with Grind Time for Oxide Composite	66
Table 11.2.2.8: Conditioner Doses for Zinc Oxide Flotation	68
Table 11.2.2.9: Optimized Zinc Oxide Flotation Results	68
Table 11.2.2.10: Calcination Results, HMS Concentrate	68
Table 11.2.2.11: Metallurgical Balance for Proposed Zinc Oxide Recovery Process	69
Table 12.2.4.1: Logged Oxide Classification of Zn and Pb Mineralization	82
Table 12.3.2.1: Statistics of All Composites Inside the 0.5% Zinc Mineral Domains	92
Table 12.3.2.2: Statistics of All Composites Inside the 0.5% Zinc Mineral Domains by Oxide Classification	92
Table 12.5.1: Base Parameters for Variogram Construction	93
Table 12.5.2: Summary of Variogram Results for Zn, Pb, Ag, and Oxide, Sulfide, Mixed for High-Angle Mineral Domains	94

Table 12.5.3: Summary of Variogram Results for Zn, Pb, Ag, and Oxide, Sulfide, Mixed for Flat Manto Domains	94
Table 12.6.1.1: Block Model Specifications	97
Table 12.6.1.2: Block Model Item Descriptions	97
Table 12.7.1: Parameters of Local Grade Estimation Using Octant Search Criteria	100
Table 12.7.2: Example of Final Classification of Mixed Material Type after Indicator Kriging	100
Table 12.9.2: Summary Statistics of Classified Blocks by Search Volume (SV)	119
Table 12.10.1: Mineral Resource Statement for the Bongará Zn-Pb-Ag Deposit, Amazonas Department, Peru, SRK Consulting (U.S.), Inc., 05 June, 2014	121
Table 12.11.1: Cut-off Grade Inputs and Calculations	122
Table 24.1.2.1: Summary of Costs for Recommended Work	139
Table 26.3.1: Definition of Terms	142
Table 26.4.1: Abbreviations	143

List of Figures

Figure 2-1: Project Location Map	4
Figure 2-2: Map of Mineral Claims	6
Figure 3-1: Photograph of the Bongará Project Area	11
Figure 3-2: Project Access Road	13
Figure 3-3: Photograph of Drilling Camp at Project Site	14
Figure 3-4: Potential Mine Infrastructure Location	16
Figure 4-1: Regional Geologic Map	19
Figure 4-2: Project Drilling History	20
Figure 5-1: Project Area Stratigraphic Column	23
Figure 5-2: Base of Chambara 2 Contour Map	25
Figure 5-3: Photograph of Coquina Marker Horizon in Chambara 2 Unit	27
Figure 5-4: Photograph of Strongly Dolomitized Core with Karst Dissolution	28
Figure 5-5: Photograph of Dolomitized Packstone with Pseudobreccia Texture	29
Figure 5-6: Photograph of Nancy Outcrop	31
Figure 5-7: Photograph of Mineralized Dolomite Packstone Pseudobreccia	32
Figure 5-8: Photograph of Heterolithic Collapse Breccia	33
Figure 5-9: Photograph of Zoned Polyphase Sphalerite from Drillhole V297, 250.0m	34
Figure 5-10: Bongará Project Geologic Map	36
Figure 5-11: Cross Section of the Project Geologic Model	38
Figure 6-1: Mississippi Valley-Type Deposit Schematic Model	40
Figure 8-1: Geologic Map with Drillhole Locations	44
Figure 8-2: Photograph of Drillhole V412, 102.4m-107.9m	46

Figure 8-3: Photograph of Project Core Storage Facility in Shipasbamba	47
Figure 8-4: Photograph of Interior of Project Core Storage Facility	48
Figure 10-1: Photograph of Project core lithology reference sample library	57
Figure 11-1: Optimized Sulfide Flotation Flow Sheet	64
Figure 11-2: Proposed Zinc Oxide Flotation Circuit	70
Figure 12-1: North-South Longitudinal Section of Geologic Model	77
Figure 12-2: Bongará Geological and Structural Map Projected on Topography	78
Figure 12-3: Geological Cross Section of Karen-Milagros Domain	79
Figure 12-4: Oblique View of Mineral Domains	80
Figure 12-5: Map of Drillholes by Company	83
Figure 12-6: Locations of Low-Precision Drillhole Collar Surveys	84
Figure 12-7: Assay statistics for Zn in logged oxide at 0% Zn threshold (left) and 3% Zn threshold (right)	86
Figure 12-8: Assay statistics for Pb in logged oxide at 0% Zn threshold (left) and 3% Zn threshold (right)	87
Figure 12-9: Assay statistics for Ag in logged oxide at 0% Zn threshold (left) and 3% Zn threshold (right)	88
Figure 12-10: Histogram and Cumulative Probability Plot for Zn	89
Figure 12-12: Histogram and cumulative probability plot for Ag	90
Figure 12-13: Histogram of thicknesses before (left) and after (right) compositing the samples, at intervals of 1m	91
Figure 12-14: Example variograms in N-S/vertical (red), N90°/20° (black) and N270°/70° (purple) directions for Zn, Pb, Ag and Oxide, Sulfide, Mixed in high-angle domains	95
Figure 12-15: Example variograms in the horizontal direction for Zn, Pb, Ag and Oxide, Sulfide, Mixed in flat manto domains	96
Figure 12-16: Block model cross section showing mineral domains in original position (bottom) and unfolded to a fixed-elevation (top)	99
Figure 12-17: Distribution of Zn grades (%) in Plan View (top) and orthogonal view (bottom)	101
Figure 12-19: Distribution of Ag grades (g/t) in Plan view (top) and Orthogonal View (bottom)	103
Figure 12-20: Distribution of Oxide material types in Plan View (top) and Orthogonal View (bottom)	104
Figure 12-21: Index Map of Block Model Cross Sections	106
Figure 12-22: NE Cross-Section of Zn Composites and Block Grades in the San Jorge Area Looking NW (Az 330°)	107
Figure 12-23: NE Cross-Section of Zn Composites and Block Grades in the San Jorge Area Looking NW (Az 330°)	108
Figure 12-24: ENE Cross-Section of Zn Composites and Block Grades in the Karen-Milagros Area Looking NW (Az 347°)	109
Figure 12-25: Swath Plot of Zinc% by Northing showing model blocks (green) compared to composites (orange) with model tonnage (blue)	111
Figure 12-26: Swath Plot of Lead% by Northing showing model blocks (green) compared to composites (orange) with model tonnage (blue)	112
Figure 12-27: Swath Plot of Silver g/T by Northing showing model blocks (green) compared to composites (orange) with model tonnage (blue)	113

Figure 12-28: Swath Plot of Zinc% by Elevation showing model blocks (green) compared to composites (orange) with model tonnage (blue)	114
Figure 12-29: Swath Plot of Lead% by Elevation showing model blocks (green) compared to composites (orange) with model tonnage (blue)	115
Figure 12-30: Swath Plot of Ag g/T by Elevation showing model blocks (green) compared to composites (orange) with model tonnage (blue)	116
Figure 12-31: Comparison of numerical (search pass) classification (left) and final "geologic" classification (right) in San Jorge domain	118
Figure 12-32: Comparison of numerical (search pass) classification (left) and final "geologic" classification (right) in Karen-Milagros domain	118
Figure 12-33: Plan View of Resource Classification	120
Figure 12-34: Grade-Tonnage Curve Based on ZnEq%	123

Appendices

Appendix A: Certificates of Qualified Persons

Introduction (Item 2)

1.1

Terms of Reference and Purpose of the Report

This report was prepared as a National Instrument 43-101 (NI 43-101) Technical Report for Solitario Exploration and Royalty Corp. (Solitario) by SRK Consulting (U.S.), Inc. (SRK). The quality of information, conclusions, and estimates contained herein is consistent with the level of effort involved in SRK’s services, based on: i) information available at the time of preparation, ii) data supplied by outside sources, and iii) the assumptions, conditions, and qualifications set forth in this report. This report is intended for use by Solitario subject to the terms and conditions of its contract with SRK and relevant securities legislation. The contract permits Solitario to file this report as a Technical Report with Canadian securities regulatory authorities pursuant to NI 43-101, Standards of Disclosure for Mineral Projects. Except for the purposes legislated under provincial securities law, any other uses of this report by any third party is at that party’s sole risk. The responsibility for this disclosure remains with Solitario. The user of this document should ensure that this is the most recent Technical Report for the property as it is not valid if a new Technical Report has been issued.

This report provides mineral resource estimates, and a classification of resources in accordance with the Canadian Institute of Mining, Metallurgy and Petroleum Definition Standards for Mineral Resources and Mineral Reserves reporting: CIM Definition Standards, November 27, 2010 (CIM). It provides the first NI 43-101 Mineral Resource Statement for the Bongará Zinc Project, located in Amazonas Department, Peru. Mineral Resource estimation for the Bongará deposit was conducted by Votorantim in August, 2013 and reported by Mineral Resources Management (MRM), an internal resource modeling group of Votorantim, in December of 2013 (Votorantim, 2013b). In April of 2014, SRK was contracted by Solitario to audit the MRM resource estimate and prepare a Technical Report on Resources compliant with the guidance of NI 43-101.

1.2

Qualifications of Consultants (SRK)

The Consultants preparing this technical report are specialists in the fields of geology, exploration, mineral resource and mineral reserve estimation and classification, underground mining, geotechnical, environmental, permitting, metallurgical testing, mineral processing, processing design, capital and operating cost estimation, and mineral economics.

None of the Consultants or any associates employed in the preparation of this report has any beneficial interest in Solitario. The Consultants are not insiders, associates, or affiliates of Solitario. The results of this Technical Report are not dependent upon any prior agreements concerning the conclusions to be reached, nor are there any undisclosed understandings concerning any future business dealings between Solitario and the Consultants. The Consultants are being paid a fee for their work in accordance with normal professional consulting practice.

The following individuals, by virtue of their education, experience and professional association, are considered Qualified Persons (QP) as defined in the NI 43-101 standard, for this report, and are members in good standing of appropriate professional institutions. The QP’s are responsible for specific sections as follows:

Walter Hunt, CPG is the QP responsible for Sections 2, 4, 18 and 21;

Chris Sheerin, R-SME is the QP responsible for Section 11;

J.B. Pennington, CPG is the QP responsible for Sections 12, 23 and 24;

Brooke J. Miller, CPG is the QP responsible for Sections 1, 3, 5-10, 13-17, 19, 20, 22, 25 and 26; and

James Gilbertson, CGeol is the QP responsible for the site visit, inspection of geological sampling and data collection practices, and review of resource estimation practices.

1.3

Details of Inspection

James Gilbertson, C. Geol., of SRK Exploration Services (U.K.), visited the Bongará Project site and core storage facility in Shipasbamba, Peru on May 5 to 7, 2014. This trip included a follow-up visit to Votorantim’s Lima, Peru office on May 9, 2014. Mr. Gilbertson is a Chartered Geologist in the Geological Society of London, and a Qualified Person in the discipline of resource geology, according to NI 43-101 requirements.

1.4

Sources of Information

The sources of information include data and reports supplied by Solitario personnel and representatives of Votorantim Metais (Votorantim), Solitario’s joint venture partner in the Bongará Zinc Project (Project) as well as documents cited throughout the report and referenced in Section 25.

1.5

Reliance on Other Experts (Item 3)

The Consultant’s opinion contained herein is based on information provided to the Consultants by Solitario and Votorantim throughout the course of the investigations.

1.6

Effective Date

The effective date of this report is June 5, 2014.

1.7

Units of Measure

The metric system has been used throughout this report. Tonnes are metric of 1,000 kg, or 2,204.6 lb. All currency is in U.S. dollars (US$) unless otherwise stated.

Property Description and Location (Item 4)

Information in Section 2 of this report is from the 2013 Votorantim report on Bongará Mineral Resources. Other references are cited as appropriate.

2.1

Property Location

The Bongará Zinc Project (the Project) is a mineral exploration project comprised of sixteen contiguous mining concessions, covering approximately 12,600 hectares. The concession titles are in the names of Minera Bongará and Votorantim Metais and are subject to the Minera Bongará joint venture agreement between Solitario and Votorantim.

The Project is located in the Eastern Cordillera of Peru at the sub-Andean front in the upper Amazon River Basin. It is within the boundary of the Shipasbamba community, 680km north-northeast of Lima and and 245 km northeast of Chiclayo, Peru, in the District of Shipasbamba, Bongará Province, Amazonas Department (Figure 2-1). The Project area can be reached from the coastal city of Chiclayo by the paved Carretera Marginal road. The central point coordinates of the Project are approximately 825,248 East and, 9,352,626 North (UTM Zone 17S, Datum WGS 84). Elevation ranges from 1,800 meters above sea level (masl) to approximately 3,200 masl. The climate is classified as high altitude tropical jungle in the upper regions of the Amazon basin. The annual rainfall average exceeds 1 m with up to 2 m in the cloud forest at higher elevations.

Figure 2-1: Project Location Map

2.2

Mineral Titles

The mineral concessions granted by the Peruvian government that comprise the Project land position (Property) are listed in Table 2.2.1 and shown in Figure 2-2. According to Peruvian law, concessions may be held indefinitely, subject only to payment of annual fees to the government. Annual concession fees as required by law are paid annually to the Peruvian government. When this study was initiated, concession payments were current, with 2013 fees of $98,600 paid on May 31, 2013. Concession fees for 2014 were due for payment by May 31, 2014 in accordance with Table 2.2.1.

Table 2.2.1: List of Mineral Claims

Concession Name	Number	Claim Date	Hectares	2014 Holding Fees (US$)	District	Province	Department
BONGARA CINCUENTICINCO	10233396	8/7/1996	1000	$23,000.00	SHIPASBAMBA	BONGARA	AMAZONAS
BONGARA CINCUENTICUATRO	10233296	8/7/1996	600	$13,800.00	SHIPASBAMBA	BONGARA	AMAZONAS
BONGARA VEINTISIETE	10783595	6/26/1995	300	$6,900.00	SHIPASBAMBA	BONGARA	AMAZONAS
DEL PIERO CINCO	10000306	1/3/2006	1000	$9,000.00	SHIPASBAMBA	BONGARA	AMAZONAS
DEL PIERO CUATRO	10000206	1/3/2006	500	$4,500.00	SHIPASBAMBA	BONGARA	AMAZONAS
DEL PIERO DOS	10338405	11/2/2005	600	$5,400.00	FLORIDA	BONGARA	AMAZONAS
DEL PIERO SEIS	10204507	3/26/2007	1000	$9,000.00	CAJARURO	UTCUBAMBA	AMAZONAS
DEL PIERO TRES	10338605	11/2/2005	700	$6,300.00	SHIPASBAMBA	BONGARA	AMAZONAS
DEL PIERO UNO	10338505	11/2/2005	1000	$9,000.00	FLORIDA	BONGARA	AMAZONAS
VM 42	10190507	3/21/2007	1000	$9,000.00	SHIPASBAMBA	BONGARA	AMAZONAS
VM 74	10193707	3/21/2007	1000	$9,000.00	SHIPASBAMBA	BONGARA	AMAZONAS
VM 75	10193807	3/21/2007	1000	$9,000.00	SHIPASBAMBA	BONGARA	AMAZONAS
VM 94	10045708	1/28/2008	900	$2,700.00	FLORIDA	BONGARA	AMAZONAS
VM 95	10045808	1/28/2008	500	$1,500.00	FLORIDA	BONGARA	AMAZONAS
VM 97	10046008	1/28/2008	1000	$3,000.00	SHIPASBAMBA	BONGARA	AMAZONAS
VM 98	10046108	1/28/2008	500	$1,500.00	SHIPASBAMBA	BONGARA	AMAZONAS
TOTAL			12600	$122,600.00

Figure 2-2: Map of Mineral Claims

2.2.1

Nature and Extent of Issuer’s Interest

The Project is controlled by Minera Bongará S.A., a subsidiary of Solitario, and is subject to a joint venture agreement with Votorantim since 2006.

On August 15, 2006, an Agreement Letter was signed between Solitario, Minera Bongará (a wholly owned subsidiary of Solitario) and Votorantim. The Letter defined the commitment of Votorantim to fund U.S. $ 1.0 MM in an annual mineral exploration program, which began in late October 2006.

On March 24, 2007, a definitive agreement superseding the Letter Agreement was signed between the Companies. This definitive agreement (Agreement) provides that the project interest owned by Votorantim and Solitario will be held through the ownership of shares in the joint operating company Minera Bongará, which controls 100% of the mineral rights and assets of the project.

Solitario currently owns 100% of the shareholding interest in Minera Bongará. Votorantim can earn up to 70% in the joint operating company through the funding of an initial $1.0M exploration program (completed), by funding annual exploration and development expenditures and by making cash payments of $100,000 on August 15, 2007 (completed) and $200,000 on subsequent anniversaries of that date. Votorantim is the operator of the Project and is responsible for keeping the property in good standing. The option to earn 70% interest can be exercised by Votorantim at any time by pledging to start the project's production based on a completed feasibility study. Votorantim has further agreed to finance Solitario's 30% participating interest to production through a loan facility from Votorantim to Solitario. Solitario will repay this loan from 50% of Solitario's cash flow distributions from the joint operating company.

2.2.2

Property and Title in Peru

Mining in Peru is governed by the General Mining Law, which specifies that all mineral assets belong to the federal government. Mining concessions granted to individuals or other entities authorize the title holder to perform all minerals related activates from exploration to exploitation and, once titled, are irrevocable for so long as the fees are paid to the federal government on time. A provisional claim is applied for and title is granted if no other claim exists over the same area. A claim can only be granted in multiples of a quadricula, which is a 100 hectare plot, up to a maximum size of 1000 hectares. No monumentation of the claim boundary in the field is necessary.

Annually a payment of US$ 3.00 per hectare ($1.00 for a “small miner”) must be made by the end of June to the Ministry of Energy and Mines (MEM) or the claim is automatically forfeited. Any claim not in commercial production exceeding a pro-rated average of $100 per hectare for any year after the sixth anniversary incurs a penalty payment of US$ 6.00 added to the annual payment. If, by the 12^th anniversary, commercial production has not been achieved then the penalty increases to US$ 20.00. The penalties are waived if the title holder shows that investments for each claim exceed ten times the value of the penalty for any given year.

Concessions are real assets and are subject to laws of private property. Foreign entities have the same rights as Peruvians to hold claims except for a zone within 50 km of international borders. Title holders have a right of access and development of minerals but an agreement is required with private property surface rights owners and formalized “Communities”. To ratify an agreement with a Community a majority of all members must vote in favor of the agreement as written. A recently issued law (as modified) also requires formal consultation with indigenous tribes in certain areas.

2.3

Royalties, Agreements and Encumbrances

Peru imposes a sliding scale net smelter return royalty (NSR) on all precious and base metal production of 1% on all gross proceeds from production up to $60,000,000, a 2% NSR on proceeds between $60,000,000 and $120,000,000 and a 3% NSR on proceeds in excess of $120,000,000. No other royalty encumbrances exist for the Project.

Corporate income tax in Peru is charged at a flat rate of 30%. However, mining companies must also pay an additional tax varying from 2 to 8.4% of net operating profit.

2.4

Environmental Liabilities and Permitting

Class I permits require little more than a notification process for approval. Class II drilling permits require an environmental impact declaration (DIA), a permit for harvesting trees (if applicable), an archeological survey report (CIRA), a water use permit (ALA) and a Closure Plan.

Many of the baseline studies required for mining have been completed by Votorantim.

2.4.1

Required Permits and Status

Votorantim has filed applications for and received Class II permits for various phases of the Project and has filed and received the required associated permits. The Project is in compliance with all permitting requirements necessary for undertaking planned activities relating to exploration.

Specific authorizations, permits and licenses required for future mining include:

EIA (as modified during the mine life);

Mine Closure Plan and Final Mine Closure Plan within two years of end of operation;

Certificate of Nonexistence of Archaeological Remains;

Water Use License (groundwater and/or surface water);

Water construction authorization;

Sewage authorization;

Drinking water treatment facility license;

Explosives use license and explosives storage licenses;

Controlled chemicals certificate;

Beneficiation concession;

Mining authorization;

Closure bonding; and

Environmental Management Plan approval.

2.5

Other Significant Factors and Risks

There are no known significant factors or risks affecting the current status of the Project that are not discussed herein.

Accessibility, Climate, Local Resources, Infrastructure and Physiography (Item 5)

3.1

Topography, Elevation and Vegetation

The Project area elevation ranges between 1,800 and 3,200 masl, with areas of steep topography consisting of prominent escarpments and deep valleys. Dense jungle or forest vegetation covers the Project area, as shown in Figure 3-1.

3.2

Climate and Length of Operating Season

The climate at the Project is high altitude tropical jungle. The annual temperature at elevations between 1,000 masl and 2,000 masl averages around 25°C. Most precipitation occurs during the rainy season, between November and April. The annual rainfall average exceeds 1 m with up to 2 m in the cloud forest at higher elevations. Although exploration can continue year-round, surface exploration is difficult during the rainy season when visibility hampers helicopter supported programs and muddy conditions hinders ground travel. The completion of a road into the Project planned for 2014 will aid in facilitating field work during the rainy season.

3.3

Sufficiency of Surface Rights

The Project concession package provides legal basis for entry, exploration and mining. However, agreements are required with local surface rights owners prior to surface disturbing activities.

3.4

Accessibility and Transportation to the Property

The access routes to the town of Pedro Ruiz near the Bongará Project area, as well as the distance and road conditions are summarized in Table 3.4.1.

Table 3.4.1: Distance and Travel Time to Bongará Project from Lima, Peru

Route	Distance (km)	Travel time (hours)	Access
Lima-Chiclayo	800	1h 20’	air
Lima-Chiclayo	800	10h	asphalt
Chiclayo-Pedro Ruiz Gallo	300	6h	asphalt
Total		10h	air
Total		1 ½ days	ground

Figure 3-1: Photograph of the Bongará Project Area

3.5

Infrastructure Availability and Sources

The Project area has little existing infrastructure with only an access road under construction and a number of primitive camps and drill pads (Figures 3-2 and 3-3). Drilling has been accomplished using helicopter support from the village of Shipasbamba which lies 10 km to the southeast. The Project core shed and sample storage facility is located in Shipasbamba.

3.5.1

Proximity to Population Center

The Project has an office in Pedro Ruiz and a core shed and heliport located in the town of Shipasbamba nearer the deposit. No services are available in Shipasbamba. Drill sites, field camps and underground workings are located 10 km northwest of Shipasbamba. The small community of Florida is 1 to 2 km south of the drill camps on the foot trail from Tingo to the Project. Florida is a one to two hour walk from the largest field camp at El Roso. The road currently under construction to connect the drill camps and Florida is approximately 60% complete.

Pedro Ruiz is the nearest town with commercial service including retail, hotels, restaurants and maintenance services. The nearest largest city with air service is Chiclayo, a coastal port city or Tarapoto, a port city on the Amazon River approximately five hours by road. A paved air strip is available for private aircraft at Bagua Grande two hours from Pedro Ruiz on the Carretera Marginal road.

The small population near the Project is supported by subsistence farming. Saleable crops include coffee, rocoto pepper, yucca, fruit and vegetables. Cedar trees are also harvested and used in local construction.

3.5.2

Power

The towns within 30 km of the Project have electrical service sufficient to support local usage only. The Olmos Hydroelectric Project located 250 km west of the Property in the Lambayeque Region of Peru is under construction. When operational, Olmos will supply 100 MW of power through the Bagua/Jaen power stations. This is planned for eventual expansion to 650 MW. A high tension power line from the site will parallel the highway and pass within 12 km of the Property.

Three sites along the Utcubamba River are under study by the Peruvian government for installation of a hydroelectric facility. The most prospective of these possible locations (Tingo I) is 8 km from the project and has a potential capacity of over 200 MW. In the absence of the construction of this plant a smaller microhydroelectric plant could be installed for local and Project use. Such small hydroelectric projects are often supported by national government grants to promote electrification of rural areas.

If no hydroelectric power is available, then diesel generated power is the only other practical power option for the site.

3.5.3

Water

There are several streams on the Property with year-round flow that would be more than adequate to support a mining operation.

Figure 3-2: Project Access Road

Figure 3-3: Photograph of Drilling Camp at Project Site

3.5.4

Mining Personnel

No trained mining personnel reside near the Project. Untrained labor is readily available from local communities where few employment opportunities exist. Peru is a mature mining country with a mobile workforce. Abundant trained labor is present in all categories of mining throughout Peru.

3.5.5

Potential Mine Infrastructure Areas

Potential sites for mine infrastructure, including a processing plant, tailings impoundment and waste rock storage are located east of the San Jorge deposit. A schematic diagram of planned infrastructure is shown in Figure 3-4.

Figure 3-4: Potential Mine Infrastructure Location

History (Item 6)

4.1

Prior Ownership and Ownership Changes

In 1996, Cominco Ltd. formed a joint venture partnership (JV) with Solitario. This agreement was terminated in 2000 and Solitario retained ownership of the property.

In 2006, Votorantim and Solitario formed a JV for the exploration and possible development of the property.

4.2

Previous Exploration and Development Results

In 1993 through 1995, Solitario executed a program of pitting and drilling at the previously known Mina Grande and Mina Chica oxide zinc prospects located 18 km northeast of the Florida Canyon (Project) area (Figure 5-1). Solitario subsequently identified the Crystal prospect nearby and other zinc occurrences in the general area. The Florida Canyon zinc deposit was located through follow-up of an anomaly generated during a regional program of stream sediments in 1994.

In 1997 to 1999, Cominco Ltd. completed various types of field work including geologic mapping, geophysical surveys, surface sampling, and diamond drilling. The scope of these programs is summarized below.

Geologic mapping at 1:1,000 scale covered 352 hectares in the Project area. Mapping was conducted within Florida Canyon and its tributaries aided by cut trails. Mapping has been validated by Votorantim;

Known mineralized outcrops in the Project area were cleared and sampled and a total of 347 rock chip channel samples were collected. This sampling consisted of channels with individual samples of thicknesses up to 2.0 m at non-regular spacing;

Sediment sampling of major drainages and streams was completed with consistent 500 m spacing along the drainages;

Soil samples were collected along topographic contour lines spaced vertically 50 m apart but with irregular lateral spacing. Part of this soil sampling followed the crests of hills, especially in the western part of Florida Canyon, mainly to identify mineralized linear structures. A total of 600 samples were collected;

Diamond drilling between 1997 and 2000 totaled 82 holes and 24,781 m; and

An Induced Polarization (IP) geophysical survey in 3 lines covered 5.2 linear km. Two lines were located along the drainages A and B of the northern part of Florida Canyon with dipole-dipole spacing at 150 m, and a third line with dipole-dipole spacing a = 100 m along the southern sector of the Sam Fault target. Cominco also surveyed 6.5 km of radial lines from holes FC-41 and FC-47, drilled in 1999. These areas are shown in Figure 4-1.

Exploration completed by Votorantim consists of surface diamond core drilling, geologic mapping, surface outcrop sampling, underground exploration drifting and underground drilling. As of August 15, 2013, Votorantim had completed 404 diamond drillholes which, when combined with the previous

drilling of Cominco, totals 117,260 m. Figure 4-2 shows drilled length by program, including 4,047 m of oriented core geotechnical drilling in 13 drillholes. Additional work completed by Votorantim includes metallurgical testing, infrastructure design and construction, and strategic planning.

4.3

Historical Mineral Resource and Reserve Estimates

No mineral resource or reserve estimates have been released by Solitario, Cominco or Votorantim prior to this report.

4.4

Historical Production

There has not been any commercial mining in the Project area. The only underground excavation has been 700 m of underground drifting by Votorantim to provide drill platforms at the San Jorge area.

A subsidiary of Hochschild Mining PLC tested open pit mining for a short time at the Mina Grande deposit near the village of Yambrasbamba, 18 km northeast of Florida Canyon, where Solitario had previously defined an oxidized zinc resource by pitting.

Figure 4-1: Regional Geologic Map

Figure 4-2: Project Drilling History

Geological Setting and Mineralization (Item 7)

Information presented herein is derived from material provided by Votorantim and Solitario, including Cominco reports, and was verified and augmented by SRK during a site visit in May 2014.

5.1

Regional Geology

5.2

Local Geology

5.2.1

Lithology and Stratigraphy

A schematic stratigraphic column developed by Cominco and refined by Votorantim shows the major geologic rock units in the Project area (Figure 5-1). The basement rocks are the Pre-Cambrian Marañón Complex consisting of gneisses, mica-schists, phyllites and quartzites. These are overlain by an angular unconformity with the overlying Permo -Triassic Mitu Group composed of a sequence of redbeds consisting of polymictic conglomerates interspersed with beds of fine-grained sandstones.

Overlying the Mitu Group is the Pucará Group of Triassic - lower Jurassic age, which hosts the zinc-lead-silver mineralization of the Bongará Project. The Pucará Group is divided into the Chambara Formation at the base, the Aramachay Formation in the middle and the Condorsinga Formation on top.

The Chambara formation has an approximate thickness between 650 m and 750 m in the project area, and consists of crinoidal packstone, wackstones and rudstones. It is divided into three members in the Florida Canyon vicinity; from bottom to top, they are Chambara 1, Chambara 2 and Chambara 3. The bulk of known zinc mineralization is hosted in Chambara 2. The stratigraphy between the distinctive Coquina (CM) and Intact Bivalve (IBM) paleontological marker horizons in Chambara 2 define a sequence of permeable higher energy facies within the Chambara 2 that control much of the especially strong dolomitization within the sequence.

The Aramachay formation lies concordantly on the Chambara with a variable thickness between 150 m and 250 m, consisting of a monotonous sequence of black and limonitic lutites and bitumen with thin interbedded nodular limestones. The Condorsinga Formation concordantly lies above, with restricted outcrop distribution due to erosion. It consists of calcareous gray mudstones with thicknesses varying between 150 m and 300 m.

The Corontochaca Formation of Upper Jurassic age lies unconformably on the Pucará Group. It outcrops in erosional remnants and is locally more than 300 m thick consisting of a package of monotonous oligomictic and polymictic fluvial calcareous sediments and colluvial limestone breccias with local fragments of Paleozoic or Precambrian fragments.

The Goyllarisquizga Formation occurs in angular unconformity over the Corontochaca and Pucará Group and is present mainly in the eastern and western sections of the Project area. It consists of poorly sorted yellowish to white sandstone deposited in coastal marine to fluvial-deltaic environments. It also contains some thin, lenticular intercalations of siltstones and mudstones whitish to reddish. The thickness ranges from 300 to 400 m.

Figure 5-1: Project Area Stratigraphic Column

5.2.2

Structure

The following discussion of structural geology in the Project area is adapted in part from an internal report by Cominco (2000).

The structure at Florida Canyon is dominated by a N50º-60ºW trending domal anticline (or doubly-plunging anticline) as defined from the base of Chambará 2 structural contour map in Figure 5-2. This domal anticline is cut on the west by the Sam Fault and to the east by the Tesoro-Florida Fault. The Sam Fault, which has been defined by drilling, has a north-south to northeast trend and a steep 80 to 85º westerly dip. The Sam Fault has an apparent scissor dip-slip displacement of >120 m in the north and <50 m in the south. To the south its trace is uncertain and complicated by northwest and possibly east-west structures. This appears to have been a long-lived structure, with its last strike-slip displacement being dextral. A facies change in the Chambará 2 from high energy to the east of the fault to low energy to the west many be due to original depositional features during growth fault formation that has important exploration implications.

At Florida Canyon there are also well defined northwest and northeast fracture systems, which appear to have important controls on the location of mineralization. Mineralized structures occur in conjugate fractures, with N10º-50ºE trends present at a number of mineralized surface outcrops while trends of N50º-80ºW are identified at other showings. Mineralization of mantos within the Karen-Milagros area appears to be preferentially controlled by northeast feeder structures.

The Tesoro-Florida Fault defining the eastern limits of most drilling to date is a N15º-30ºW trending structure, part of a regional lineament, and defined by an escarpment. It is interpreted to have a steep dip, with its sense of motion not having been defined, but with the east block being structurally lower than the west block, which results in significantly deeper drilling on the east fault block to reach the Chambará 2 stratigraphy. Because most of the work has concentrated further west on the San Jorge, Karen Milagros and Sam Fault areas there is little information on the Tesoro-Florida Fault, but it likely has similarly complex splays as the Sam Fault and may be, like the Sam fault, a controlling feeder for untested mineral potential in the eastern area.

At both the Karen-Milagros and San Jorge areas, feeder structures have an important control on the mineralized mantos but also represent a significant portion of the resource as steeply dipping structural fillings and replacement. The displacement along these structures is not large although the exact throw is often difficult to ascertain due to the strong alteration and later mineralization. The interpretation of displacement is further obscured by likely subtle variation in thickness and lithology of local stratigraphic units on either side of structures due to growth faulting.

Pre-mineral karsting also played a role in controlling mineralization along with simple structural filling and passive replacement adjacent to conduits. Replacement of karst fragments and cave sediments are commonly observed in larger structurally controlled mineralized bodies. The configuration of mineralized structures as they control and merge with manto replacements often take the form of Christmas–tree breakthrough structures and will likely be shown to represent a larger proportion of the resource as more horizontally oriented drilling from underground workings supplants the dominantly high angle surface drilling performed to date.

Post mineral structure and karsting overprints earlier structural trends and controls in part oxidized remobilized mineralization.

Figure 5-2: Base of Chambara 2 Contour Map

5.2.3

Alteration

The alteration and solution overprints in the Florida Canyon deposit include dolomitization, pseudobrecciation and karstification, mainly affecting the limestones of Chambara 2 and locally Chambara 1 and 3. Dolomitization and karstification occurred in multiple events spatially overlapping the structural corridors Sam, San Jorge and Karen-Milagros. Dolomitization was an important control on the movement of mineralizing fluids and has been studied and logged in detail throughout all of the drilling campaigns. It is also modeled in this study as a limiting constraint on mineralization.

The alteration halo is open in all directions and is especially pervasive in the stratigraphic interval lying between the paleontological marker horizons “CM” (coquina marker) and “IBM” (intact bivalve marker) of the Chambara 2 formation. A sample from the Coquina Marker unit is shown in Figure 5-3. The alteration halo is composed mostly of medium and coarse-grained crystalline dolomite replacing calcareous packstone, rudstones, floatstones and wackestones, as shown in Figure 5-4 and Figure 5-5. Mostly the dolomitic rudstones, and locally the packstones, transform laterally when in proximity of faults and major fractures (corridors Sam, San Jorge and Karen-Milagros) to mineralized pseudobreccias and karst structures. There is great complexity in the alteration events, but they are both stratigraphically and structurally controlled and are overprinted solution features resulting from penetrative migration of fluids.

In the Project area, the three prospective corridors for economic mineralization studied in detail are San Jorge, Karen-Milagros, and Sam. In these areas, dolomitization and karsting is best developed in proximity to faulting and fracturing associated with each structural zone. In turn, these structures provided access for the altering fluids to bleed laterally into stratigraphic horizons with more permeable sedimentary characteristics.

Figure 5-3: Photograph of Coquina Marker Horizon in Chambara 2 Unit

Figure 5-4: Photograph of Strongly Dolomitized Core with Karst Dissolution

Figure 5-5: Photograph of Dolomitized Packstone with Pseudobreccia Texture

5.2.4

Mineralization

The zinc-lead-silver mineralization of the Bongará deposit occurs as sulfides hosted in dolomitized zones of the Chambara 2 Formation. Dolomite paragenesis and later sulfide mineralization are controlled by a combination of porosity, permeability and structural preparation. Metals occur in sphalerite and lesser galena, which contains silver. Minor mineralization is hosted in limestones, but the bulk of sphalerite and galena is hosted in dolomite.

In a number of core samples, the mineralization has very sharp contacts along the dolomitization boundary. Characteristic mineralization textures include massive and disseminated mantos, mineralization in dissolution breccias, collapse breccias and pseudobreccias. The different breccias and vein types are structurally controlled by faults of north-south and northeast-southwest direction. Figure 5-6 shows a manto outcrop containing massive sphalerite and galena.

The mineralization at Florida Canyon is characterized by the presence of sphalerite, galena and locally pyrite. Sulfide replacements occur in dolomitized limestone of variable grain sized and in solution breccias with white dolospar and lesser amounts of late generation calcite, as shown in Figure 5-7 and Figure 5-8. Pyrite content is generally low, with percentages averaging less than 2% by volume. Sphalerite in mineralized sections has variable grain size from 0.1 to greater than 5 mm, with colors ranging from dark brown through reddish brown to light brown. It occurs as individual crystals or in massive form, sometimes displaying colloform textures with bands of slightly differing color zoning, indicators of polyphase hydrothermal deposition (Figure 5-9).

Early fine-grained sphalerite has evidence of later deformation and reactions to secondary mineralizing fluids. A second phase of more massive sphalerite mineralization is observed within the core of the deposit. These crystals are coarse-grained, regular, euhedral and show very little evidence of any post-depositional deformation. The sphalerite is contemporaneous with fine to coarse grained galena and is often overprinted with a later stage coarse-grained, euhedral galena.

The presence of significant amounts of zinc oxides to considerable depths is due to syngenetic oxidation, with later contributions of basin-derived connate water and movement of rainwater through fractures that leached the limestones and formed significant karst cavities.

Figure 5-6: Photograph of Nancy Outcrop

Figure 5-7: Photograph of Mineralized Dolomite Packstone Pseudobreccia

Figure 5-8: Photograph of Heterolithic Collapse Breccia

Figure 5-9: Photograph of Zoned Polyphase Sphalerite from Drillhole V297, 250.0m

5.3

Property Geology

The areas of current exploration interest are the Karen/Milagros, San Jorge and Sam Fault deposits. These mineralized zones are hosted in the dolomitized Chambará 2 sub-unit of the Pucará Group carbonates, bracketed by the Coquina and Intact Bivalve Marker beds. Geologic mapping and modeling includes refining the extents of Chambará 2, and further defining the steeply dipping feeder structures to predict additional zinc-lead-silver mineralization. The outcrop geology of the Project area is shown in Figure 5-10, with emphasis on the Chambará Formation.

Figure 5-10: Bongará Project Geologic Map

5.4

Significant Mineralized Zones

Local and regional geologic mapping, geologic drillhole logs, and the dome-shaped geometry of the Florida Canyon deposit suggest the deposit is hosted in a broad anticline structure. Florida Canyon is the collective name of the deposits in the Project area, and includes the Karen-Milagros, San Jorge, Sam Fault zones and similar mineralized strata between these areas.

The sphalerite and galena mineralization of economic abundance is hosted in a gently folded and faulted carbonate sequence. Sulfide mineralization preferentially occurs in dolomitized areas of the Chambara 2 unit, between the fossiliferous Coquina and Intact Bivalve marker beds. Diagenetic and mineralizing fluids migrated along structures and stratigraphic units with favorable porosity and permeability.

Modeled manto zones are between 1m and 9m thick and occur over an area of about 1 by 3 km and are open in all directions. Unmineralized gaps exist within the mineralized manto zones, as is typical for hydrothermal replacement deposits. Irregular steeply dipping replacement bodies also occur, frequently at the intersection of vein-like feeder structures and in karst-controlled mineralization.

Mineralization outcrops locally in a number of areas, and have been drilled at depths of up to about 450 m below ground surface. Figure 5-11 is a west-facing cross section of the geologic model in the mineralized zone. Zinc mineralization occurs as massive sphalerite (ZnS), and is locally oxidized to smithsonite (ZnCO₃) and hemimorphite (Zn₄Si₂O₇ (OH)₂). Lead occurs in galena (PbS), cerussite (PbCO₃) and anglesite (PbSO₄).

Figure 5-11: Cross Section of the Project Geologic Model

Deposit Type (Item 8)

MVT deposits are hosted in dolomitized limestone, and show cavity-filling or replacement-style mineralization. The characteristic minerals are sphalerite, galena, fluorite, and barite. The host rock may be silicified, and common alteration minerals include dolomite, calcite, jasperoid and silica. MVT deposits are typically spatially extensive, but limited by the permeability of the host rock units. This control makes them appear stratabound. Chemical and structural preparation are the main controls on permeability, and therefore, the extent of fluid migration and metal precipitation (Guilbert and Park, 1986).

6.1

Mineral Deposit

An area of 20 by 100 km extending from Mina Grande to north to 80 km south of the Florida deposit has become the focus of what is an emerging Mississippi-Valley Type (MVT) zinc and lead province, with many surface occurrences and stream sediment anomalies distributed throughout the Pucará Group. The main host rock of zinc and lead occurrences in the mineral district and Project area is dolomitized limestone, which may show karst or collapse breccia textures.

6.2

Geological Model

The current Votorantim genetic model for Bongará sees mineralization being classified as syn-to post tectonic. Specifically, upwelling mineralizing fluids entered the Chambara Formation and precipitated in porous and reactive dolomites with interaction of sulfide and organic ions (H₂S and CH₄) resulting from reaction with overlying evaporitic and bituminous sequences, all channeled by axial planar faults. The schematic mineralization model is presented in Figure 6-1.

Figure 6-1: Mississippi Valley-Type Deposit Schematic Model

Exploration (Item 9)

7.1

Relevant Exploration Work

The focus of Votorantim’s recent exploration work at the Project has been resource definition drilling in the San Jorge and Karen-Milagros areas. The results and methodology are described in Section 8.

In earlier years Cominco and then Votorantim executed detailed surface mapping programs and mineralized outcrop clearing, mapping and sampling. Stream sediment and soil samples were collected and analyzed as described in Section 4.2. Regional exploration programs have been conducted throughout the Mesozoic carbonate belt to the north and south of the Property.

During development of the San Jorge adit, Votorantim completed geologic mapping and chip sampling of the underground workings. Results were applied to the Project geologic model in support of resource estimation and continued exploration drillhole planning.

7.2

Surveys and Investigations

Solitario, Votorantim and Cominco have not completed any additional surveys or other investigations outside of mapping and sampling surface and underground workings as described.

7.3

Sampling Methods and Sample Quality

Sampling of drill core is described in detail in Section 8. Limited soil samples collected were composites of B horizon soils and C horizon when accessible. Stream sediment sampling was conducted using minus 80 mesh samples, ashing and analyzing for a multielement suite by ICP.

Rock sample methodology varied according to location. Grab samples were taken where outcrops were found that showed evidence of dolomitization of carbonate beds. Mineralized outcrops were cleared manually with machetes and shovels and systematically chip channeled. Channels were oriented perpendicular to bedding to most accurately represent stratigraphic thickness. Channel samples were limited to 2 km in length by Cominco and one meter by Votorantim. Most of the chip channel sampling of higher grade mineralization has been conducted in the Karen Milagros zone and other areas in the central part of the Property where outcrops of mineralization are most common, as illustrated in Figure 7-1.

7.4

Significant Results and Interpretation

Analytical results from soil and rock samples and data from surface geologic mapping have been applied to drillhole planning and the geologic model. To date, no chip channel data has been used in resource modelling but is planned for incorporation into future models.

Figure 7-1: Project Geology with Mineralized Outcrops

Drilling (Item 10)

The database used for modeling and estimation of mineral resources was frozen on August 15, 2013 and includes 486 diamond drillholes, with a total of 117,280.25 m drilled length. Since the previous Resource Estimation for the Project was completed in 2012 (unpublished), Votorantim completed 94 drillholes totaling 13,413 m.

8.1

Type and Extent

All drillholes completed in the Project area are HQ-diameter core (63.5 mm). If poor ground conditions necessitated, the core diameter was reduced to NQ (47.6 mm). Cominco completed a total of 82 drillholes from the current ground surface in the Karen-Milagros and Sam deposit areas, and the San Jorge structural corridor. Votorantim had completed 404 drillholes between 2006 and 2013, from surface or from the San Jorge Adit. The Votorantim drilling is distributed throughout the Project area. All holes mentioned above are included in the geologic modeling and resource estimation database, and shown in Figure 8-1.

Figure 8-1: Geologic Map with Drillhole Locations

8.2

Procedures

All drilling contracted by Votorantim was completed with triple-tube HQ tooling and followed industry standard procedures to ensure sample quality. Surface drilling was executed with a helicopter-supported LD-250 diamond core rig operated by Bradley Bros. Limited. Sermin completed the underground development and also completed drilling from the San Jorge adit with a LM-70 electric diamond core rig.

Drilling was performed on two 12-hour shifts with full 24-hour geological supervision by a Votorantim geologist. The rig geologist role included:

Coordination and communication between the drilling contractor and Votorantim;

Monitoring drilling procedures and inspecting the core extraction for sample quality;

Boxing the core;

Measuring and recording core recovery and Rock Quality Designation (RQD); and

Completing a preliminary geological log.

Downhole surveys were completed with a Reflex EZ-Shot survey tool by the drillers at varying spacing, as summarized in Table 8.2.1. The survey records are stored digitally at the core facility and SRK reviewed them during the 2014 site visit. Drillhole collar locations were surveyed by Votorantim with a GPS-based instrument.

Table 8.2.1: Downhole Survey Data Point Spacing

Drilling Program (Year)	Survey Spacing (m)
2010	100
2011	50
2012 to 2013	20

Source: SRK, 2014

Votorantim completed 13 oriented geotechnical drillholes, totaling 4,046.70 m. In these holes, the recovery was excellent (90% to 100%) with RQD results greater than 75%. RQD is the total length of pieces of core greater than 10 cm long, or with fewer than 10 joints per meter, divided by the total drilled length. A RQD value of 100% indicates there are no natural joints in the rock. Figure 8-2 shows core boxes with recovery and rock quality typical of the core drilled at the Project.

From the drill site, filled core boxes were transported in batches of 14 via helicopter to the drill core logging facility in Shipasbamba (Figures 8-3 and 8-4). These were photographed and fully logged by Votorantim geologists in natural light. During the 2012 to 2013 program, many of the core photographs were taken after the core had been cut for sampling, due to the large quantity of core produced.

Figure 8-2: Photograph of Drillhole V412, 102.4m-107.9m

Figure 8-3: Photograph of Project Core Storage Facility in Shipasbamba

Figure 8-4: Photograph of Interior of Project Core Storage Facility

8.3

Interpretation and Relevant Results

The geologic logging and analytical data were added to the Project database after validation and applied to modeling and resource estimation. Due to the large number of drillholes in the database, and because the modeling and resource estimation are discussed in detail, in Section 12 (Mineral Resources), the recent drilling results by interval are not presented here. According to Solitario representatives, the true thickness of the mineralized intercepts is about 80% of the drilled length, and varies with the orientation of the drillhole.

Votorantim’s documentation of drilling procedures and SRK’s observation of the program indicate that there is little or negligible sampling bias introduced during drilling.

SRK considers the drilling procedures to be appropriate for the geology, conducted according to industry best practice and standards, and the relevant results are sufficient for use in resource estimation.

Sample Preparation, Analysis and Security (Item 11)

9.1

Sampling Methods

Sampling procedures for core drilled on behalf of Cominco are not well-documented. Cominco included assay quality control samples in the analytical programs, but the results were not available to review. The resource classification from these samples is limited because the location and analytical data was not obtained according to current industry standard protocol.

Most of the information in this section pertains to the sampling completed by Votorantim. Available information about sampling completed by Cominco is included if available, and is specified as such. About 20 percent of the holes in the current drillhole database were drilled by Cominco.

9.1.1

Sampling for Geochemical Analysis

After photographing the core and completing geotechnical and geologic logging, a geologist marked the core for sample intervals that averaged 100 cm long. Samples had a minimum length of 30 cm and a maximum of 150 cm, but were defined so that 100 cm samples were maintained as much as possible. Cut lines parallel to the core axis were drawn by the logging geologist, to ensure nearly symmetrical halves and minimal sampling bias relative to any visible mineralization. The core was cut on a rock saw with a 40 cm blade, under supervision of a Project geologist. After the core was cut, both halves were replaced in the core box.

Samples were always taken from the left side of the saw-cut core, double bagged and marked with sample numbers in two places. These were transported in larger bags containing 7 samples each by Mobiltours freight company to the ALS Minerals laboratory in Trujillo or Lima, operated by ALS Minerals. Prior to 2012, analysis was completed in Trujillo. Since then, it has been done in Lima.

Cominco also split the core samples and sampled half for geochemical analysis. Sample breaks were determined by geologic criteria. Cominco core samples were analyzed by Acme Labs, in Lima, Peru.

9.1.2

Sampling for Density Measurement

Specific gravity (SG) measurements were completed on site by Votorantim on every sample from the 2013 drilling program. For previous drilling programs, SG measurements were completed on all mineralized intervals. Three SG measurement methods were used:

Volume displacement;

Hydrostatic; and

A mesh method for broken material.

These techniques were designed and implemented by Inspectorate Services Peru SAC. Votorantim has also performed some density measurements on older Cominco core.

9.2

Security Measures

During the SRK site visit, the observed sample storage was secure, and provided adequate protection from rainfall. Sample security and chain of custody was maintained while the samples were transported from the core shed in Shipasbamba to Lima. Assay certificates are retained in the

Votorantim office in Lima. Analytical data is loaded directly from the laboratory results files to the drillhole database, to minimize the risk of accidental or intentional edits.

9.3

Sample Preparation

ALS Minerals (ALS) in Trujillo or Lima, Peru, completed sample preparation and analysis for all Votorantim core samples. ALS is an independent, global analytical company recognized for quality, and is used by many exploration and mining companies for geochemical analysis. Current certifications and credentials include ISO 17025:2005 Accredited Methods & ISO 9001:2008 Registration in Peru, Brazil, Chile and Argentina (ALS Minerals, 2014a).

Upon delivery at the lab, bar coded sample identification labels were scanned and the samples were registered to the Laboratory Information Management System (LIMS). Samples were weighed, and then air-dried in ambient conditions. Excessively wet samples were dried in an oven at a maximum 120^°C. The sample preparation and analysis procedures used are summarized in Table 9.3.1. Specific analytical procedures and method detection limits for elements in the suite are reported in Table 9.3.2.

After analysis is complete, the remaining coarse reject and pulp samples are returned to the Bongará core shed for storage.

Cominco analyzed samples with visible zinc or lead mineralization by atomic absorption spectrophotometry. All samples containing greater than 10,000 ppm zinc + lead were then analyzed by wet chemistry and the latter results were reported in the data base.

Table 9.3.1: Analytical Codes and Methods

Procedure Code	Description
Sample Prep
CRU-31	Crush to 70% less than 2mm.
SPL-21	Riffle split off 1kg and retain the coarse reject.
PUL-32	Pulverize split to better than 85% passing 75 microns.
Multi-Element Methods
ME-ICP61, -a	Multi-element Inductively-Coupled Plasma method with Atomic Emission Spectroscopy analysis. Includes 4-acid, "near-total" digestion of 0.5g sample.
(+)-AA62	HF, HNO3, HClO4 digestion, HCl leach and Atomic Absorption Spectroscopy analysis.
(+)-VOL70	Volumetric titration for very high grade samples.
XRF10	X-Ray fluorescence on fused pellet, 5g sample.
Element-Specific Methods
Au-AA23	Gold by fire assay and Atomic Absorption Spectrometry, 30g sample.
Au-AA25	Ore-grade gold by fire assay and Atomic Absorption Spectrometry, 30g sample.
Au-GRA21	Gold by fire assay and gravimetric finish, 30g sample.
Hg-CV41	Trace level mercury by aqua regia and cold vapor/AAS.
Hg-ICP42	High grade mercury by aqua regia and ICP-AES.
In-MS61	Multi-element Inductively-Coupled Plasma method with Mass Spectrometry detection. Includes 4-acid, "near-total" digestion of 0.5g sample.
S-IR08	Total sulfur by Leco furnace.

Source: ALS Minerals, 2014b, compiled by SRK, 2014

Table 9.3.2: Analyzed Elements and Method Detection Limits

Element	Symbol	Method	Unit	Lower MDL	Upper MDL	Overlimit Method	Unit	Lower MDL	Upper MDL	Overlimit Method	Unit	Lower MDL	Upper MDL
Silver	Ag	ME-ICP61	ppm	0.5	100	Ag-AA62	ppm	1	1,500
Aluminum	Al	ME-ICP61	%	0.01	50
Arsenic	As	ME-ICP61	ppm	5	10,000
Barium	Ba	ME-ICP61	ppm	10	10,000	ME-ICP61a	ppm	50	50,000	XRF10	%	0.01	50
Beryllium	Be	ME-ICP61	ppm	0.5	1,000
Bismuth	Bi	ME-ICP61	ppm	2	10,000
Calcium	Ca	ME-ICP61	%	0.01	50
Cadmium	Cd	ME-ICP61	ppm	0.5	1,000	Cd-AA62	%	0.0005	10
Cobalt	Co	ME-ICP61	ppm	1	10,000
Chromium	Cr	ME-ICP61	ppm	1	10,000
Copper	Cu	ME-ICP61	ppm	1	10,000
Iron	Fe	ME-ICP61	%	0.01	50
Gallium	Ga	ME-ICP61	ppm	10	10,000
Potassium	K	ME-ICP61	%	0.01	10
Lanthanum	La	ME-ICP61	ppm	10	10,000
Magnesium	Mg	ME-ICP61	%	0.01	50
Manganese	Mn	ME-ICP61	ppm	5	100,000
Molybdenum	Mo	ME-ICP61	ppm	1	10,000
Sodium	Na	ME-ICP61	%	0.01	10
Nickel	Ni	ME-ICP61	ppm	1	10,000
Phosphate	P	ME-ICP61	ppm	10	10,000
Lead	Pb	ME-ICP61	ppm	2	10,000	Pb-AA62	%	0.001	20	Pb-VOL70	%	0.01	100
Sulfur	S	ME-ICP61	%	0.01	10	S-IR08	%	0.01	50
Antimony	Sb	ME-ICP61	ppm	5	10,000
Scandium	Sc	ME-ICP61	ppm	1	10,000
Strontium	Sr	ME-ICP61	ppm	1	10,000
Thorium	Th	ME-ICP61	ppm	20	10,000
Titanium	Ti	ME-ICP61	%	0.01	10
Thallium	Tl	ME-ICP61	ppm	10	10,000
Uranium	U	ME-ICP61	ppm	10	10,000
Vanadium	V	ME-ICP61	ppm	1	10,000
Tungsten	W	ME-ICP61	ppm	10	10,000
Zinc	Zn	ME-ICP61	ppm	2	10,000	Pb-AA62	%	0.001	30	Zn-VOL70	%	0.01	100
Gold	Au	Au-AA23	ppm	0.005	10	Au-AA25	ppm	0.01	100	Au-GRA21	ppm	0.05	1,000
Indium	In	In-MS61	ppm	0.005	500
Mercury	Hg	Hg-CV41	ppm	0.01	100	Hg-ICP42	%	0.1	10

Source: Votorantim (2014b), translated by SRK

9.4

QA/QC Procedures

Votorantim’s Technical Report (2014b) includes assay quality assurance/ quality control (QA/QC) results available through June 15, 2013. Sample dates in the QA/QC data files are between 2011 and 2013, and no information for prior samples was available. For the 2011 to 2013 drilling programs, assay QC samples were 10.9% of the total samples analyzed. Some programs included duplicate core or coarse reject samples, and/or duplicate analysis of fine pulp samples. Votorantim compiled and analyzed the results from 2011 to 2013 drilling programs, which SRK has reviewed and summarized below. Assay QC results from drilling programs prior to 2011 were not available to include in this report.

9.4.1

Standards

Summaries of the Standard Reference Material (SRM) certified values and analytical results for lead and zinc are shown in Table 9.4.1.1 and Table 9.4.1.2, respectively. The certified Standard Reference Material, ST800044B, was included in the core sample suite, and is highlighted with bold text in the tables. Other, lower-grade reference materials made from Bongará core were also included.

Table 9.4.1.1: Summary of SRM Statistics for Lead

Pb SRM	Mean (ppm)	Standard Deviation (ppm)	Samples	Outliers	Percent Outliers	Bias
STD_RK1	13.4	2.35	127	1	1%	-4.3%
STD_RK2	439.18	17.26	154	2	1%	2.6%
STD_RK3	3149.47	113.00	134	0	0%	-2.9%
ST800044B	18100	500	80	0	0%	0.3%

Table 9.4.1.2: Summary of SRM Statistics for Zinc

Zn SRM	Mean (ppm)	Standard Deviation (ppm)	Samples	Outliers	Percent Outliers	Bias
STD_RK1	22.93	4.32	125	3	2.4%	-4.5%
STD_RK2	452.5	18.62	154	3	2%	2.8%
STD_RK3	2688.13	86.32	134	2	1.5%	-0.4%
ST800044B	33400	1000	80	0	0%	1.8%

Source: Votorantim (2014b), formatted and translated by SRK

Low-grade standards STD_RK1, -2 and -3 are less than economic grade for both zinc and lead. However, the results provide important information on the quality of analytical data across a range of values. The lowest-grade standard, RK1, shows consistent low bias for both lead and zinc (about 4.5% lower than the mean), while RK2 has consistent, but minor, high bias for both elements (about 2.8% higher). Although lead values for RK3 have slightly low bias (-2.9%), zinc values average very close to the mean.

All results for ST800044B were within three standard deviations of the certified value for lead and zinc; all results but two for lead and four for zinc were within two standard deviations of the respective certified values. On average, results were greater than the certified value by 1.8% for zinc and 0.3% for lead, indicating unbiased analytical data.

9.4.2

Blanks

Two types of blank samples were included in the sample suite:

Fine-grained BLK_RK1 (n = 223); and

Coarse-grained BLK_RK1_GR (n = 229).

The fine-grained blank material served as a control on analytical quality, and was not subjected to any stage of the sample preparation process. The coarse blank material was included to identify possibly cross-contamination during sample preparation. Between August 2011 and June 2013, 452 blank samples were analyzed with drill samples. All blank samples but one were less than 7 times the lower method detection limit for zinc, and all were less than 4 times the method detection limit for lead. One sample was greater than 10 times the method detection limit for zinc. The accepted tolerance range for blank samples is up to 10 times the lower method detection limit. Blank sample results from the 2011 and 2012 drilling programs indicate that there was no cross-contamination during sample preparation.

Statistical and graphic analysis of blank sample and previous sample pairs showed that some blank sample results were outside of acceptable limits, caused by “drag” in the ICP instrument. However, the percentage of samples outside of tolerance is less than 5%, and indicates acceptable analytical data quality.

9.4.3

Duplicates

Several types of duplicate samples were included in the 2013 drilling program:

Quartered core samples, to assess the quality of the sampling procedure and identify sample mix-ups;

Coarse rejects (sample preparation);

Pulps (analysis); and

Pulps from previous drilling as blind duplicates (analysis).

A summary of all duplicate sample pairs is shown in Table 9.4.3.1. In the 2011 to 2012 drilling programs, only quartered-core sample duplicates were included.

Table 9.4.3.1: Summary of Duplicate Samples

Type	Program	Pairs (n)
Quarter-core	2011 to 2013	811
Coarse rejects	2013	38
Pulps	2013	76
Blind Pulps	2013	33

Source: SRK, 2014

Votorantim collected a duplicate core sample approximately every 50^th sample interval, on average. These intervals were halved, and then the halves were halved again. Two opposing quadrants of core were sampled separately as the original and duplicate sample. The remaining two quarters of core were retained in the core box.

Starting in 2013, Votorantim included additional types of duplicate samples to assess the quality of each step of sample preparation and analysis. Coarse reject duplicates were collected by the laboratory, by taking a second 1,000 g split from the crushed sample, and pulverizing it separately to

create a second pulp sample. Pulp duplicates are re-analysis of the prepared original pulp. Votorantim specified the pulp duplicate sample intervals and the lab prepared them. Votorantim also included blind duplicate samples of prepared pulps of recent drilling programs, to test the repeatability of analytical results without the lab’s knowledge.

Votorantim analyzed zinc, lead and silver results for all duplicate pair types. The results from each type of duplicate sample showed repeatable results at all stages of sample preparation and analysis.

9.4.4

Actions

Standard and blank sample results indicate accurate lab data free of analytical bias. Duplicate sample results show that sample quality is adequate and the reported results were free of sample mix-ups.

Some improvements, fixes and deployments in the assay QC program were identified in 2013 and are already underway. Votorantim has recently changed assay QC protocols so that:

Each hole starts with a coarse blank and has a blank for every 50 drill samples;

A SRM is inserted for every 20 drill intervals;

A type of duplicate is included for every 20 drill samples, as ¼ core, coarse rejects, pulps, or blind pulps; and

Check analysis at a second independent laboratory was completed for 2010 to 2012 samples at SGS Labs and for 2013 samples at BVI (Inspectorate) labs.

Additional planned quality control measures include:

Generate new standards from Bongará core, and continue using the high grade standard ST800044B; and

Separate about 200 kg of unmineralized material from the Project to create a certified blank.

One or two additional SRM with zinc, lead and silver grades in the range of economic interest should be included in future drilling programs. If possible, these should be matrix-matched to the Project. Coarse blank samples should be adopted in favor of prepared blank samples, to test all phases of sample preparation and analysis.

9.5

Opinion on Adequacy

The assay QC database is organized well and free of errors in the cells that SRK checked. Votorantim maintains the assay QC data well, and analyzes it in real time to address any issues promptly. There were no systematic issues apparent in the results available to review.

SRK considers the sample preparation and analysis procedures, and the QA/QC methods and results to adequately verify the analytical database as sufficient for use in resource estimation.

Data Verification (Item 12)

10.1

Procedures

All analytical data is checked by the on-site and Lima-based geologists before it is added to the database. This includes review of standard, blank and duplicate sample results for outliers, and requesting re-analysis if necessary. Final analytical data is appended to the database by the Sao Paulo office staff after additional verification.

During the site visit by SRK, the geologic database was checked for its consistency to a) logged core, b) logging sheets and sample records and c) database provided to SRK. All aspects of the data capture and storage were seen to be in good order. The core sample library in the core shed (Figure 10-1) helps to make the logged geology consistent.

Drillhole collar locations are verified against topography, and compared with the survey reports. Downhole survey data are reviewed by an on-site geologist to verify the results.

10.2

Limitations

SRK did not verify the analytical values in the database with reported values on assay certificates. An additional means to verify analytical zinc and lead grades in the drillhole database could be comparison to visual estimations of sphalerite and galena abundance or to measured specific gravity.

10.3

Opinion on Data Adequacy

The Project geologists and support staff were diligent about data verification and the quality of the drillhole database. Database validation in preparation for resource estimation has been done by Votorantim. Although SRK did not verify the analytical values in the database with reported values from assay certificates, there were no indicators of erroneous data. SRK believes the degree of organization of the data base and the measures in place to minimize errors in data ensure a high-quality database.

Figure 10-1: Photograph of Project core lithology reference sample library

Mineral Processing and Metallurgical Testing (Item 13)

Votorantim retained Smallvill S.A.C. (Smallvill) to perform metallurgical studies on Bongará mineralized material types in 2010 and 2011. Information presented in this section is summarized from the Smallvill metallurgical testing reports (2010, 2011a, 2011b). Unless noted, all tables were excerpted from the Smallvill reports and translated to English by SRK for this report. The 2013 Scoping Study (AMEC, 2013) cost information was considered in the development of the operating cost inputs for the cut-off grade estimate.

The Bongará sulfide resource consists of zinc and lead sulfides in a limestone matrix where zinc is in higher proportions than lead. The recovery testing focused on conventional lead-zinc flotation. The oxide resource has zinc in much higher proportion than lead, and consists of zinc carbonates and silicates in a dolomitic limestone matrix. The zinc oxide material is predominately smithsonite and hemimorphite, and lead oxide material is cerussite. The oxide recovery process Smallvill investigated focused on a combination of heavy media separation (HMS) followed by conventional zinc oxide flotation. The two concentrates are then upgraded to marketable products through calcination and Waelz roasting processes.

Smallvill also tested a sample of mixed oxides and sulfides using a combination of the processes described above. The mixed material represents a minor amount of mineralization and is only discussed briefly. Mixed materials only represent a minor amount of the resource and they were tested with the sulfide and oxide recovery methods. Results were comparable to the pure sulfide and oxide composite results, and are not included in this document.

11.1

Testing and Procedures

Metallurgical testwork was carried out on three composites of three material types (sulfide, oxide and mixed) by Smallvill in San Isidro- Lima, Peru, and reported between April 2010 and August 2011. Methods included whole-rock and trace element determination, mineralogy, comminution, and flotation on all samples. Oxide and mixed samples were processed with Heavy Media Separation (HMS), oxide flotation, and acid leaching tests were conducted on the oxide sample. Calcining and Waelz processing (roasting) of the HMS and flotation concentrates were also conducted. The following results discuss the relevant processing methods used in the development of the cut-off grade for the three material types.

11.2

Relevant Results

11.2.1

Sulfide Material

Head Analysis

Chemical head analysis is provided in Table 11.2.1.1 showing 1.7% lead, 7.5% zinc and 11.6 g/T silver.

Table 11.2.1.1: Head Grade of Sulfide Composite

Ag*	PbT	ZnT	Fe	PbOx	ZnOx	PbS	ZnS	S
11.6	1.72	7.52	1.88	0.46	1.42	1.26	6.1	4.86

Source: Smallvill, 2011

*Reported value for silver is in grams per metric tonne; other values are percent

A multi-element ICP analysis on the head sample was also conducted and the results are provided in Table 11.2.1.2. The levels of zinc, lead, magnesium, calcium and copper and low silver content suggests a similar composition to the San Vicente (Chandigarh) lead-zinc deposit in Peru. The presence of deleterious elements in concentrates (As, Sb, Bi, Co and Ni) is less than 0.02% of the total mass and unlikely to affect the quality of lead and zinc concentrates.

Table 11.2.1.2: Multi-Element Composition of Sulfide Composite

Concentration in ppm
Ag	As	Ba	Be	Bi	Cd	Co	Cr	Cu	Ga
12.6	151	140	<0.5	<5	177	2	15	44.6	<10
La	Mn	Mo	Nb	Ni	Pb	Sb	Sc	Sn
1.6	1869	2	<1	3	>10000	25	<0.5	<10
Sr	Tl	Th	U	V	W	Y	Zn	Zr
53.8	5	<50	<8	5	<10	1.2	>10000	21.1
Concentration in %
Al	Ca	Fe	K	Mg	Na	P	Sn	Ti
0.44	>15	2.01	0.07	8.15	0.64	0.06	4.71	<0.01

Source: Smallvill, 2011

Mineralogy

Mineralogical analysis was conducted on the head sample by X-ray diffraction. The results are provided in Table 11.2.1.3. The majority of the sample (80%) consists of calcium and magnesium carbonates from the dolomite matrix. The low iron sulfide content as pyrite, arsenopyrite, and pyrrhotite, suggests that the material will not require special iron depressants in flotation and the sulfide material will be amenable to conventional lead-zinc selective sulfide flotation.

Table 11.2.1.3: Mineralogy of Sulfide Composite

Mineral	Weight %
Dolomite	76.7
Quartz	4.8
Calcite	3
Smithsonite	2
Hemimorphite	0.2
Pyrite	3.5
Sphalerite	7.9
Galena	1.5
Cerussite	0.3
Total	100

Source: Smallvill, 2011

Comminution Testwork

Conventional bond work index testwork was conducted. A work index comparison was made to the San Vicente operation with similar rock types. The work index reported by San Vicente was 12.31 kWh/t; indicating a medium-hard matrix. In comparison, the Bongará work index is 8.56 kWh/t, indicating that it has a 30 percent lower specific energy requirement than San Vicente. Table 11.2.1.4 provides a comparison of results.

Table 11.2.1.4: Comparison of Bond Work Index for Sulfide Materials

San Vicente				Bongará
WI: 12.31 Kwh/T				WI: 8.54 Kwh/T
T, min	P₈₀	Wt	Wt/T	T, min	P₈₀	Wt/T
10.0	45	14.39	1.44	5.0	93	5.98
6.0	93	8.71	1.45	4.0	126	4.78
5.5	107	7.86	1.43	3.0	182	3.59
5.0	151	5.98	1.20	2.0	200	2.39
0.0	933			1.0	316	1.20
				0.0	891

Source: Smallvill, 2011

Flotation Testwork

Grind Size Optimization:

Optimization of the flotation feed size (grind-recovery and concentrate grade) was conducted for both lead and zinc. Table 11.2.1.5 provides the results for lead and silver, and Table 11.2.1.6 provides the results for zinc.

Table 11.2.1.5: Effect of Grind Size on Lead and Silver Flotation

Sample	Grinding		pH		T, minutes		ZnSO₄	g/T z-11		g/T NaCN		Lead Recovery			Lead Concentrate Grade			Zinc Recovery			Conc RCI
BG-	min	-200%	Ro	Cl	Cl	RCI	g/T	Ro	Scv	Cl	RCI	Ro I/II	Cl	RCI	Ro I/II	Cl	RCI	Ro I/II	Cl	RCI	%Zn	%Fe
21	4	60.9	7.6	7.6	2	2	0	16	6	6	2	90.9	80	70.6	13	28.4	40	12.2	3.6	2.2	5.8	14
22	5.5	68.7	7.6	7.6	2	2	0	16	6	6	1	92.4	83.4	78.8	9.9	25.1	37	15	5.4	3.4	7.5	9
23	7	73.5	7.6	7.6	2	2	0	16	6	6	2	90.8	78.4	71.3	12.4	30.6	45	10.9	3.6	2.5	8.3	10.3

Source: Smallvill, 2011

Table 11.2.1.6: Effect of Grind Size on Zinc Flotation

Sample	Grinding	pH				T, Minutes			Cu			g/T Z-11		g/t NaCN
BG-	min	Ro	Cl	RCI	SC I/II	Ro I/II	Cl	RCI	Ro	SC I	SC II	Ro	Scv	in RCI
21	4	7.6	7.8	7.8	4/4	2/5	2	2	200	60	60	20	12/12	1.6
22	5.5	4.6	4.8	10	4/4	2/5	2	2	200	60	60	20	12/12	0
23	7	7.6	7.8	7.8	4/4	2/5	2	2	200	60	60	20	12/12	0
Sample	Zn Recovery				Zinc Concentrate				Zinc Recovery				Conc RCI %
BG-	Ro/Sc	RO I/II, Scl	Cl	RCI	Ro/Sc	RO I/II, Scl	Cl	RCI	Ro/Sc	RO I/II, Scl	Cl	RCI	Fe	Pb
21	97	96	93	91	32	35	50	52	37	34	25	23	2	0.2
22	99	98	96	93	30	32	49	51	40	38	26	24	2.2	0.1
23	98	98	95	94	34	37	55	58	38	34	21	20	2.7	0.2

Source: Smallvill, 2011

The results show that grinding to 61 percent minus 200 mesh is sufficient to liberate the lead and zinc minerals, whereby optimizing recovery and concentrate grade.

Reagent Optimization:

Common lead and zinc collectors and depressants at varying dosage rates were tested. Details of the test procedures and results are available in Smallvill (2011).

Zinc sulfate as a depressant in lead flotation was determined to not be required;

The optimum lead flotation pH was determined to be neutral at 7.6;

Sodium Isopropyl Xanthate, as a lead collector non selective for zinc and iron, at a dosage of 12 g/t was optimal for lead recovery. Higher dosages were required to depress zinc and pyrite; and

Copper sulfate, coupled with Z-11 to depress pyrite, was tested to activate the zinc in zinc flotation. The optimum dosages were 100 and 20 g/t, respectively.

Sulfide Flotation Flowsheet and Optimized Process Parameters

The testwork was conducted utilizing a conventional selective lead-zinc flotation flowsheet provided in Figure 11-1. The optimized lead and zinc flotation process parameters are provided in Table 11.2.1.7 and Table 11.2.1.8, respectively. The material parameters for this process include:

Particle Size of 61% -200 mesh;

Work Index of 8.56 kW-h/T; and

Ball Mill Consumption of 0.35 kg/T.

Table 11.2.1.7: Optimized Lead Sulfide Flotation Parameters

Lead Flotation
pH	Around 7.8
Concentration of Solids	40%
Collector	Sodium Isopropyl Xanthate, Z-11
Collector Dosage	12 g/T in Rougher, 4 g/T in Scavenger
Frothing Agent	MIBC or ER-350
Frothing Agent Dosage	20 g/T in Rougher I and Scavenger
Conditioning Time	5 minutes
Depressor	NaCN only in Cleaner
Depressor Dosage	6 g/T
Flotation Time (industrial scale is 2-3x to avoid short circuiting)
Rougher I	1.0 min
Rougher II	3.0 min
Scavenger I	4.0 min
Cleaner	1.5 min
Recleaner	1.0 min
Sedimentation Area	0.011 m²/(T/d)
Flocculant	Superfloc A-110
Flocculant Dosage	20 g/T of concentrate

Source: Smallvill (2011), Translated by SRK (2014)

Table 11.2.1.8: Optimized Zinc Sulfide Flotation Parameters

Zinc Flotation
pH	Around 7.8
Concentration of Solids	40%
Collector	Sodium Isopropyl Xanthate, Z-11
Collector Dosage	20 g/T in Rougher, 20 g/T in Scavenger
Activator	Copper Sulfate, CuSO₄
Activator Dosage	100 g/T in Rougher, 60 g/T in Scavenger
Frothing Agent	MIBC or ER-350
Frothing Agent Dosage	60 g/T in Rougher I and 20 g/T in Scavenger
Conditioning Time	7 minutes, with Z-11 and CuSO₄
Depressor	None
Flotation Time (industrial scale is 2-3x to avoid short circuiting)
Rougher I	3.0 min
Rougher II	3.0 min
Scavenger I	6.0 min
Cleaner	1.5 min
Recleaner	1.0 min
Sedimentation Area	0.022 m²/(T/d)
Flocculant	Superfloc A-110
Flocculant Dosage	20 g/T of concentrate

Source: Smallvill (2011), Translated by SRK (2014)

Source: Smallvill, 2011

Figure 11-1: Optimized Sulfide Flotation Flow Sheet

Metallurgical Balance

The metallurgical balance is shown in Table 11.2.1.9. The lead concentrate contained 52.6 percent lead and 7.3 oz/t silver, at a recovery of 85 and 30 percent for lead and silver, respectively. The zinc concentrate of 52.6 percent zinc and 1.0 ounce per tonne (oz/T) silver had 93 and 25 percent recovery for zinc and silver, respectively.

Table 11.2.1.9: Metallurgical Balance for Sulfide Flotation

Product	Weight %	*Concentrate Grade (%, g/T)**				Recovery, %
Product	Weight %	Ag*	Pb	Zn	Fe	Ag	Pb	Zn	Fe
Concentrated Pb	1.81	226.4	52.61	4.72	8.47	30.3	84.8	1.2	8.3
Concentrated Zn	11.68	29.5	0.16	55.17	2.12	25.3	1.6	93.1	13.4
Final Tailings	86.5	6.8	0.18	0.45	1.68	44.4	13.6	5.7	78.4
Total/ Average	100.0	13.7	1.13	6.92	1.85	100	100	100	100

Source: Smallvill, 2011

*Reported silver (g/T) is converted by SRK from oz/T in original report.

11.2.2

Oxide Material

Head Analysis

The chemical composition of the oxide material composite sample is shown in Table 11.2.2.1. Zinc is the only metal in economic abundance in this sample. Lead, copper and silver are present in oxide minerals, which are difficult to recover and concentrate to marketable values.

Table 11.2.2.1: Head Grade of Oxide Composite

Sample	Cu	Ag*	PbT	ZnT	Fe	PbOx	ZnOx	ST	SS
Oxide Composite	0.008	11.6	0.44	13.4	3	0.38	19	0.38	0.38

Source: Smallvill, 2011

*Reported value for silver is in grams per metric tonne; other values are percent

Table 11.2.2.2 provides a summary of the ICP analysis for trace element abundance.

Table 11.2.2.2: Multi-Element Analysis of Oxide Composite

Concentration, ppm
Ag	As	Ba	Be	Bi	Cd	Ce	Co	Cr	Cs	Ga	Ge	Hf
13	118	3937	<0.5	<0.03	370	2	0.8	13	0.3	7.6	107	0.6
In	La	Li	Mo	Nb	Ni	Re	Rb	Sb	Sc	Se	Sn	Sr
<0.1	1.1	2.8	3.7	0.3	10.1	<0.002	1.5	20.4	<0.5	8	1.1	116
Ta	Tb	Te	Th	Tl	U	V	W	Y	Yb	Zr
2.5	<0.1	2	0.2	0.7	1.2	12	10	1.8	0.4	5.6
Concentration, %
Al	Ca	Cu	Fe	K	Mg	Mn	Na	P	Pb	S	Ti	Zn
0.31	11.25	0.01	3	0.16	4.52	0.18	0.24	0.12	0.44	0.38	<0.01	>1.0

Source: Smallvill, 2011

In addition to the high zinc content, the analysis shows high magnesium and calcium and low copper and silver. The low concentrations of impurities (As, Sb, Bi, Co and Ni) at less than 0.02% each suggests that they would report to the concentrate in concentrations below the smelter penalty limits.

Mineralogy

A mineralogical analysis by X-ray diffraction was conducted and the results are provided in Table 11.2.2.3.

Table 11.2.2.3: Mineralogy of Oxide Composite

Mineral	Weight %
Dolomite	45.83
Smithsonite	27.16
Hemimorphite	10.05
Calcite	9.1
Quartz	6.3
Barite	0.88
Sphalerite	0.67
Total	100

Source: Smallvill, 2011

Approximately 60 percent (by volume) of the material is gangue comprised of dolomite, calcite and quartz. These minerals have specific gravities between 2.70 and 2.85 g/cm³, and are amenable to HMS from the denser zinc minerals. XRD analysis also confirmed the presence of zinc oxides, predominantly as smithsonite, and to a lesser extent, hemimorphite.

Comminution

Conventional bond work index testwork was conducted. Table 11.2.2.4 provides the bond work index results. The oxide sample work index was 12.6 kWh/t in comparison to the San Vicente work index of 12.3 kWh/t.

Table 11.2.2.4: Variation of Work Index with Grind Time for Oxide Composite

Time	P80	WI	% Acum. Fine
(minutes)	(microns)	Kwh/T	-200	-400
0	1317		15.6	13.7
3	279	13.58	40.7	26
5	162	12.14	53.2	33.9
7	125	12.08	62.4	41.4
Average		12.60

Source: Smallvill, 2011

Zinc Oxide Flotation

The zinc oxide flotation testing started with grinding the sample for five minutes. At this stage, the feed size distribution was 56 percent minus 200 mesh and 27 percent minus 20 microns. Flotation tests were conducted without and with a typical desliming procedure. Initially, desliming was performed using a 2-inch hydrocyclone, but switched to elutriation due to sample loss.

Table 11.2.2.5 provides the flotation parameters. A significant difference in results was observed between the two methods and summarized in Tables 11.2.2.6 and 11.2.2.7.

Table 11.2.2.5: Zinc Oxide Flotation Parameters with Desliming

Stage	Time min	pH	Dose, kg/T
Stage	Time min	pH	Na Sulf	Flotigam	Humic Acid
Conditioning I	1.0		3.28
Conditioning II	1.0				0.77
Conditioning III	2.0			1.46
Zn Flotation Rougher I	1.0	11.2
Zn Flotation Rougher II	2.0
Conditioning IV	1.0		0.46		0.26
Conditioning V	2.0			0.27
Zn Flotation Scavenger I	3.0

Source: Smallvill, 2011

Table 11.2.2.6: Zinc Oxide Flotation Results without Desliming

Products	Weight	Concentration, %			Distribution, %
Products	%	Pb	Zn	Fe	Pb	Zn	Fe
Zn Rougher Conc. I	6.9	1.17	23.67	3.62	15.9	10	7.4
Zn Rougher Conc. II	5.7	0.65	16.17	4.28	7.3	5.6	7.1
Zn Rougher Conc. I + II	12.6	0.93	20.29	3.92	32.2	15.6	14.5
Zn Scavenger Conc.	8.5	0.6	17.08	4.28	10.1	8.9	10.7
Zn Rougher + Scavenger	21.1	0.8	19	4.06	33.3	24.5	25.2
Final Tailings	78.9	0.43	15.67	3.23	66.7	75.5	74.8
Oxide Composite without Desliming	100	0.51	16.37	3.41	100	100	100

Source: Smallvill, 2011

Table 11.2.2.7: Zinc Oxide Flotation Results with Desliming

Products	Weight	Concentration, %			Distribution %
Products	%	Pb	Zn	Fe	Pb	Zn	Fe
Zn Rougher Conc. I	46.5	0.68	31.50	3.02	68.8	83.4	45.1
Zn Rougher Conc. II	3.6	0.60	25.67	2.88	4.7	5.3	3.4
Zn Rougher Conc. I + II	50.2	0.68	31.08	3.01	73.5	88.7	48.5
Zn Scavenger Conc.	1.1	0.27	7.25	2.6	0.6	0.5	0.9
Zn Rougher + Scavenger	51.3	0.67	30.57	3	74.2	89.2	49.4
Final Tailings	48.7	0.25	3.90	3.23	25.8	10.8	50.6
Oxide Composite with Desliming	100	0.46	17.57	3.11	100	100	100

Source: Smallvill, 2011

Without desliming, the rougher concentrate zinc recovery was 10% with a grade of 24 percent, compared to 83 percent recovery and a grade of 32 percent with desliming. Zinc oxide flotation is uneconomic without a prior desliming step.

A series of flotation tests were also conducted to determine optimal doses of a conditioner (sodium sulfide), a collector (Clariant’s Flotigam 2835-2) and an iron oxide depressant (humic acid). The optimized parameters and results are provided in Tables 11.2.2.8 and 11.2.2.9.

Table 11.2.2.8: Conditioner Doses for Zinc Oxide Flotation

Stage	Time min	pH	Dose, kg/T
Stage	Time min	pH	Na Sulf	Flotigam	Humic Acid
Conditioning I	1		2.42
Conditioning II	1				3.03
Conditioning III	2			0.55
Zn Flotation Rougher I	1	10.8
Zn Flotation Rougher II	2
Conditioning IV	1		1.21		1.01
Conditioning V	1			0.15
Zn Flotation Scavenger	3
Zn Rougher Conditioner I	2		1.21		1.01
Zn Cleaner Flotation I	1
Zn Cleaner Flotation II	1

Source: Smallvill, 2011

Table 11.2.2.9: Optimized Zinc Oxide Flotation Results

Products	Weight	Concentration, %			Distribution %
Products	%	Pb	Zn	Fe	Pb	Zn	Fe
Zinc Cleaner Conc. I	4.3	0.44	38.00	1.53	7.1	11.5	4.7
Zinc Cleaner Conc. II	18.9	0.42	33.50	2.03	28.9	43.9	27.2
Zinc Rougher and Cleaner Conc. (I + II)	23.2	0.42	34.34	1.94	36.0	55.4	31.9
Zinc Rougher and Cleaner Tailings	14.2	0.52	31.00	2.68	27.0	30.7	27.1
Zinc Rougher Conc. I	37.4	0.46	33.70	2.22	63.0	86.0	59.0
Zinc Rougher Conc. II	3.9	0.43	25.50	2.15	6.3	7.0	6.0
Zinc Rougher Conc. (I + II)	41.4	0.46	32.35	2.22	69.3	93.0	65.0
Zinc Scavenger Conc.	4.4	0.42	10.40	1.53	6.8	3.2	4.8
Zinc Scavenger + Rougher Conc.	45.8	0.45	30.22	2.15	76.1	96.2	69.9
Final Tailings	54.2	0.12	1.00	0.78	23.9	3.8	30.1
Oxide Composite without Desliming	100	0.27	14.39	1.41	100.0	100.0	100.0

Source: Smallvill, 2011

The results show that zinc can be concentrated to 32.4 percent of the concentrate, at a recovery of 93 percent with desliming. The overall recovery including the zinc losses in the slimes is 73 percent.

Calcination Processes

Calcination and Waelz pyro-metallurgical processes testing were conducted on Heavy Media Separation (HMS) and flotation concentrates to upgrade them to a level marketable to smelters. While the calcination process was not tested on the flotation concentrate, results of direct calcination of the heavy media concentrate are shown in Table 11.2.2.10. At 900°C, 32 percent of the carbonates volatilize after one hour. The composite product of 47 weight percent zinc could be sold directly to the Cajamarquilla or other refineries.

Table 11.2.2.10: Calcination Results, HMS Concentrate

Test	T, 0C	t, hr	% Volat.	Concentrate, %Zn
Original	25	0	0	34.1
TB-21	700	0.5	23.8	44.7
TB-22	700	1	24.2	45
TB-23	700	2	25.7	45.9
TB-24	750	3	31	49.4
TB-25	900	1	31.6	49.8

Source: Smallvill, 2011

While the HMS process was not utilized for the purpose of this technical report, the calcination results are applicable. Additionally, Votorantim has conducted benchmarking of calcining zinc oxide flotation concentrates at Mae Sod Padaeng in Thailand and Angouran in Iran.

Oxide Metallurgical Balance and Flowsheet

Metallurgical Balance for the proposed flowsheet

The overall metallurgical balance is provided in Table 11.2.2.11. The results show that 73 percent of the zinc can be recovered at a concentrate grade of 47.5 percent zinc.

Table 11.2.2.11: Metallurgical Balance for Proposed Zinc Oxide Recovery Process

Bongará Metallurgical Balance - Oxide	Percent
Feed Grade, %Zn	13.4
Recovery, % Zn	73
Flotation Concentrate Grade, % Zn	32.4
Flotation Concentrate Weight, t Zn	0.302
Flotation Metal, t Zn	0.098
Calcine Recovery, % Zn	100
Calcine Grade, % Zn	47.5
Calcine Weight, t	0.206
Calcine Metal, tZn	0.098

Source: SRK, 2014

Proposed Recovery Flowsheet

The overall proposed zinc oxide recovery circuit is provided in Figure 11-2.

Figure 11-2: Proposed Zinc Oxide Flotation Circuit

11.3

Recovery Estimate Assumptions

The recovery estimates for the sulfide, oxide and mixed material types are provided in Table 11.3.1. They are based on the Smallvill metallurgical test report results.

Table 11.3.1: Recovery and Concentrate Grade Estimate for Each Material Type

Metallurgical	Feed Grade			Recovery			Concentrate Grade
Metallurgical	Pb, %	Zn. %	Ag, PPM	Pb	Zn	Ag	Pb,%	Zn, %	Ag-Pb. opt	Ag-Zn, opt
1 Sulfide (Smallvill)	1.4	11.7	14.7	84.8	93.1	55.6	52.6	55.2	7.28	0.95
2 Mixed (SRK Calculated)		8.9		50.0	84.9	32.8	52.6	52.0	7.28	0.95
3 Oxide {Smallvill)		8.5			73.0			47.5

Source: SRK, 2014

Notes: SRK MineSight 3D Resource Confirmation, May 22, 2014 AFTER REBLOCKING, File:ox3.rpt; @ 3.0% Zn Cut-off Grade

Mixed = 59% sulfide and 41% oxide from resource tonnes

For the sulfide, the conventional selective lead-zinc flotation process and treatment of the concentrate in lead and zinc smelters was utilized to estimate metal recovery, concentrate grades and processing costs. Oxide recovery, concentrate grade and operating costs were based on conventional zinc oxide flotation, calcining the flotation concentrate and treating the calcined concentrate at a zinc smelter. Recovery and processing costs for the mixed material was based on a weighted average; 59: 41 percent sulfide to oxide ratio.

Other processing options were investigated by Votorantim/ Smallvill for the oxide material, but were not utilized due to process conventionality and higher operating costs.

11.4

Sample Representation

11.4.1

Sample Location

The specific locations of the samples used for metallurgical testing relative to the mineral resource were not included in the Smallvill metallurgical testing reports. However, because material for the composite samples was obtained from drill core, we can assume that spatial coverage of the metallurgical composites is comparable to the drilling coverage from Votorantim programs through 2009.

Additional variability testing to characterize comminution and flotation will be necessary as the resource is developed.

11.4.2

Material Types

The material types and their approximate proportions of the resource are summarized in Table 11.4.2.1. More than half of the resource is sulfide material, and about 30 percent is oxide material. Mixed (oxide and sulfide) material is about 10 percent, a minor contribution.

Composites of each material type were generated from available saw-split drill core in late 2009. The sulfide composite was about 300kg, and although the masses of the other composites were not reported, we expect that the mixed and oxide composite sample sizes were comparable.

Table 11.4.2.1: Bongará Material Types

Material Type	Percentage of Resource
Sulfide	60
Mixed Sulfide and Oxide	10
Oxide	30

Source: SRK, 2014

The following details about the sulfide composite were provided by Smallvill.

In October 26, 2009, Votorantim provided 32 sample boxes of saw-split diamond drill core from the Project. Half of these boxes contained duplicates made from quartering the original samples and were mixed to make a composite sample for metallurgical testing. The remaining 16 boxes containing the other half of the samples were stored in the laboratory for future use.

The sulfide composite contained 517 individual drillhole intervals with weights ranging from 80 to 1800 grams, and length between ¼ and 3 inches. The composite sample totaled 293 kg and was crushed to 100 percent passing 10 mesh, blended and split into 75 kg samples. One of these samples was split into lots of 0.5 kg and 4.0 kg and placed in sealed polyethylene bags. The three remaining 75 kg samples were also packed in polyethylene bags to prevent oxidation.

11.5

Significant Factors for Processing and Costs

Several factors require additional study to better understand mineral process efficiency and costs.

11.5.1

Sample Representation

The locations of the samples used for metallurgical testing relative to the resource were not included in the Smallvill metallurgical testing reports; therefore, the composites’ representativeness was not reviewed.

11.5.2

Material Processing

Sulfide

This is a conventional process with little risk. The next step is to conduct comminution, flotation and concentrate impurities variability testing.

Oxide

For the zinc oxide material, three processing methods were tested: 1) conventional oxide flotation; 2) less conventional heavy media separation (HMS) and 3) acid leaching. Conventional zinc oxide flotation produced a zinc recovery of 73 percent zinc compared to 92 percent for HMS and 99 percent for acid leaching. However, the flotation process was selected for the following reasons:

HMS is a non-conventional process not yet proven on the commercial scale, and the over-all processing costs were sufficiently higher than those for conventional oxide flotation;

Acid leaching of the whole material and flotation concentrates both produced zinc recoveries in excess of 99 percent. However due to the reported acid costs, these processes also incurred higher operating costs to also produce a higher cut-off than flotation. Secondly, Votorantim already operate a smelter in Peru that can accept the Bongará concentrates; therefore, incurring SXEW capital costs is not the preferred option. However, there are opportunities and synergies with the sulfide material to suggest further evaluation of this process is warranted; and

Although calcining the flotation concentrate was not tested by Smallvill, benchmarking the process was conducted and it has been commercially applied.

Mixed

Mixed materials can be campaigned through the sulfide plant. Additional testwork to float the zinc oxide with the zinc sulfide through a sulfidization process is planned.

11.5.3

Operating Costs

The operating costs were estimated using the AMEC (2013) and Smallvill (2011) operating cost data as the basis. Table 11.5.3.1 provides a summary of the cost estimates for the three material types.

Table 11.5.3.1: Bongará Processing Operating Costs ($/t)

Process	Sulfide	Oxide	Mixed
Process	9.4	28.1	17.0
Freight	21.6	12.8	18.0
Treatment Charge (Smelter)	29.0	15.1	23.3
Total	60.0	55.9	58.3

Source: SRK, 2014

Note: Mixed = 59% sulfide and 41% oxide from resource tonnes

Assumptions Sulfide

Process – conventional selective flotation; and

Operating, Shipping and Treatment Costs - AMEC report.

Assumptions Oxide

Process – conventional oxide flotation and Waelz;

Operating Costs – Smallvill with an AMEC factor; and

Shipping and Treatment – AMEC report.

Assumptions Oxide

Process – sulfide and oxide flotation and Waelz; and

Operating, Shipping and Treatment Costs – sulfide oxide average.

Mineral Resource Estimate (Item 14)

Mineral Resource estimation for the Bongará deposit was conducted by Votorantim Metais (Votorantim) in August, 2013 and reported by Mineral Resources Management (MRM), an internal resource modeling group of Votorantim, in December of 2013 (Votorantim, 2013b). In April of 2014, SRK Consulting was contracted by Solitario to audit the MRM resource estimate and prepare a Technical Report on Resources compliant with the guidance of National Instrument 43-101 (NI 43-101). SRK has relied on the MRM report for technical information related to the construction of the resource model and has taken the necessary steps to validate the estimation methods and results. SRK’s validation included an independent analysis of the project database, geostatistical analysis of the data, and reconstruction of the resource model using 3-D modeling software. Other key elements of the validation included an SRK visit to the project site on May 5 to 7, 2014 followed by a meeting with Votorantim’s chief resource modeler, Saulo Oliveira, in Lima, Peru on May 9, 2014. Digital data files for drilling and block modeling were provided by Votorantim as requested by SRK following the May 9 meeting.

The Mineral Resource estimate was based on a 3-D geological model of major structural features and stratigraphically controlled alteration and mineralization. A total of 23 mineral domains were interpreted from mineralized drill intercepts, comprised mostly of 1 m core samples. The block size of the model is 10 m x 10 m x 1 m. The project is in metric units. Zinc, lead and silver were estimated into model blocks using Ordinary Kriging (OK). Oxide, Sulfide and Mixed material types were estimated by Indicator Kriging (IK). Density was determined from a large percentage (56%) of measured values, which were used to develop equations for density assignment based on rock type and kriged metal content. The digital data files listed in Table 12.1.1 were provided to SRK by Votorantim and these were used for model auditing and comparative geostatistics.

Table 12.1.1: Digital Data Files Provided to SRK by Votorantim

File	Description
BO-15-08-2013-basedados.mdb	Drillhole database as of August 15, 2013
BO-15-08-2013-QAQC_basedados.mdb	QAQC database
BO-15-08-2013-dhcomp.dm	Regularized samples (Composites)
BO-15-08-2013-topo_pt.dm	Topography points
BO-15-08-2013-topo_tr.dm	Wireframe Topography
BO-15-08-2013-geo_min_manto_pt.dm	Points of interpreted mineralized bodies (mantos)
BO-15-08-2013-geo_min_manto_tr.dm	Wireframes of interpreted mineralized bodies (mantos)
BO-15-08-2013-geo_min_estutura_pt.dm	Points of interpreted mineralized bodies (structurally controlled bodies)
BO-15-08-2013-geo_min_estutura_tr.dm	Wireframes of interpreted mineralized bodies (structurally controlled bodies)
BO-15-08-2013-modfinal.dm	Block models

Source: SRK, 2014

12.1

Geology and Mineral Domain Modeling

Bongará is interpreted as a Mississippi Valley Type (MVT) base metal deposit dominated by the zinc and lead sulfides sphalerite and galena. These minerals occur as disseminated and massive replacements hosted in stratigraphically controlled dolomitized limestones of the Upper Triassic to Lower Jurassic Chambara Formation. The deposit is located in karst terrain and due to locally high degrees of water percolation, shallow sulfide mineralization is commonly altered to oxidized silicate and carbonate minerals (smithsonite, hemimorphite and cerussite), collectively referred to in this report as “oxides”. Mineralization occurs both as a set of nearly flat-lying stratiform “mantos” intersected locally by high-angle mineralized faults (e.g.: Sam and San Jorge).

The geological model underpinning the resource estimate was generated in Leapfrog Geo™ 1.3 software using the drillhole database from the drilling campaigns of Cominco and Votorantim.

The underlying carbonate stratigraphy of the Bongará deposit is dome-shaped on a regional scale (Figure 12-1). This geometry was fundamental to the construction of the geological contacts and boundaries of mineralized bodies.

Surfaces that represent stratigraphic units Chambara 1, 2 and 3 were constructed through the contact points of the lithologies in 3-D. The fossil marker beds of Coquina and IBM were identified and used as guide horizons. Then the five main faults that cut the deposit were modeled. The faults were located using a 3-D projection of the geological surface map onto topography in conjunction with fault intercepts as logged in drillholes. The projected geologic surface map is shown in Figure 12-2.

Mineralization is hosted exclusively in dolomitized limestone. The interpreted dolomitized zones between the lower Coquina and the upper IBM marker horizons are shown in tan in Figure 12-3. The extent of dolomite alteration was logged in drillholes and modeled within the five major structural domains.

Mineralized wireframes were built in close relationship to the dolomitization envelope and modified (offset) by internal structures when these offsets were clearly defined. Mineral domains were constructed using a 0.5% zinc cut-off grade. The mineral domain wireframes were built in Leapfrog Geo™ and then imported to Datamine Studio 3® format for block coding and resource estimation.

In total, 23 individual wireframes were built, which vary from 1 to 9 m in thickness, but most were a minimum of 2 to 3 m thick to address dilution. SRK observed several mineralized intercepts outside of all mineral domains. These were intentionally left out due to insufficient thickness or continuity. Figure 12-4 illustrates the stratiform manto-style mineralization (red, n = 21) and the N-S oriented steeply dipping (70°) Sam and San Jorge zones (blue, n = 2).

Figure 12-1: North-South Longitudinal Section of Geologic Model

Figure 12-2: Bongará Geological and Structural Map Projected on Topography

Figure 12-3: Geological Cross Section of Karen-Milagros Domain

Figure 12-4: Oblique View of Mineral Domains

12.2

Drillhole Database

12.2.1

Database

SRK acquired the project drilling data in a Microsoft Access database entitled “BO-15-08-2013-basedados.mdb.” The database contained individual tables for collar locations, down-hole surveys, geochemistry, lithology, alteration and oxidation.

The database includes drilling campaigns of two different companies. A total of 82 drillholes were completed by Cominco totaling 24,781.19 m drilled from 1997 to 2000, and 404 drillholes were completed by Votorantim including 92,499.15 m drilled from 2006 to 2013. The distribution of drillholes, color coded by drilling campaign is shown in Figure 12-5.

12.2.2

Analytical Data Collation

The database SRK received contained zinc, lead and silver analytical data in multiple columns representing the different methods of preparation and analysis. In some cases, maximum detection limits were exceeded and these samples were re-assayed by another method to provide an accurate result at a higher detection limit. Some pre-processing was necessary to collate the data to single element fields for further work. SRK pre-processing involved:

The values in the column Zn_ppm_ME_ICP61 were divided by 10,000 in order to convert from parts per million to percent;

The column Zn_pct_Zn_AA62 overlapped the column Zn_pct_ME_ICP61 when Zn_pct_ME_ICP61 >= 1.5 (upper detection limit). The column Zn_pct_Zn_VOL70 overlapped Zn_pct_Zn_AA62 when Zn_pct_Zn_AA62 >= 45 (upper detection limit);

Column Ag_ppm_Ag_AA62 was superimposed to the others when Ag_ppm_ME_ICP61 >= 150 ppm (upper detection limit);

Column Pb_pct_Pb_AA62 was superimposed to Pb_pct_ME_ICP61 when Pb_pct_ME_ICP61 >= 1.5 (upper detection limit);

Column Pb_pct_Pb_VOL70 was superimposed to Pb_pct_ME_ICP61 when Pb_pct_ME_ICP61 >= 1.5 and Pb_pct_Pb_AA62 >= 20 (upper detection limits); and

Pb values of TP-1505304 and PD-1505299 (0.00003%) were replaced by the detection limit (0.0001%).

12.2.3

Topography and Sample Locations

Surface topography was generated using a digital aerial survey modified by the points of the drill collars recently surveyed with a total station instrument.

Most of the drillholes have coordinates surveyed with a total station, and have adequate location precision to use for Measured or Indicated resources. Eight of 486 have coordinates surveyed with a portable GPS that lacks precision. These drillholes were limited to Inferred resource classification, and drillholes from only two of the eight drill sites are in the resource grade shells. Figure 12-6 highlights the locations of drillhole collars located with portable GPS.

SRK imported the digital topography into Mintec’s MineSight 3-D® software and validated drill collar elevations relative to topography.

Downhole surveys were completed by Reflex EZ-Shot by the drillers at 100 m (2010), 50 m (2011) and 20 m (2012/13) down-hole spacings. The records of these are kept digitally at the core facility and were verified during the SRK site visit.

12.2.4

Oxide Classification in Drillhole Logging

Oxide classification of core sample intervals was determined visually according to the abundance of sphalerite and galena, as shown in Table 12.2.4.1. Hemimorphite and smithsonite phases were classified together as oxide.

Table 12.2.4.1: Logged Oxide Classification of Zn and Pb Mineralization

Sulfide percentage (%)	Oxide percentage (%)	Classification
>90%	<10%	1 - Sulfide
<10%	>90%	2 - Oxide
90% > sulfide > 10%	90% > oxide > 10%	3 - Mixed

Source: Votorantim, 2013b.

Figure 12-5: Map of Drillholes by Company

100

Figure 12-6: Locations of Low-Precision Drillhole Collar Surveys

101

12.3

Drilling Data Analysis

The database contains 486 diamond core drillholes totaling 117,280.25 m. There are 47,970 intervals with geological description, from which 23,863 were sampled and have chemical analyses for zinc. Fewer have analyses for lead and silver- 13,780 and 23,699 intervals, respectively. Approximately 91% of the sample intervals had measured core recovery and the core recovery averaged 98.3%. Raw assay statistics are presented in Table 12.3.1.

Table 12.3.1: Statistics of Raw Assays in Logged Oxide (Oxide 1, 2, or 3)

Item	n	Sum	Minimum	Maximum	Mean	Std. Devn.	Co. of Variation
collar_id	N/A	N/A	1	486	N/A	N/A	N/A
From (m)	N/A	N/A	0	739.15	N/A	N/A	N/A
To (m)	N/A	N/A	0.10	750.50	N/A	N/A	N/A
Interval (m)	47,970	117,280.20	0.01	180.85	2.5	3.9	1.6
Recovery (%)	21,795	2,143,071	15.00	100.0	98.3	5.1	0.1
Ag_ppm_SRK	23,699	67,925.70	0.01	258	2.87	11.65	4.07
Pb_pct_SRK	13,780	3,851	0	44.00	0.30	1.70	6.00
Zn_pct_SRK	23,863	40,361.24	0	57.31	1.69	6.05	3.58

Source: SRK, 2014.

Box plots of zinc in samples with logged oxide show higher average means and higher grades in sulfides than in oxides (Figure 12-7, left). However, if a 3% zinc threshold is applied (Figure 12-7, right), zinc grades in oxide are upgraded significantly, becoming more consistent with sulfide and transition grades and suggesting that modeling all oxide classifications together is valid. Above the 3% zinc threshold, approximately 90% of zinc oxide values are excluded from the data set, compared to only 50% exclusion of sulfide and transition materials. This suggests that there is a large population of low grade zinc in oxide.

Box plots for lead and silver in samples with logged oxide are presented in Figures 12-8 and 12-9. There is low lead and silver mineralization in oxide.

102

Source: SRK, 2014

Figure 12-7: Assay statistics for Zn in logged oxide at 0% Zn threshold (left) and 3% Zn threshold (right)

103

Source: SRK, 2014

Figure 12-8: Assay statistics for Pb in logged oxide at 0% Zn threshold (left) and 3% Zn threshold (right)

104

Source: SRK, 2014

Figure 12-9: Assay statistics for Ag in logged oxide at 0% Zn threshold (left) and 3% Zn threshold (right)

105

12.3.1

Capping

SRK’s standard approach for capping is to analyze raw assay data and identify statistical outliers in each element of economic interest. For this analysis, those assays contained within the interpreted mineral domains (n = 2,910) were analyzed. Histograms and cumulative frequency graphs were prepared for zinc, lead and silver variability. In the variability charts provided in Figures 12-10, 12-11 and 12-12, a predominantly log-normal distribution was observed, which does not show clear inflections, signifying a single population distribution and not separate high and low-grade populations. Silver may be the exception, where future modeling should consider a cap at approximately 180 ppm. Capping silver at that level would exclude nine values in the database, all of which are supported by high-grade zinc in the same intervals and are therefore considered acceptable intercepts for modeling. For these reasons, SRK concludes zinc, lead and silver do not require capping.

The single anomalously high zinc value (57.3%) in the database in hole V_465 (116.1-117.1m) was inspected in 3-D and found to be consistent with and part of a 10m high grade interval in an area of the San Jorge mineral domain supported by high-grade intercepts in neighboring drillholes.

Source: Votorantim, 2013b

Figure 12-10: Histogram and Cumulative Probability Plot for Zn

106

Source: Votorantim, 2013b

Figure 12-11: Histogram and Cumulative Probability Plot for Pb

Source: Votorantim, 2013b

Figure 12-12: Histogram and cumulative probability plot for Ag

107

12.3.2

Compositing

In the software, the raw assay database was back-coded using the mineral domain wireframes described in Section 12.1, resulting in 3,165 intercepts inside the mineralized shapes. The modal length of the raw assays was 1m, and the mean length of the coded intervals was 0.93m as shown in Figure 12-13 (left).

The coded samples were then composited to the length of 1 m (modal value of the original sample) generating 3,034 composited samples out of 3,165 original samples (Figure 12-13, right).

Source: Votorantim, 2013b

Figure 12-13: Histogram of thicknesses before (left) and after (right) compositing the samples, at intervals of 1m

All samples were composited by length (LENGTH) and by drilling recovery (COREREC). From 3,165 samples, 265 intervals (8%) are shorter than 0.50 m (half of the interval). The minimum length accepted was 0.30m. Intervals shorter than 0.30 m (29 samples) were excluded. After compositing only 54 intervals showed length less than 0.50 m.

For each interval in the mineral domains without a chemical analysis, such as the barren dolomite LITO=DO (n=10), the interval was assigned the value of half of the lowest detection limit, equal to 0.001% for zinc and lead, and 0.01 ppm for silver.

There were intervals where LITO=XX and COREREC = absent (n = 114), i.e. with no core recovery. These were interpreted to represent karst caves or voids and were assigned a code COLOUR = 24 in the composite file to distinguish them. These intervals were not included in the compositing process and were not used in the estimation. Thus, from the final 3,034 samples, a total of 2,912 were carried into resource estimation. Composite statistics are presented in Table 12.3.2.1 for all data and by OXIDE classification in Table 12.3.2.2.

108

Table 12.3.2.1: Statistics of All Composites Inside the 0.5% Zinc Mineral Domains

Item	Valid	Sum	Minimum	Maximum	Mean	Std. Devn.	Co. of Variation
LENGTH (m)	2,912	2,843.79	0.3	1.50	0.98	0.12	0.12
ZN (%)	2,912	N/A	0	57.14	8.81	10.96	1.24
PB (%)	2,912	N/A	0	33.83	1.22	2.68	2.19
AG (ppm)	2,912	N/A	0	213.85	12.32	22.42	1.82

Source: SRK, 2014

Table 12.3.2.2: Statistics of All Composites Inside the 0.5% Zinc Mineral Domains by Oxide Classification

	Item	Minimum	Maximum	Mean	Co. of Variation
Oxide n = 1,125	ZN%	0.01	46.33	5.37	1.59
	PB%	0.00	16.48	0.49	2.66
	AGppm	0.00	138.00	5.50	2.09
Sulfide n = 1,226	ZN%	0.01	53.43	12.60	0.98
	PB%	0.00	26.55	1.89	1.77
	AGppm	0.00	190.00	19.17	1.46
Mixed n = 487	ZN%	0.03	57.14	8.58	1.12
	PB%	0.00	33.83	1.43	2.00
	AGppm	0.00	213.85	12.64	1.76

Source: SRK, 2014

12.4

Density

From the 2,912 samples that had chemical analysis and were flagged in mineral domains for modeling, 1,576 samples (54%) had measured density values, obtained through the wax-coated displaced volume method.

Different densities occur due to the difference in host lithology and the degree of oxidation. Where oxidized minerals are dominant, the average density is 2.70 g/cm³, while in the sulfide domain the average density is 3.08 g/cm³. The average density in mixed oxide/sulfide is 2.91 g/cm³.

Scatter plots were generated for Zn% versus Density and Pb% versus Density resulting in a best-fit linear regression for each paired data set. These regression equations served as the basis for calculating density by metal grade and material type (OXIDE 1, 2, 3). MRM adjusted downward the slope of the regression curves for both zinc and lead so that the when the average composite grades were input to the equation, the calculated result matched the average densities listed above.

For example, the average composite grades in the sulfide population (OXIDE = 2) were 13.5% and 2.0% for zinc and lead, respectively. Inserting these grades into the density equation results in:

DENSITY = 2.786 + (0.016 * 13.5) + (0.037 * 2.0) = 3.08 (equal to the average sulfide density)

In the block model the zinc and lead grades were estimated by Ordinary Kriging and used to calculate the block density as follows:

OXIDE = 2.65 + ( 0.008 * ZN )

SULFIDE = 2.786 + ( 0.016 * ZN ) + ( 0.037 * PB )

MIXED = 2.685 + ( 0.016 * ZN ) + ( 0.042 * PB )

109

SRK replicated the density evaluation using the composite data provided by Votorantim. SRK’s scatter plots produced unadjusted regression equations that yielded higher densities than MRM by 4% and 3% for Sulfide and Mixed materials, respectively. SRK matched the MRM reported density in Oxide. SRK also compared the Bongará Project density equations to other similar polymetallic deposits for which we have recent experience, and found them to be typical of the industry standard. Therefore, the Votorantim density determination is considered valid, if not slightly conservative, for calculating resource tonnage.

12.5

Variogram Analysis and Modeling

Separate semi-variograms were generated using samples from: 1) high-angle structurally controlled domains (Sam, San Jorge) and 2) flat stratiform mineralized mantos (Karen-Milagros). The variograms were normalized to a sill of 1. Variograms were built using the base parameters listed in Table 12.5.1.

Table 12.5.1: Base Parameters for Variogram Construction

Parameter	Value
Angular tolerance	90º
Steps in X and Y	10m
Substeps near the origin	2m
Steps in Z	1m
Number of steps	15
Step Tolerance	50%
Maximum Vertical width	5m

Source: Votorantim, 2013b

Oxide was also modeled, using an indicator approach. The “Oxide” field was used, which carries integer codes 1, 2 and 3, referring to the predominance of certain minerals as defined previously in Table 12.2.4.1. These codes were converted into binary values (1 or 0) and each of the three material types were treated as an independent variable.

Results of the variography for the high-angle mineralized zones Sam and San Jorge are presented in Table 12.5.2 with example variograms for zinc, lead and silver shown in Figure 12-14. Results of the variography for the flat mineralized zones are presented in Table 12.5.3 with graphic examples shown Figure 12-15. In general, ranges on the variograms were moderate to short, typically less than 50 m, with perpendicular ranges considerably shorter, as expected, in these tabular mineral domains.

The variogram parameters listed were applied to grade estimation and indicator estimation for oxide, sulfide and mixed material types.

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Table 12.5.2: Summary of Variogram Results for Zn, Pb, Ag, and Oxide, Sulfide, Mixed for High-Angle Mineral Domains

Variable	Nugget Effect	Structure	Model		X (m)		Y (m)		Z (m)		Spatial Variance
ZN	0.05	1a		Spherical		25		6		3		0.35
		2a		Spherical		54		10000		10		0.35
		3a		Spherical		55		10000		10000		0.25
PB	0.1	1a		Spherical		7		9		1		0.30
		2a		Spherical		8		21		7		0.20
		3a		Spherical		10		10000		12		0.40
AG	0.05	1a		Spherical		25		8		5		0.30
		2a		Spherical		45		10000		10		0.40
		3a		Spherical		49		10000		10000		0.25
OXI	0.15	1a		Spherical		22		1		1		0.20
		2a		Spherical		29		9		5		0.50
		3a		Spherical		30		10000		10000		0.15
SLF	0.1	1a		Spherical		8		12		6		0.50
		2a		Spherical		19		10000		15		0.38
		3a		Spherical		20		10000		10000		0.02
MIX	0.17	1a		Spherical		12		1		1		0.36
		2a		Spherical		18		10		10		0.20
		3a		Spherical		18		20		10000		0.27

Source: Votorantim, 2013b

Table 12.5.3: Summary of Variogram Results for Zn, Pb, Ag, and Oxide, Sulfide, Mixed for Flat Manto Domains

Variable	Nugget Effect	Structure	Model	X (m)	Y (m)	Z (m)	Spatial Variance
ZN	0.2	1ª	Spherical	3	5	5	0.62
		2ª	Spherical	5	12	12	0.18
PB	0.1	1ª	Spherical	2	2	2	0.50
		2ª	Spherical	19	20	20	0.40
AG	0.2	1ª	Spherical	2	3	3	0.41
		2ª	Spherical	24	25	25	0.38
OXI	0.2	1ª	Spherical	1	4	4	0.23
		2ª	Spherical	20	35	35	0.57
SLF	0.05	1ª	Spherical	1	1	1	0.00
		2ª	Spherical	53	5	5	0.95
MIX	0.1	1ª	Spherical	1	2	2	0.64
		2ª	Spherical	11	50	50	0.26

Source: Votorantim, 2013b

Source: Votorantim, 2013b

Figure 12-14: Example variograms in N-S/vertical (red), N90°/20° (black) and N270°/70° (purple) directions for Zn, Pb, Ag and Oxide, Sulfide, Mixed in high-angle domains

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Source: Votorantim, 2013b

Figure 12-15: Example variograms in the horizontal direction for Zn, Pb, Ag and Oxide, Sulfide, Mixed in flat manto domains

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12.6

Block Model

12.6.1

Model Specifications

The block model was constructed in UTM metric coordinates using Datamine Studio® modeling software. The parent block size used was 10 m wide by 10 m long by 1 m high. Horizontal block dimensions were determined based on drill sample spacing, and the block height was based on the length of the samples (typically 1 m). The model has sub blocks up to 4 times smaller than the parent blocks, with length and width of 2.50 m and down to half the height (0.50 m). The parameters used in the generation of the block model are summarized in Table 12.6.1.1. Field descriptions of model items are provided in Table 12.6.1.2.

Table 12.6.1.1: Block Model Specifications

Parameters	Values (m)
X origin coordinate	823680
Y origin coordinate	9351760
Z origin coordinate	1598.5
block size in X	10
block size in Y	10
block size in Z	1
number of blocks in X	182
number of blocks in Y	242
number of blocks in Z	2501

Source: Votorantim, 2013b

Table 12.6.1.2: Block Model Item Descriptions

Campo	Description
CLASS	Resource classification 1-MEASURED, 2-INDICATED, 3-INFERRED
CLI	ID of mineralized bodies (1to 23)
VAZIO	ID for samples that present no recovery
DENSITY	density
OXIDOS	Mineralogic classification 1-OXIDES, 2-SULPHIDES, 3-MIXED
ZN_PCT	Zn estimated by Ordinary Kriging or nearest neighbor
PB_PCT	Pb estimated by Ordinary Kriging or nearest neighbor
AG_GT	Ag estimated by Ordinary Kriging or nearest neighbor
VOL	volume: XINCYINCZINC
TON	tonnage: DENSITYXINCYINC*ZINC
NSR	net smelter return

Source: Votorantim, 2013b, edited by SRK, 2014

12.6.2

Model Construction

The two sets of mineralized wireframes were imported and coded into the Datamine® model and checked against their volumes from the source software (Leapfrog Geo™). The volume of the coded blocks was found to be 6,230,575 m³.

Given the uneven distribution of holes and the domal geometric shape of the deposit, the samples were unfolded from their original shape and projected to a horizontal plane for grade estimation. The unfolding process consisted of reblocking all sub-blocks to the parent dimensions and then projecting

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each of the samples to a fixed elevation as illustrated in Figure 12-16. After the grade estimation, each block in the block model was returned to its original position.

SRK has reviewed the Bongará model in detail and found that the model block grades match drill intercepts with close correlation, validating the methodology and confirming the spatial relocation of the data after unfolding.

12.6.3

Special Handling of Voids

In some drill intervals there was no core recovery. These intervals likely represent the existence of karst caves, or friable unconsolidated ground where material was lost.

In these cases (n = 114 intervals) identified with the database as COLOUR = 24, a block was generated with dimensions of 2.5 x 2.5 m and height equal the thickness of the drilling interval (1m). These blocks were assigned a code VAZIO = 1 and a density equal to zero to omit them from the tonnage calculation for the resource.

SRK validated this approach through an inspection of drill core at the Bongará core storage facility during the site visit. The 2.5 x 2.5 x 1 m void assignment in the block model closely matches the actual gaps observed in drill core. SRK also confirmed that the VAZIO code 1 coincides with a zero density assignment in the block model as described.

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Figure 12-16: Block model cross section showing mineral domains in original position (bottom) and unfolded to a fixed-elevation (top)

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12.7

Grade Estimation

The strategy for block grade estimating was the same for all variables considered in the 23 mineral domains. Grades in each domain were estimated only with composites coded to that domain. The estimate for zinc, lead and silver was performed by Ordinary Kriging. The indicator variables OXY, SLF and MIX were estimated by Indicator Kriging, using variograms parameters and search ellipsoid criteria defined in Table 12.5.2 and Table 12.5.3 of this report. Overall, variogram ranges suggest an average spatial correlation of approximately 25 m.

For blocks that were not estimated with the defined variogram parameters, the search radius of the ellipsoid was multiplied by 2x (2nd search radius) and then by 10x (3rd search radius), and if there were still blocks without estimation they were assigned the value of the closest sample by nearest neighbor methods.

For blocks estimated within the variogram ranges, an octant method was used to divide the samples in the search ellipsoid into octants (8 sectors) with an optimum number of samples per sector as 1 and a minimum of 2 samples for estimating a given block as shown in Table 12.7.1.

Table 12.7.1: Parameters of Local Grade Estimation Using Octant Search Criteria

Parameters	Value
Division of ellipsoid in sectors	8
Optimum number of samples per sector	1
Minimum number of samples to estimate a block	2
Regular discretization (X, Y and Z)	3 x 3 x 1

Source: Votorantim, 2013b

Figures 12-17, 12-18, and 12-19 show the distribution of the grades for zinc, lead and silver in the block model. Figure 12-20 shows the final classification of the Oxide material type obtained through post processing, after estimation by Indicator Kriging. For each block, the probability of the material type being OXI, SLF or MIX was estimated. The final classification was made by adopting the highest probability according to Table 12.7.2, after which the Oxides model item then received the code:

1 - Where the highest probability is oxidized material;

2 - Where the highest probability is of sulfide material; and

3 - Where the highest probability is mixed material.

Table 12.7.2: Example of Final Classification of Mixed Material Type after Indicator Kriging

Óxide	OXI	SLF	MIX
3	0.17	0.23	0.48

Source: Votorantim, 2013b

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Source: Votorantim, 2013b

Figure 12-17: Distribution of Zn grades (%) in Plan View (top) and orthogonal view (bottom)

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Source: Votorantim, 2013b

Figure 12-18: Distribution of Pb grades (%) in Plan View (top) and Orthogonal View (bottom)

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Source: Votorantim, 2013b

Figure 12-19: Distribution of Ag grades (g/t) in Plan view (top) and Orthogonal View (bottom)

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Source: SRK, 2014

Figure 12-20: Distribution of Oxide material types in Plan View (top) and Orthogonal View (bottom)

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12.8

Model Validation

Validation of the block model involved an SRK review of the Votorantim model coupled with an independent statistical evaluation of the model by SRK. In order to carry out the independent evaluation, SRK loaded the drilling database (assays and composites) and block model files provided by Votorantim into Mintec’s MineSight® 3-D mining software.

SRK validated the model by several methods:

Visual comparative analysis between composite and block grades;

Statistical comparison of global averages of the original composite values and the model estimates; and

Swath plots of composite and model grades through the deposit.

12.8.1

Visual Comparison

SRK’s first step in validating the block model was to replicate reported resource tonnes, grades and mineral domain volumes in MineSight® 3-D. Once completed, SRK conducted a visual comparison of block grades to drillhole composites in 2-D (plan, section) and in 3-D. Figure 12-21 is an index map that shows the three vertical cross-section traces in Figures 12-22 through 12-24. These cross sections show close correlation between composite grades in drillholes and adjacent model block grades. In the images presented, blocks are shown full-sized; however, resources were reported for block tonnages falling inside the mineral domains only.

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Figure 12-21: Index Map of Block Model Cross Sections

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Figure 12-22: NE Cross-Section of Zn Composites and Block Grades in the San Jorge Area Looking NW (Az 330°)

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Figure 12-23: NE Cross-Section of Zn Composites and Block Grades in the San Jorge Area Looking NW (Az 330°)

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Figure 12-24: ENE Cross-Section of Zn Composites and Block Grades in the Karen-Milagros Area Looking NW (Az 347°)

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12.8.2

Comparative Statistics

The global mean of zinc, lead and silver of composite samples for each of the mineral domain groups was compared to the mean of estimated values of the blocks at zero cut-off grade. The comparison is presented in Table 12.8.2.1 for all classifications of resource (Measured, Indicated and Inferred) combined. Block grades are lower than composite grades for all elements, as desired. However, it is noted that zinc block grades in the high-angle structures are slightly higher (5%) than their source composites. This is likely attributable to the projection of Inferred high-grades in the San Jorge mineral domain and does not affect Measured and Indicated resources.

Table 12.8.2.1: Comparison of Composite and Block Grades

Element	Domain	# Samples	# Blocks	Sample Grade	Block Grade	% Difference
Zn%	All	799	228934	8.81	8.40	-5%
Pb%	All	799	228934	1.22	1.02	-19%
Ag g/t	All	696	228934	12.29	10.43	-18%
Zn%	Mantos	2108	174812	7.48	6.85	-9%
Pb%	Mantos	2108	174812	1.18	1.06	-11%
Ag g/t	Mantos	2108	174812	10.73	9.63	-11%
Zn%	Faults	799	54122	12.39	13.07	5%
Pb%	Faults	799	54122	1.34	0.91	-48%
Ag g/t	Faults	696	54122	19.08	12.82	-49%

Source: SRK, 2014

Notes: Sample Grades from input file VMcmp.csv

Block Grades from MS3D resource reports from Model bng15.rbl (reblocked)

12.8.3

Swath Plots

A swath plot is a graphical display of the grade distribution derived from a series of bands, or swaths, generated in several directions through the deposit. Grade variations from the block model were compared using the swath plot to the distribution derived from the underlying composites.

Swath plots were generated in two orthogonal directions for distribution of zinc, lead and silver grades. Swath plots along the EW (Northings) and horizontal (Elevations) directions are shown in Figures 12-25 through 12-30.

All of the swath plots show considerable smoothing of the block grades compared to the original composites, as evidenced by the peaks and valleys of the composite curves. This was expected because the composites were built on narrow 1m intervals. Even so, the grade trends in the composite data track well with the block grade trends in the various parts of the deposit. The Northing swath plots, which display grades from south (left on the graph) to north (right on the graph) clearly show the grade increase in the southern San Jorge zone compared to the northern Karen-Milagros zone. The Elevation swath plots demonstrate strong block-to-composite correlation in shallow and moderate depths (right on the graphs) where drill density is high. Drill density is lower at depth and is the cause for lower block-to-composite correlation.

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Figure 12-25: Swath Plot of Zinc% by Northing showing model blocks (green) compared to composites (orange) with model tonnage (blue)

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Figure 12-26: Swath Plot of Lead% by Northing showing model blocks (green) compared to composites (orange) with model tonnage (blue)

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Figure 12-27: Swath Plot of Silver g/T by Northing showing model blocks (green) compared to composites (orange) with model tonnage (blue)

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Figure 12-28: Swath Plot of Zinc% by Elevation showing model blocks (green) compared to composites (orange) with model tonnage (blue)

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Figure 12-29: Swath Plot of Lead% by Elevation showing model blocks (green) compared to composites (orange) with model tonnage (blue)

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Figure 12-30: Swath Plot of Ag g/T by Elevation showing model blocks (green) compared to composites (orange) with model tonnage (blue)

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12.9

Resource Classification

The Mineral Resources of the Bongará deposit were classified based on the guidelines promulgated by CIM Definition Standards for Mineral Resources, November 27, 2010 (CIM) where resources are ranked in order of decreasing geological confidence into classes of Measured, Indicated and Inferred. Mineral domaining was the first level of classification. Mineral domains were bounded by drill intercepts, where the wireframe boundaries were defined half way between mineralized and non-mineralized samples on an interpreted grade horizon or structure. The structure and stratigraphic controls on the Bongará deposit are well understood; hence, all of the material in the block model inside the mineral domains achieved at least Inferred classification. Higher classification categories (Measured and Indicated) required close-spaced drilling.

Classification of the resources reflects the relative confidence of the grade estimates. This is based on several factors, including: sample spacing relative to the geological and geostatistical observations regarding the continuity of mineralization; mining history; specific gravity determinations; accuracy of drill collar locations; and quality and reliability of the assay data.

Resource classification at Bongará was based initially on numerical criteria, but benefited from a subsequent revision of classification boundaries into geologically sensible and coherent zones that reflect the appropriate level of geological and grade estimation confidence. This process of geologic refinement resulted in minor additions and subtractions of blocks compared to the numerical result.

Search radius criteria for resource classification are presented in Table 12.9.1. Figures 12-31 and 12-32 illustrate the comparison between a pure search-driven classification and the final resource classification of blocks. At the perimeter of the Measured and Indicated classification categories, the final classification, which had a geologist’s input, is more uniform and slightly conservative.

Table 12.9.1: Search Criteria and Extrapolation Limits for Resource Classification

Resource Classification	Interpolation	Extrapolation
Measured	25m	25m
Indicated	50m	25m
Inferred	100m	>50m

Source: Votorantim, 2013b

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Source: Votorantim, 2013b, annotated by SRK, 2014

Figure 12-31: Comparison of numerical (search pass) classification (left) and final "geologic" classification (right) in San Jorge domain

Source: Votorantim, 2013b, annotated by SRK, 2014

Figure 12-32: Comparison of numerical (search pass) classification (left) and final "geologic" classification (right) in Karen-Milagros domain

Certain conditions limited classification independent of sample spacing. These included:

Data from Cominco's campaigns lacked quality control for chemical analysis (QA /QC) and there were no density data recorded; and

Eight drill sites have an inadequate survey of the drill location, having been measured only by portable GPS.

In these cases, resources were classified as Inferred.

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Summary statistics after resource classification by search volume (search pass) are presented in Table 12.9.2. Blocks classified as Measured were estimated by Ordinary Kriging using an average of 5 samples, and are mostly (96%) within the 1st and 2nd search volumes, and demonstrate a low kriging variance (0.47). SRK is confident in the Measured classification because it its represents closely-spaced drilling, which is recent (2012-2013), and supported by reliable analytical quality control programs. Additionally, SRK has inspected the recent drill core and found it to demonstrate excellent mineral-horizon continuity.

Blocks classified as Indicated were estimated by Ordinary Kriging using an average of 3 samples, and are mostly (74%) within the 1st and 2nd search volume, with a kriging variance slightly higher relative to the previous category (0.53).

Table 12.9.2: Summary Statistics of Classified Blocks by Search Volume (SV)

Class	% of blocks in SV 1	% of blocks in SV 2	% of blocks in SV 3	Number of samples	Kriging variance
Measured	44%	52%	4%	5.01	0.47
Indicated	23%	51%	26%	3.73	0.53
Inferred	7%	33%	60%	5.59	0.51

Source: Votorantim, 2013b

A plan view of the final resource classification is illustrated in Figure 12-33.

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Figure 12-33: Plan View of Resource Classification

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12.10

Mineral Resource Statement

The Mineral Resource Statement for the Bongará zinc-lead-silver deposit is presented in Table 12.10.1.

Table 12.10.1: Mineral Resource Statement for the Bongará Zn-Pb-Ag Deposit, Amazonas Department, Peru, SRK Consulting (U.S.), Inc., 05 June, 2014

Category	Mass	Grade				Contained Metal (millions)
Category	Mass	Zn	Pb	Ag	ZnEq	Zn	Pb	Ag	ZnEq
	Mt	%	%	g/t	%	(lbs)	(lbs)	(oz)	tonnes	(lbs)
Measured	1.43	13.02	1.85	19.3	15.45	410.0	58.3	0.884	0.221	486.5
Indicated	1.35	12.51	1.71	17.1	14.74	372.6	50.9	0.744	0.199	438.8
Measured + Indicated	2.78	12.77	1.78	18.2	15.10	782.5	109.2	1.628	0.420	925.3
Inferred	9.07	10.87	1.21	12.2	12.44	2,173.0	241.5	3.554	1.130	2,487.6

Source: SRK, 2014

Notes:

i. *Metal price assumptions considered for the calculation of metal equivalent grades are: Zinc (US$/lb 0.95), Lead (US$/lb 0.95) and Silver (US$/oz 20.00),

iii. *** NSR factors for calculating cutoff grades were: ZnEq% = Zn% * 1 + Pb% * 0.74 + Ag g/t * 0.02

Resulting cutoff grades used in this resource statement were 4.1% ZnEq for sulfide, 5.0% ZnEq for oxide, and 4.5% ZnEq for mixed material types.

Zinc equivalency for reporting in situ resources was calculated using:

ZnEq (%) = Zn (%) + 1.0 * PB (%) + 0.03 * Ag (g/t)

Density was calculated based on material types and metal grades. The average density in the mineralized zone was 2.91 g/cm³ as a function of the zinc and lead sulfide mineral content.

Mineral Resources as reported are undiluted.

Mineral resource tonnage and contained metal have been rounded to reflect the precision of the estimate, and numbers may not add due to rounding.

The resource is comprised of 63% sulfide, 28% oxide and 9% mixed material types by contained zinc above cut-off. The cut-off grade was established based on a Net Smelter Return (NSR) zinc-equivalent (ZnEq%) for each material. The resulting cut-offs were as follows: 4.1% ZnEq% for sulfide, 5.0% ZnEq% for oxide, and 4.5% ZnEq% for mixed material types. Cut-off grades account for recovery and treatment/smelting charges.

The zinc-equivalent for reporting in situ resources in Table 12.10.1 was calculated based on metal price ratios of lead and silver relative to zinc as follows:

ZnEq (%) = Zn (%) +1.0 * PB (%) + 0.03 * Ag (g/t).

12.11

Cut-off Grade Determination

Mineral Resources were constrained by applying a zinc-equivalent (ZnEq%) cut-off grade to the model originally constructed by Votorantim and validated by SRK in this report. A cut-off grade was

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applied to ensure that the resources reported have a reasonable expectation of economic extraction in compliance with NI 43-101 guidelines.

At this stage of project development, SRK assumed that the Bongará deposit will be mined using underground cut and fill or other stoping methods and processed by conventional sulfide flotation to produce a concentrate that will be transported to an offsite smelter/refinery. Costs for mining and processing have been developed by SRK based on prior experience and from project development projections by Votorantim. Recovery estimates for all metals by material types were developed by SRK after a detailed review of metallurgical test work completed by Votorantim or their contractors as presented in Section 11 of this report. Resources are undiluted, apart from the constraint that a 2-3m minimum thickness was used when the mineral domains were constructed. The calculation for ZnEq% was based on Net Smelter Return (NSR) factors for contributing metals as follows:

ZnEq% = (Zn% * 1) + (Pb% * 0.74) + (Ag g/t * 0.02) for sulfide material

ZnEq% = Zn% for oxide material

ZnEq (%) = 0.59 * [Sulfide ZnEq (%)] + 0.41 * [Oxide ZnEq (%)] for mixed

The NSR values were based on the inputs and calculations presented in Table 12.11.1.

Table 12.11.1: Cut-off Grade Inputs and Calculations

ZnEq%, Sulfide			ZnEq%, Oxide
Mining Cost	$/mt	$15.30	Mining Cost	$/mt	$15.30
Processing Cost	$/mt ore	$9.40	Processing Cost	$/mt ore	$28.00
Transportation*	$/mt ore	$21.60	Transportation*	$/mt ore	$12.80
Smelting*	$/mt ore	$29.00	Smelting*	$/mt ore	$15.10
G&A	$/mt ore	$5.00	G&A	$/mt ore	$5.00
Total Cost	$/mt ore	$80.30	Total Cost	$/mt ore	$76.20
Mill Recovery		93.1%	Mill Recovery		73.0%
Sales price	US$/lb Zn	$0.95	Sales price	US$/lb Zn	$ 0.95
	US$/lb Pb	$0.95
	US$/oz Ag	$20.00
Cut-off grade, Mining	ZnEq%	4.1	Cut-off grade, Mining	ZnEq%	5.0
Cut-off Grade, Internal	ZnEq%	3.3	Cut-off Grade, Internal	ZnEq%	4.0

Source: SRK, 2014

*Transportation and smelting costs are based on tonnes of concentrate, which are factored to tonnes of ore.

12.12

Mineral Resource Sensitivity

The grade-tonnage curve for the Bongará Mineral Resource based on zinc equivalent grade is provided in Figure 12-34. Quantities include Measured, Indicated and Inferred Resources.

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Figure 12-34: Grade-Tonnage Curve Based on ZnEq%

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12.13

Relevant Factors

SRK is unaware of any environmental, permitting, legal, title, taxation or marketing factors that could limit or affect the resource stated in this document.

12.13.1

Equivalency

Mineral Resources were reported by SRK using a zinc equivalent grade. The inputs and calculations associated with the equivalency are presented in Section 12.11 and summarized in Table 12.11.1 of this report.

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Mineral Reserve Estimate (Item 15)

There were no Mineral Reserves estimated for the Bongará deposit. Further engineering studies by Votorantim in the areas of mine planning, metallurgy and mineral processing are currently underway, but are not at a level to support Mineral Reserves at this time.

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Mining Methods (Item 16)