Coffey Mining (SA) Pty Ltd (2006/030152/079) VAT Number (415 023 9327)

Block D, Somerset Office Estate, 604 Kudu Street, Allen’s Nek 1737 Roodepoort, South Africa www.coffey.com/mining

Resource Estimation of Tsumeb Tailings Dump, Namibia, August 2011

Prepared by Coffey Mining (SA) (Pty) Ltd on behalf of:

Weatherly International Plc

JTSU01

Coffey Mining Pty Ltd

Tsumeb dump– JTSU01 Page: i Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

Author(s): Rachel McKinney Consultant-Geology (MSC (Geology))

Brendan Botha Exploration Manager (BSc (Hons) Geology, MSc (ESPM), MSc (MRM), Pri.Sci.Nat, MGSSA)

Janine Fleming Senior Consultant- Resources

(BSc Hons Geology, Pr.Sci.Nat, MGSSA)

Kathleen Body Principal Consultant- Resources

(BS Arts and Sciences (Geology), GDE (Mining), Pr.Sci.Nat)

Date: August 2011

Project Number: JTSU01

Version / Status: v.01 / Final

Path & File Name: F:\Projects\Projects\Weatherly International\ JTSU01-Estimation of Tsumeb dump\Roport\JTSU01-Estimation of Tsumeb dump_Final.docx

Print Date: Friday, 26 August 2011

Copies: Weatherly International Plc (2)

Coffey Mining – Johannesburg (1)

Document Change Control

Version Description (section(s) amended) Author(s) Date

Document Review and Sign Off

Author Janine Fleming

Author Rachel McKinney

Author Brendan Botha

Supervising Principal Kathleen Body

This document has been prepared for the exclusive use of Weatherly International Plc (“Client”) on the basis of instructions, information and data supplied by them. No warranty or guarantee, whether express or implied, is made by Coffey Mining with respect to the completeness or accuracy of any aspect of this document and no party, other than the Client, is authorized to or should place any reliance whatsoever on the whole or any part or parts of the document. Coffey Mining does not undertake or accept any responsibility or liability in any way whatsoever to any person or entity in respect of the whole or any part or parts of this document, or any errors in or omissions from it, whether arising from negligence or any other basis in law whatsoever.

Coffey Mining Pty Ltd

Tsumeb dump– JTSU01 Page: ii Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

Table of Contents

EXECUTIVE SUMMARY .......................................................................................................................v

1 Introduction ................................................................................................................................7

1.1 Scope of Work.................................................................................................................7

1.2 Participants .....................................................................................................................8

1.3 Technical Report .............................................................................................................8

1.4 Disclaimer .......................................................................................................................9

1.5 Site and Technical Visits .................................................................................................9

1.6 Data Acquired .................................................................................................................9

2 Property Description ............................................................................................................... 10

2.1 Location and Access ..................................................................................................... 10

2.2 Physiography and Climate ............................................................................................ 12

2.3 Local Infrastructure and Services .................................................................................. 13

3 History ...................................................................................................................................... 13

4 Geological Setting ................................................................................................................... 14

4.1 Regional Geology .......................................................................................................... 14

4.2 Local Geology ............................................................................................................... 14

5 Mineralization ........................................................................................................................... 15

6 Data and verification ............................................................................................................... 16

6.1 Drilling ........................................................................................................................... 16

6.2 Sample Logging ............................................................................................................ 17

6.3 Sample Logging ............................................................................................................ 19

6.4 Bulk Density Measurements .......................................................................................... 19

6.5 Data Location ................................................................................................................ 19

6.6 Sample Analysis ............................................................................................................ 19

6.7 Analytical Quality Assurance and Quality Control Data ................................................. 19

7 Geological Modelling ............................................................................................................... 24

7.1 Introduction ................................................................................................................... 24

8 Statistical Analysis .................................................................................................................. 25

8.1 Introduction ................................................................................................................... 25

9 Block Model Development ...................................................................................................... 28

9.1 Introduction ................................................................................................................... 28

9.2 Block Construction Parameters ..................................................................................... 28

10 Grade Estimation ..................................................................................................................... 29

10.1 Introduction ................................................................................................................... 29

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10.2 Nearest Neighbour Estimate ......................................................................................... 29

11 Resource Reporting ................................................................................................................ 31

11.1 Introduction ................................................................................................................... 31

11.2 Criteria for Mineral Resource Classification ................................................................... 31

11.3 Application of Cut-off Grade and other Modifying Factors ............................................. 32

11.4 Mineral Resource Estimate Tabulation .......................................................................... 32

12 Conclusion ............................................................................................................................... 33

13 References ............................................................................................................................... 34

Coffey Mining Pty Ltd

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List of Tables Table 1.1 – Mineral Resources of the Tsumeb Dump vi

Table 6.7_1 – Summary of the Number of Control Samples 21

Table 6.7_2 – Summary of Certified Reference Standards Used 22

Table 8.1_1 – Descriptive Statistics 26

Table 9.2_1 – Block Model Construction Parameters 28

Table 10.2_1 – Nearest Neighbour estimation and search parameters 29

Table 10.2_2 – Block and drillhole grade comparison 30

Table 11.2_1 – Confidence Levels of Key Criteria 31

Table 11.4_1 – Measured Mineral Resource Estimate (August 2011) 32

List of Figures

Figure 2.1_1 – Location of the Tsumeb Dump Project 10

Figure 2.1_2 – Locality of Tsumeb Dump in relation to the town of Tsumeb 11

Figure 2.1_3 – Orthographic Photo of the Tsumeb Dump 12

Figure 6,1_1 – Tailings Dump Showing Boreholehole Locations 16

Figure 6.2_1 - Sampling Procedure 18

Figure 8.1_1 – Histograms of distributions 27

List of Appendices

Appendix A – Level Plans and Cross Sections of Copper Distribution in the Tsumeb Dump

Appendix B – Level Plans Of Copper Leached Distribution in the Tsumeb Dump

Appendix C – QAQC Plots

Coffey Mining Pty Ltd

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EXECUTIVE SUMMARY

Coffey Mining (SA) (Pty) Ltd was requested by Weatherly International Plc to complete a Mineral

Resource estimation of the Tailing Dump of the closed Tsumeb Copper Mine in Namibia. Reporting

was requested to conform to ‘Australasian Code for Reporting of Exploration Results, Mineral

Resources and Ore Reserves’ of December 2004 (the JORC Code) as prepared by the Joint Ore

Reserves Committee of the Australasian Institute of Mining and Metallurgy, Australian Institute of

Geoscientists and Mineral Council of Australia (JORC).

The Tsumeb Tailing Dump is on the northern boundary of the town of Tsumeb in Namibia, a town well

serviced with infrastructure, i.e. sealed roads, power and municipal water and waste services. There is

also a railway line connecting Tsumeb with Walvis Bay via Windhoek.

The Tsumeb Copper Mine is a world renowned polymetalic mine that was in production for just under

100 years. During its operation it produced 30 million tonnes of ore at 4.3% copper, 10% lead, 3.5%

zinc and 95g/t silver.

The Tsumeb Dump contains the waste product from the processed ore. It was constructed with a

single inflow pipe which was moved around the perimeter of the dump as required. The dump is

essentially a compound, pod-like deposit with grades varying from one pod to another due to variations

in the beneficiation process and recovery improvements over time. The dump’s dimensions are

approximately 1000m x 1000m x15m and consist mainly of finely crushed felspathic sandstone, which

was the host rock of the mineralization within the Tsumeb Mine. The mineralization of the dump is

directly linked to the original mineralogy of the mine and the recoveries of the copper-bearing minerals

during beneficiation. The dump also contains copper oxides that were not recovered prior 1986 as well

as lead, zinc and minor amounts of silver. The mineralization in the dump and its distribution is directly

linked to the operational day-to-day variations and recoveries.

A total of 112 auger boreholes were drilled by Dump & Dune who are specialists in drilling tailings and

other waste dumps. Samples were taken every meter and a half and sent to Bureau Veritas Laboratory

in Swakopmund for analysis and copper solubility. For the drilling and analysis a full quality control

program was establish to ensure the accuracy of the data collected. The referee samples sent to ALS

Chemex in Johannesburg did reveal some issues regarding the original analysis. The queries

regarding the referee results have not been resolved however these only involve the copper leach

assays which have not been used in the mineral resource estimation.

Statistical analysis of the borehole data that sufficient data was collected to have confidence in the

distribution of the various elements within the dump

A 3D model was created with survey data received from Namibian Custom Smelters for upper surface

and the base as interpreted from borehole logs. Due to the podlike nature of the mineralization, the

nearest neighbour estimation method was deemed most appropriate. The block model was constructed

such that not more than one sample was represented in a block. The tonnes calculated from the block

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model are based on densities obtained using on sand replacement tests. The density determined from

the samples taken is 1.4g/m2.

Data collected for the Tsumeb dump is sufficient and generally good quality. Therefore the Dump is

classified as a Measured Mineral Resource (Table 1).

{ TC “Table 1.1 – Mineral Resources of the Tsumeb Dump”\fi }

Table 1

Tsumeb Dump

Mineral Resources of the Tsumeb Dump

Tonnage (Mt) Density *Cu (%) Pb (%) Ag ppm Zn (%)

Measured 12 1.4 0.48 0.77 12.74 0.63

*PPM/10 000 = %

The samples were also submitted for sulphuric acid leach assay. The result of these analyses indicates

the copper by acid leaching is 0.3 % (average), which is 72% of the total estimated copper.

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1 INTRODUCTION

1.1 Scope of Work

Coffey Mining (SA) (Pty) Ltd (Coffey Mining) was requested by Weatherly International Plc

(Weatherly) to complete an estimation of the mineral resources on the Tsumeb Mine

Tailings Dump (Tsumeb Dump) at Tsumeb in Namibia.

Collectively Coffey Mining was commissioned to carry out the following activities for the

resource estimation study of the Tsumeb Dump:

Three dimensional modelling of the dump volume.

Quality Assurance and Quality Control (QA/QC) of assay laboratory.

Database generation, review and validation.

Statistical analysis.

Block model construction.

Completion and validation of the mineral resource estimate based on data obtained

during this phase of drilling. The elements to be estimated are Copper (Cu), Lead (Pb),

Zinc (Zn) and Silver (Ag), as well as contaminant elements Arsenic (As), Bismuth (Bi),

Cadmium (Cd), Mercury (Hg) and Sulphur (S).

Compilation of a JORC compliant report.

The report describes the methods used to define the mineral resource as well as the result

of the mineral resource estimation. The report also states the criteria used to classify the

mineral resources. It is understood that this report will be used for stock exchange reporting

purposes.

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1.2 Participants

The participants consist of a number of technical experts brought together by Coffey Mining

to complete the mineral resource estimate. The participants in the review and their

individual areas of responsibility are listed as follows:-

Rachel McKinney, Coffey Mining - : Consultant

MSc Geology

Site visits, QA/QC, data collection, report preparation

Janine Fleming, Coffey Mining - : Senior Consultant – Resources

(BSc (Hons) Geology , MGSSA, Pr.Sci.Nat)

Geological interpretations, mineral resource estimation, report preparation.

Brendan Botha, Coffey Mining - : Senior Consultant - Exploration

(BSc (Hons) Geology, MSc (Earth Science and Project Management), MSc (Mineral

Resource Management), Pr.Sci.Nat., MGSSA)

Project Management, report preparation

Kathleen Body, Coffey Mining - : Principal Consultant - Resources

(BS Arts and Sciences (Geology), GDE (Mining), Pr.Sci.Nat)

Peer Review, and Competent Person

Neither Coffey Mining, nor the key personnel nominated for the work, has any material

interest in Weatherly. The work, and any other work done by Coffey Mining for Weatherly, is

strictly in return for professional fees. Payment for the work is not in any way dependent on

the outcome of the work or on the success or otherwise of Weatherly’s own business

dealings. As such there is no conflict of interest in Coffey Mining undertaking the

independent mineral resource estimate as contained in this document.

1.3 Technical Report

The report has been compiled under the guidelines of the ‘Australasian Code for Reporting

of Exploration Results, Mineral Resources and Ore Reserves’ of December 2004 (the

JORC Code) as prepared by the Joint Ore Reserves Committee of the Australasian Institute

of Mining and Metallurgy, Australian Institute of Geoscientists and Mineral Council of

Australia (JORC).

This report is also compliant with the South African Code for Reporting of Mineral

Resources and Mineral Reserves (SAMREC Code) of 2007, prepared by The South African

Mineral Resource Committee (SAMREC) under the auspices of The South African Institute

of Mining And Metallurgy (SAIMM). The Competent person for the purposes of this report is

Kathleen Body who has supervized all aspects of the work reported. She is a registered

Professional Natural Scientist (Pr.Sci.Nat.) in terms of the Natural Scientific Professions Act

(Act 27 of 2003) and is a “Competent Person” as defined in the JORC and SAMREC Codes.

Kathleen Body is a full-time employee of Coffey Mining and has sufficient experience which

is relevant to the style of mineralization and type of deposit under consideration and to the

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activity which she is undertaking to qualify as a Competent Person as defined in the 2004

Edition of the ‘Australasian Code for Reporting of Exploration Results, Mineral Resources

and Ore Reserves’ and the South African Code for Reporting of Mineral Resources and

Mineral Reserves (SAMREC Code) of 2007. Kathleen Body consents to the inclusion in the

report of the matters based on her information in the form and context in which it appears.

1.4 Disclaimer

Coffey Mining has based its mineral resource estimate for the Tsumeb Dump on information

largely provided by Weatherly. This data includes third party technical reports along with

other relevant published and unpublished third party information. Coffey Mining has

endeavoured by making all reasonable enquiries to confirm the authenticity and

completeness of the third party technical data upon which this report is based. A final draft

of this report was provided to Weatherly, along with a written request to identify any material

errors or omissions, prior to finalisation.

Neither Coffey Mining, nor the authors of this report, are qualified to provide extensive

comment on legal facets associated with ownership and other rights pertaining to the

Tsumeb Dump.

No warranty or guarantee, be it express or implied, is made by Coffey Mining with respect to

the completeness or accuracy of the legal, environmental, metallurgical, mineral processing

or mineral resource estimate information contained in third party reports. While Coffey

Mining has reviewed such third party reports and relied on certain aspects of such reports in

reaching its conclusions herein, neither Coffey Mining nor the authors of this report accept

any responsibility or liability in any way whatsoever to any person or entity in respect of

information contained in such third party reports and documents and included in this

document, or any errors in or omissions from it, whether arising from negligence or any

other basis in law whatsoever.

1.5 Site and Technical Visits

A site visit was conducted by Mrs Rachel McKinney on 18 March 2011. The intention of the

site visit was to identify the property, understand its location and local infrastructure,

establish the nature of the exploration undertaken and confirm the positions of a selected

number of boreholes. In addition it was possible to verify the logging and sampling

procedures and confirm the quality of the exploration. A site visit to the laboratory, Bureau

Veritas, in Swakopmund Namibia, where the initial assays were to take place, was done

concurrently (17 March 2011). This visit was intended to assess laboratory operating

procedures, formal QA/QC procedures and capabilities.

1.6 Data Acquired

The data and information made available to Coffey Mining by Weatherly consisted of

electronic and hardcopies of geological data (collar coordinates, geological logs, assay data)

generated from the current drilling phase and surveyed topography files of the dump

surface. This data formed the basis from which the mineral resource estimation could be

completed.

Tsumeb dump JTSU01 Page: 10

2 PROPERTY DESCRIPTION

2.1 Location and Access

The Tsumeb Copper Mine, and its associated tailings dump, is located on the northern

boundary of the town of Tsumeb in northern Namibia (Figure 2.1._1). Figure 2.1_2 indicates

the location of the Tsumeb Dump in relation to the town of Tsumeb. Access to the project

area is a tarred road and the railway line passes the project area in the south. The project is

centred on coordinates 19°14’ South and 17°42’ East, at an approximate elevation of

1,300m above mean sea level (amsl). Figure 2.1_2 and 2.1_3 are a orthographic map of

the Tsumeb Dump.

{ TC “Figure 2.1_1 – Location of the Tsumeb Dump Project”\fj } Figure 2.1_1

Location of the Tsumeb Dump Project

Tsumeb Project

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Figure 2.1_2

Locality of Tsumeb Dump in relation to the town of Tsumeb

{ TC “Figure 2.1_2 – Locality of Tsumeb Dump in relation to the town of Tsumeb”\fj }

Tsumeb dump– JTSU01 Page: 12 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

Figure 2.1_3

Orthographic Photo of the Tsumeb Dump

{ TC “Figure 2.1_3 – Orthographic Photo of the Tsumeb Dump”\fj }

2.2 Physiography and Climate

The Tsumeb area is semi arid, with an average annual rainfall of 572mm, falling mainly from

December to April. However, rainfall is highly variable, and multiyear droughts are common.

The climate is sub-tropical, with mean summer temperatures averaging 35°C, and mean

winter temperatures average around 10°C. Field conditions are such that it is possible to

work all year round; poor weather conditions rarely disrupt exploration or mining operations.

Tsumeb is situated on the northern fringe of the Otavi Mountain land, a highland region that

extends approximately 100km east-west and 75km north-south. At the mine the landscape

is dominated by low hills. The Tsumeb Project area lies on a flat plain sandwiched between

low lying dolomitic hills both to the southern and northern sides.

The soil type is closely related to the bedrock lithology. Over the sandstone plain is a thin

red-brown sandy soil, overlying one to 10m of white calcrete. Below this calcrete are the

arenaceous sandstones of the Mulden Group. The dolomite hills are covered by a thin layer

of dark brown sandy soil, with abundant chert boulder rubble.

The vegetation in the plain is dominantly low bushland, comprised of Acacia and

Dichrostachys species, interspersed with open grassland. On the hills there is a more

diverse range of tree cover. The water table is at approximately 70 – 80m below surface.

The main land use activity in the area is cattle farming with minor game farming.

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2.3 Local Infrastructure and Services

The Tsumeb Dump lies almost adjacent to the major tarred road that links Tsumeb to

Etosha and Angola to the north. There is an electrical power line located on the project site.

The railway linking Tsumeb to Walvis Bay and Windhoek passes directly south of the

Tsumeb Dump.

Skilled labour and most services are available in Tsumeb, and Namibia has a well

established mining industry. Tsumeb serves as a base for providing a full range of urban

amenities, including medical and educational facilities, financial, retail and commercial

services. Tsumeb is a major tourist destination, thanks to the proximity of Etosha National

Park. Modern hotels, lodges, shops and restaurants are able to provide most services.

Telephone and mobile phone services are reliable, as are the high-speed internet facilities.

3 HISTORY

The Tsumeb Copper Mine is a world renowned copper deposit that was operational for just

under 100 years. In this period the mine changed ownership various times, up to its closure

in 1998.

Tsumeb Mine produced approximately 10 000t of copper and 20 000t of lead per annum

and during the period from 1954 to 1963 a germanium-enriched zinc concentrate was

produced (0.2 to 0.5% germanium).

The Tsumeb Dump, which was built-up from tailings fed from the flotation plant, comprises

finely crushed host rock with copper bearing minerals that were not recovered during the

beneficiation process. Not all of the tailings from the flotation plant were deposited on the

Tsumeb Dump. A large percentage was also used to produce cemented backfill for the

mine.

The beneficiation process was primarily by differential flotation up to 1987; thereafter a

gravity plant was installed to recover some oxides that did not react to flotation. This would

have caused a decrease in the copper bearing minerals in the Tsumeb Dump.

The total recorded production when the mine closed in 1998 was approximately 30Mt with

an average grade of 10% lead, 4.3% copper, 3.5% zinc and 95g/t silver (Maiden and

Hughes, 2000).

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4 GEOLOGICAL SETTING

4.1 Regional Geology

The Tsumeb Copper deposit is located within the Otavi Group, which is the northern

boundary of the Damara Belt. The Otavi Group represents the miogeosyncline sediments

on the boundary of the orthogeosyncline where stable tectonic processes existed and is

dominated by dolomite and limestone.

The neighbouring, central Damara depositional environment represents eugeosyncilal

facies. This eugeosyncline facies was subjected to more intense tectonic activities than the

Otavi Group and formed a central tectonic mountain range.

The Otavi Group sediments are followed by the Mulden Group sediments. These sediments

are syntectonic and were deposited around and within the central Damara geosynclines

tectonic mountain ranges. The Mulden Group consists predominantly of arkose,

conglomerate, felspathic sandstone, phyllite and limestone.

4.2 Local Geology

The Tsumeb Dump is a man-made structure and not formed by geological processes. The

dump was built up by means of a single inlet pipe that was moved at regular intervals

around the perimeter of the dump. The dump is essentially a compound, pod-like deposit

with grades varying from one pod to another due to variations in the beneficiation process

and recovery improvements over time.

The structure of the deposit is directly related to the type of material (host rock) that was

mined and the fluctuations in the beneficiation process. There were also intermittent

deposits of smelter dust deposited on the dump. This direct dependency on the efficiency of

the plant and the smelter dust quality contributes to the vertical variation of the deposit, with

regards to grades and mineralization.

The main copper mineral mined at the Tsumeb Copper Mine was tennantite; therefore the

majority of minerals in the dump should be tennantite and the secondary oxides that did not

react to flotation up to 1986.

The dump’s dimensions are approximately 1000m x 1000m x 15m high, consisting of mostly

finely crushed felspathic sandstone.

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5 MINERALIZATION

The Tumeb Mine is one of the most spectacular and complex base metal deposits in the

world however; the mineralization of the Tsumeb Dump is not well understood as it was

primarily a waste dump for the flotation circuit. The mineralization should correspond with

the mineralization of the original Tsumeb orebody less the economic portion. Cu solubility

results indicate that a large portion of the Dump’s copper mineralization occurs in oxide form

(72% solubility). There is also associated lead, silver and zinc.

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6 DATA AND VERIFICATION

6.1 Drilling

A nominal 75m by 75m drill pattern was employed over the Tsumeb Dumps, oriented east -

west. Four boreholes could not be drilled and sampled due to standing water. These were

borehole 3135, 3150 and 3166. A total of 112 boreholes were drilled. The borehole

locations were laid out and surveyed by a local surveyor, Eliert Schwarting of Schwarting

Land Surveyors.

Drilling was conducted and managed by Dump and Dune (Pty) Ltd who specialise in the

auger drilling of tailings using a handheld auger powered by a 1400kW hydraulic motor,

which was mounted separately on the ground. Core barrels and extension rod lengths used

were 1.5m, 3m or 4.5m. The core barrel comprises a rotating spiral encased in a counter

rotating stainless steel core barrel 50mm in diameter. All drilling, sampling and bagging was

done by the drill supervisor and a site visit was done at the start of the drilling program by

the project geologist to ensure the correct logging and sampling protocols were followed.

The rig is lightweight and man portable allowing access to all portions of the dumps.

{ TC “Figure 6,1_1 – Tailings Dump Showing Boreholehole Locations”\fj } Figure 6.1_1

Tsumeb Dump Showing Borehole Locations

The typical drilling procedure is as follows:

At each site a platform box is dug into the surface down to approximately 20cm to

stabilize the rods during drilling and remove topsoil.

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Drilling to 1.5m depth using the 1.5m core barrel. The sample is collected by extracting

the barrel and using the hydraulic motor to reverse the auger and redirect the material

into a plastic sample bag. This will typically happen in two to three stages as the entire

1.5m sample cannot fit into the core barrel due to volume taken up by the spiral within.

The 3m core barrel is then used mostly in two stages for the same reason stated

above. The second 1.5m sample increment is collected from the 3m core barrel.

There after the 4.5m core barrel is inserted. This will produce the third 1.5m sample.

On top of the 4.5m core barrel, the 1.5m extension rod is attached, then the 3m

extension, thereafter the 4.5m extension and so on to continue advancement at 1.5m

increments.

Depth to end of tailings could not be determined accurately as the exact point of bottom

intersection is not known unless bedrock was encountered. If soil was penetrated the exact

depth of soil could not be calculated due to material expansion in the auger and unknown

loss from the base of the auger on withdrawal. Depth estimations were made according to

the amount of material in the bags after separating tailings and sub soil. Accuracy is

estimated at better than 0.5m.

All holes were drilled to underlying soil or bedrock.

6.2 Sample Logging

The first two 1.5m samples, i.e. down to 3m depth, were collected by laying the rods

horizontally on trestles and reversing the motor to discharge the samples directly into plastic

bags. The auger was then removed from the outer sleeve over a length of 150mm PVC

pipe that had been cut in half lengthwise, and cleaned and the material added to the

sample. Material from the longer 4.5m rods was sampled manually by rotating the inner

spiral in the opposite direction with a hand crank. The first part of the sample is collected

from the nose of the core barrel, the remainder from the PVC pipe on extraction of the inner

auger as above. Sleeve, auger and pipe were cleaned with a cloth after each sample. If the

sample was wet then water was used to clean. All reasonable measures were taken to

ensure full sample recovery (Figure 6.2_1).

Each sample was given a unique sample number. The soil in the final run was given an

estimated depth in the log and bagged separately to the dump material. The soil sample

was then placed inside the bag containing the last dump sample and both samples were

assigned the same ticket number. The laboratory was instructed to give a suffix A to the

sample number for the dump material and a suffix B to the soil to differentiate between the

two. Where an impenetrable bottom was encountered it was noted in the log.

A sample ticket printed with the sample number was placed in the sample bag and a second

ticket with the same number was stapled into the fold at the top of the bag. Bags were

sealed within a half hour of sample extraction.

Samples were stored until transported in a closed vehicle to Bureau Veritas Laboratory in

Swakopmund, for moisture analysis, screening, drying and splitting off of representative

portions for chemical analysis.

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{ TC “Figure 6.2_1 - Sampling Procedure”\fj }

Figure 6.2_1: Sampling Procedure

From top, left to right

Reversing auger to discharge sample into bag

Removing auger from sleeve over PVC pipe

Collecting remaining sample from PVC pipe

Cleaning auger and sleeve between samples

Tagged and sealed sample bags

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6.3 Sample Logging

Tailings samples were logged by Dump and Dune in a very simple manner. Only the From

depth, To depth, and colour of the sample was noted on the logging sheet. Also if the

sample was particularly wet it was noted in the comments

Where subsoil was penetrated this was merely logged as soil and the colour mentioned.

The logs were entered into a Excel spreadsheet and a database compiled for geological

modelling purposes.

6.4 Bulk Density Measurements

A total of six surface bulk density samples were taken from the dumps. The sampling

methodology used to determine the density of the tailings material was to clear an area of

topsoil/organic matter and dig a square pit 0.5 m by 0.5m and 0.5 m deep. The sides are

finished off vertical and as smooth as possible.

Material excavated was carefully bagged into multiple bags and sent to the laboratory and

weighed to produce a wet weight. The material was then oven dried at 750C for 12 hours

and re-weighed to provide moisture estimation and from this an in situ dry bulk density was

calculated.

6.5 Data Location

All borehole collars were laid out and accurately surveyed by a local surveyor Eliert

Schwarting of Schwarting Land Surveyors, and the holes drilled right next to the surveyed

pegs. Namibian Custom Smelters which is located adjacent to the Tsumeb Dump had

conducted a DTM survey over the area which they released for use in order to model the top

surface of the dump.

6.6 Sample Analysis

All drill samples were collected from site and transported to Bureau Veritas Mineral

Laboratories in Swakopmund for analysis. Bureau Veritas Namibia is still awaiting final

accreditation but analysis is conducted following procedures based on ISO 9001 Quality

Management Systems and ISO 17025 accreditation.

The samples were first dried, de-lumped and riffle split to yield approximately 2.5kg before

being pulverized to 95% <75µ. The remaining sample was then stored to be composited at

a later date by the client. Once pulverized a 100g split was sent for wet chemistry and ICP.

A 0.25g sample was taken for each of a 4-acid digest and sulphuric acid leach (5% H2SO4

and 0.1% Supafloc) with ICP-OES and ICP-MS finish. The main elements of interest were

copper, lead, zinc and silver.

6.7 Analytical Quality Assurance and Quality Control Data

A comprehensive quality assurance and quality control (QA/QC) programme was

undertaken. The QA/QC programme identifies various aspects of the results that could

have negatively influenced the subsequent resource estimate. It was possible to identify

Tsumeb dump– JTSU01 Page: 20 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

samples that had been swapped, missing samples, and incorrect labelling amongst other

aspects.

The QA/QC aims to confirm both the precision and accuracy of the laboratory and thereby

confirm that the data used is of a sufficient quality for the mineral resource estimate.

The control samples used comprised of two different standards, a blank and a duplicate

within every 20 samples submitted. The intended aim was 5% coverage for each of the

control sample types. Further control on data integrity was achieved through submittal of

pulps to a referee laboratory (ALS Chemex, Johannesburg). The quality control data was

analysed on an on-going basis and generated some queries with the laboratory. The results

are presented in Appendix C.

Definition of terms related to the QA/QC protocols applied and subsequent evaluations are

provided below:

A standard is a reference sample with a known (statistically) element abundance and

standard deviation (certified independently). Reference standards are used to gauge the

accuracy of analytical reporting by comparing the pre-determined values to those reported

by the analytical laboratory used during an exploration project.

A blank is a standard with abundance of the element of interest below the level of detection

of the analytical technique (certified independently).

A duplicate is the split of a sample taken at a particular stage of the sampling process; e.g.

Field Duplicate.

The precision and accuracy will be discussed in terms of the following statistical measures

routinely applied by Coffey Mining.

Thompson and Howarth Plot showing the mean relative percentage error of

grouped assay pairs across the entire grade range, used to visualize precision

levels by comparing against given control lines.

Rank HARD Plot, which ranks all assay pairs in terms of precision levels measured

as half of the absolute relative difference from the mean of the assay pairs (HARD),

used to visualize relative precision levels and to determine the percentage of the

assay pairs population occurring at a certain precision level.

Mean vs HARD Plot, used as another way of illustrating relative precision levels by

showing the range of HARD over the grade range.

Mean vs HRD Plot is similar to the above, but the sign is retained, thus allowing

negative or positive differences to be computed. This plot gives an overall

impression of precision and also shows whether or not there is significant bias

between the assay pairs by illustrating the mean percent half relative difference

between the assay pairs (mean HRD).

Tsumeb dump– JTSU01 Page: 21 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

Correlation Plot is a simple plot of the value of assay 1 against assay 2. This plot

allows an overall visualisation of precision and bias over selected grade ranges.

Correlation coefficients are also used.

Quantile-Quantile (Q-Q) Plot is a means where the marginal distributions of two

datasets can be compared. Similar distributions should be noted if the data is

unbiased.

Quality control monitoring protocols involved submission of blanks, duplicates and certified

reference standards with the core sample batches. Originally after every 8th sample an

alternating blank or duplicate was allocated to the sampling sequence followed by a

standard as the 10th sample. The actual numbers of control samples submitted are shown

in Table 1.6_1. For field duplicates an empty sample bag was submitted for the laboratory

to split the previous sample after crushing during sample preparation. Two different

standards were used, one low and one high. Their expected values are in Table 1.6_2.

Both standards were supplied by African Mineral Standards (Pty) Ltd. Sand sourced from

the dunes near Swakopmund was used as the blank material, as the laboratory was using

the material and has tested it in the past.

{ TC “Table 6.7_1 – Summary of the Number of Control Samples”\fi }

Table 6.7_1

Tsumeb Dump Project

Summary of the Number of Control Samples

Control Type

Submitted Rate of Control

Total Number of Samples

Proportion of Total

Standards 1320

AMIS0149 63 4.8%

AMIS0158 58 4.4%

Duplicates 57 4.3%

Blanks 63 4.8%

Referee samples 65 5.0%

Tsumeb dump– JTSU01 Page: 22 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

{ TC “Table 6.7_2 – Summary of Certified Reference Standards Used”\fi }

Table 6.7_2

Tsumeb Dump Project

Summary of Certified Reference Standards Used

Expected Value and Two Between Laboratory Standard Deviations

Standard AMIS0149 AMIS0158

Element

EV 2 Std EV 2 Std (ppm) Dev (ppm) Dev

Ag 30.1 ±2.3 5.6* ±0.9*

As 205 ±23 NC NC

Cu 3769 ±206 370 ±16

Pb 17100 ±800 2162 ±192

Zn 153700 ±6400 16200 ±600

All standards supplied by African Mineral Standards (Pty) Ltd

* Provisional Concentration NC - Not Certified

Blanks

Most blanks reported higher than three times detection limit for each element though much

lower than the actual tailings samples. It is suspected that the dune sand used for the blanks

carries minor grade causing the higher than expected results and should not be used in

future, a washed silica sand should rather be used. It can also be seen that the results return

higher in the last two batches which could be due to slight contamination from previous

samples during the preparation stage.

AMIS0149

Most results for Ag, As and Zn returned within two standards deviations of the expected

values with a bias of 2% or less. A single sample, C11680 returned blank results in all

elements except Cu, it is suspected that this is an error caused in the laboratory. It was asked

to re-assay but there was insufficient sample to re-analyse.

Most of the Cu results returned higher than expected with a bias of 4.8%, though all except six

were within two standard deviations of the EV. Samples of this standard that were sent to the

referee laboratory also produced higher results than the EV. During the round robin analysis

for standard certification some laboratories also reported similar results for Cu. It is most

likely a slight calibration issue causing the higher results and this is not a concern for the

mineral resource estimation.

Three Pb results returned results far lower than expected. These have all been followed up

with the laboratory and have been corrected. The EV for Pb is outside of the calibration range

for ICP and it was confirmed by the laboratory that the correct assays were not taken from the

fusion results.

Tsumeb dump– JTSU01 Page: 23 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

AMIS0158

Most results have returned within two standard deviations of the EV except sample C11550.

This sample does not correspond to any other QA/QC sample nor is it an obvious sample

transposition. The laboratory was asked to re-assay, including five samples above and below.

but similar results were returned. When this sample is removed from the dataset all elements

have an acceptable bias of less than 4%.

Field Duplicates

Of all data pairs grading better than ten times detection limit 90% or more are within 10%

HARD precision limits for all elements. In all cases bar one where the duplicate sample was

preceded by a soil sample (suffix B), it was the dump sample above that which was duplicated

(suffix A) not the soil sample. The laboratory did not follow requested procedures exactly.

With two of the duplicate pairs it could not be ascertained which sample had been duplicated.

These two samples were C11309 and C11489.

Referee Analysis

Pulps were sent to ALS Chemex laboratory in Johannesburg. The analytical techniques

employed were the same as those utilised by Bureau Veritas in the primary analysis to ensure

compatibility of data. All standards returned acceptable values. All elements show

acceptable precision and accuracy with <11% difference bias between laboratories. There

was a problem with samples from batch S0348 for Cu leach assays. The original results from

Bureau Veritas are approximately 45% less than the results obtained from ALS. This has

been queried with Bureau Veritas and the initial response is that they confirmed a dilution

error and corrected the results by applying a mathematical factor to the all the Cu leach

results from this batch. Coffey Mining is of the opinion that this is not correct as the solubility

is related to the copper minerals present and is unlikely to be linear but rather related to the

type and habit of copper minerals throughout the grade range.

Tsumeb dump– JTSU01 Page: 24 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

7 GEOLOGICAL MODELLING

7.1 Introduction

The Tsumeb Dump was modelled using the 3D software package Datamine™.

A model was generated for the surface of the dump and the base of the dump. The surface of

the dump is based on the survey supplied to Coffey Mining from Namibian Custom Smelters.

The interpretation of the base of the dump is based on the coding in the borehole data where

soil first appears in the log, as mentioned in Section 6.1, this method of defining the base has

an approximate error of 0.5m.

Tsumeb dump– JTSU01 Page: 25 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

8 STATISTICAL ANALYSIS

8.1 Introduction

Statistical analyses were completed on the Tsumeb Dump for the raw data in the de-surveyed

borehole file which is based on the analysis received from the laboratory.

Statistical analysis and distribution histograms were calculated for Cu, Pb, Ag and Zn as well

as for minor elements; arsenic (As), sulphur (S), cadmium (Cd) as well as Cu leached. These

are shown in Table 8.1_1 and Figure 8.1_1.

The statistical analysis indicates that the major elements and Cu leached approximate normal

distributions except for Ag, which is positively skewed. This can be due to the low

concentrations of Ag found in the dump.

The minor elements Cd and As have normal distributions. Sulphur (S) is positively skewed.

All the elements the statistical analysis was based on have a moderate to large co-efficient of

variation, especially the minor elements. This is due to the way the dump was built, the

operational fluctuations, and recovery improvement with time of the beneficiation process.

The statistical analysis indicates that there is adequate understanding of the variation in the

Tsumeb Dump to do a high level resource classification.

Level plans and cross sections of the Cu distribution on a 5m and 10m elevation from surface

is appended in Appendix A and for Cu solubility in Appendix B

Tsumeb dump– JTSU01 Page: 26 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

Table 8.1_1

Tsumeb Dump

Descriptive Statistics (based on Borehole Data) – Values presented in PPM

Cu Pb Ag Zn As S Cd Cu leached

Number 1075.00 1075.00 1075.00 1075.00 1075.00 1075.00 1075.00 1072.00

Minimum 208.00 0.00 0.00 0.00 2.00 0.00 0.00 0.00

Maximum 31900.00 91500.00 119.00 89000.00 8760.00 70000.00 2800.00 10800.00

Mean 4935.11 9027.95 13.01 6826.67 1910.04 2444.19 176.95 3524.79

Median 4460.00 8590.00 11.00 6040.00 1900.00 1900.00 144.00 3290.00

Std Dev 74.49 169.36 0.25 163.41 31.40 88.05 5.46 54.61

Std Error 2442.22 5552.83 8.12 5357.65 1029.45 2886.99 178.99 1787.97

Coeff Var 0.49 0.62 0.62 0.78 0.54 1.18 1.01 0.51

{ TC “Table 8.1_1 – Descriptive Statistics”\fi }

Tsumeb dump– JTSU01 Page: 27 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

Figure 8.1_1

Tsumeb Dump Showing Borehole Locations

{ TC “Figure 8.1_1 – Histograms of distributions”\fj }

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Tsumeb dump– JTSU01 Page: 28 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

9 BLOCK MODEL DEVELOPMENT

9.1 Introduction

A three dimensional block model was constructed for the area of interest, covering all the data

and interpreted dump volume.

9.2 Block Construction Parameters

A sub-block model was used to construct the Tsumeb Dump. The parent block size

(75mE x 75mN x 1.5mRL) was selected on the basis of the borehole spacing and the

estimation method. For the nearest neighbour estimation method it is advisable to have not

more than one sample per block. Sub-blocking to a 9.375mE x 9.375mN x 0.075mRL cell

size was undertaken to allow the effective volume representation of the interpretation based

on the wireframes (Table 9.2_1).

Table 9.2_1

Tsumeb Dump

Block Model Construction Parameters

Minimum (m) Maximum (m) Extent (m) No of Blocks Parent/Sub Block

Size(m)

X 74500 76000 1500 20 75/9.375

Y 306100 307000 900 12 75/9.375

Z 1250 1295 45 30 1.5/0.075

{ TC “Table 9.2_1 – Block Model Construction Parameters”\fi }

A block model for the grade estimation was generated using the modelled surfaces for the

topography of the dump and the base of the dump, and filling the volume between the two

surfaces.

Tsumeb dump– JTSU01 Page: 29 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

10 GRADE ESTIMATION

10.1 Introduction

The resource estimation for the Tsumeb Dump was completed using a nearest neighbour

estimation method. Based on the fact that the dump had been constructed using a single inlet

which had been re-positioned over time, nearest neighbour estimation was deemed to provide

the most accurate representation of the grade distribution within the dump. This method also

has a proven track record in the estimation of old gold mine dumps in South Africa. Grade

estimation was carried out using the Datamine software.

10.2 Nearest Neighbour Estimate

A Nearest Neighbour (NN) estimate was completed for the entire dump area. A two pass

estimation strategy was applied using progressively expanded and less restrictive searches to

successive estimation passes. The search parameters were determined from the borehole

spacing and block sizes and are shown in Table 10.2_1.

Table 10.2_1

Tsumeb Dump

Nearest Neighbour estimation and search parameters

Estimation Pass

Rotation Search Distance

X Y Z X Y Z

1 0 0 0 100 100 20

2 0 0 0 150 150 50

{ TC “Table 10.2_1 – Nearest Neighbour estimation and search parameters”\fi }

As the estimation method was nearest neighbour- it was not necessary to limit the number of

samples used as the estimation method simply uses the nearest sample value for each block.

All relevant statistical information was recorded in order to validate and review the estimate.

The recorded information included average distance to sample per block estimate.

The model was checked visually and statistically to ensure the results could be confidently

reported. The statistical analysis compared the block average for each estimated element to

that of the raw borehole data (Table 10.2_2). In most cases the model grade compares very

well to the original borehole average grade, except in the case of Bi, where there is a

considerable discrepancy between the two averages. This is due to the amount of data

available and the very low values reported for Bi

Tsumeb dump– JTSU01 Page: 30 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

{ TC “Table 10.2_2 – Block and drillhole grade comparison”\fi }

Table 10.2_2

Tsumeb Dump

Block and Borehole grade comparison – Values presented in PPM

Block Grade Borehole grade Difference %

Ag 12.,74 13.01 -2.16

Cu 4788.88 4935.11 -3.05

Pb 7715.26 9027.95 -17.01

Zn 6319.59 6826.66 -8.02

As 1727.84 1910.04 -10.56

Bi 0.78 0.37 52.51

Cd 158.38 176.95 -11.72

Hg 2.23 2.31 -3.75

S 2407.24 2444.19 -1.53

Cu leached 3432.49 3524.79 -2.69

Tsumeb dump– JTSU01 Page: 31 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

11 RESOURCE REPORTING

11.1 Introduction

Based on the assessment of borehole spacing, geological understanding and grade

estimation, and the confidence in the analyses the mineral resource is classified as an

Indicated Mineral Resource.

11.2 Criteria for Mineral Resource Classification

The mineral resource classification has been based on the robustness of the various data

sources available, confidence of the geological interpretation, variography and various

estimation service variables (e.g.: distance to data, etc). The higher the confidence levels

shown in the key criteria, the better the confidence in the resource and thus, the better the

resource classification i.e. highest confidence would enable a resource classification of

Measured, lowest confidence would enable a resource classification of Inferred. Confidence

levels do vary slightly between man-made deposits such as dumps, and in situ mineral

resources, however the classification mechanism remains the same; highest confidence –

Measured Resource. The resource estimate has been classified as an Measured Mineral

Resource based on the criteria set out in Table 11.2_1.

{ TC “Table 11.2_1 – Confidence Levels of Key Criteria”\fi }

Table 11.2_1

Tsumeb Dump

Confidence Levels of Key Criteria

Items Discussion Confidence

Drilling Techniques Auger drilling *high

Logging Standard nomenclature logged in Excel spreadsheet moderate

Borehole Sample Recovery Recovery +80% high

Sub-sampling Techniques and Sample Preparation

Sub-sampling techniques were not used N/A

Quality of Assay Data Most of the available data is of industry standard quality but there are still unresolved assay issues.

moderate

Verification of Assaying Referee analysis completed with good correlation but there are still unresolved assay issues with Cu solubility, but does not effect the resource status of the Dump

Moderate - high

Location of Sampling Points Survey of all collars. Vertical boreholes with typically small deviation.

high

Data Density and Distribution Boreholes spaced across the dump on a 75 m grid high

Database Integrity Minor errors identified and rectified. Data scrutinized prior to inclusion in resource model database.

high

Geological Interpretation Top of dump has been surveyed and bottom contacts for the dump were well defined based on drilling intersections

moderate

Compositing Composites were not used. N/A

Statistics Low coefficient of variation for the variables modeled and relatively well defined statistical distributions.

moderate

Block size Block size selected based on drilling spacing and estimation method moderate

Estimation and Modeling Techniques Nearest Neighbour *high

Cut off Grades No cut-off applied N/A

Mining Factors or Assumptions Total extraction is assumed moderate

Metallurgical Factors or Assumptions None N/A

* Only applicable to tailing dumps

Tsumeb dump– JTSU01 Page: 32 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

11.3 Application of Cut-off Grade and other Modifying Factors

The Tsumeb Dump will be reclaimed by hydraulic mining from the top of the dump to the

bottom. This type of mining/dump reclamation makes the mining of selective areas difficult.

Therefore, no cut-off grade was applied in the resource estimation as it is assumed that the

total dump will be reclaimed and processed.

No “geological” losses were incorporated in the Mineral Resource estimation as there should

not be any structures present in the dump that will cause losses and a 100% reclamation of

the dump is assumed.

11.4 Mineral Resource Estimate Tabulation

The Mineral Resource is tabulated in Table 11.4_1

{ TC “Table 11.4_1 – Measured Mineral Resource Estimate (August 2011)”\fi }

Table 11.4_1

Tsumeb Dump

Indicated Mineral Resource (August 2011)

Tonnage

(Mt) Density *Cu (%) Pb (%) Ag ppm Zn (%)

Measured 12 1.4 0.48 0.77 12.74 0.63

*PPM/10 000 = %

Tsumeb dump– JTSU01 Page: 33 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

12 CONCLUSION

The Tsumeb Dump consists mainly of the crushed tails from the flotation circuit of the Tsumeb

Copper Mine’s beneficiation plant (specifically the flotation circuit).

The drilling of dump, taking of the samples and implementation of QAQC procedures were

conducted under the supervision of Coffey Mining. This was done to ensure a high level of

confidence in the data and the estimation of the dump.

The statistical analyses of the data obtained from the assayed samples indicate that sufficient

information and knowledge regarding the variation of the data existed on which to base a

resource estimate.

The quality control procedures, which are implemented to ensure accuracy of the analysis,

revealed various issues with the original result from the laboratory. Not all queries submitted

to the laboratory have been address adequately; quality of the assays results is compromised

resulting in a low level of confidence for some parts of the assay results especially Cu

solubility.

The mineral resource estimate is based on the dump topography and the base of the dump,

as interpreted from borehole logs, wireframes created in Datamine. While the quality of the

data is generally good. As a result the mineral resource is classified as Measured.

A Measured Mineral Resource with 12 million tonnes at 0.48% Cu was estimated for the

Tsumeb Dump.

Tsumeb dump– JTSU01 Page: 34 Resource Estimation of Tsumeb Tailings Dump, Namibia – August 2011

13 REFERENCES

Brown, I et al. 2009.Tscudi Copper Deposit, Geological Modelling and Resource Estimate.

Coffey Mining Report for Weatherly Mining Namibia Ltd.

Gebhard, G.1999. Tsumeb. Pub. G.G. Publishing, Grossenseifen, Germany

Grunert, N. 2000. Namibia. Fascination of Geology. A Travel Handbook. Pub.Klaus Hess

Publishers, Germany.

Lombaard, A.F. et al. 1986. The Tsumeb Lead-Copper-Zinc-Silver Deposit, South West

Africa/Namibia. Mineral Deposits of South Africa. pp.1761-1787

Mineralogical Record. 1977. Tsumeb. Ed.Wilson, W.E. Pub. The Mineralogical Record Inc.,

Maryland, USA.vol.8, no.3 (May-June 1977)

Ministry of Mines and Energy, Geological Survey. 1992. The Mineral Resources of Namibia.

pp. 2.3-52 to 2.3-69, 2.5-2 to 2.5-9

Sohnge,G. 1967. Tsumeb a historical sketch. Pub. Committee of the S.W.A. Scientific

Society, Windhoek

Appendix A Level Plans and Cross Sections of Copper

Distribution in the Tsumeb Dump { TC “Appendix A – Level Plans and Cross Sections of Copper Distribution in the Tsumeb Dump”\fa }

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[ ABSENT]

[ 450, 3000]

[ 3000, 6000]

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Appendix A (a) – Level plan of Copper distribution 5m below top surface

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[ ABSENT]

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Appendix A (b) – Level plan of Copper distribution 10m below top surface with section lines

Section 1 Section 2 Section 3

Section 4

Section 5

Section 6

Appendix A (c) – Section 1

Appendix A (d) – Section 2

Appendix A (e) – Section 3

Appendix A (f) – Section 4

Appendix A (g) – Section 5

Appendix A (h) – Section 6

Appendix B Level Plans of Copper Leached Distribution

in the Tsumeb Dump { TC “Appendix B – Level Plans Of Copper Leached Distribution in the Tsumeb Dump”\fa }

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306600 N 306600 N

306700 N 306700 N

306800 N 306800 N

306900 N 306900 N

307000 N 307000 N

Cu ppm

[ ABSENT]

[ 450, 3000]

[ 3000, 6000]

[ 6000, 9000]

[ 9000, 15000]

[ 15000, 19000]

[19000,22000]

Appendix B (a) – Level plan of Copper Leached distribution 5m below top surface

74

700

E

7470

0 E

74

800

E

7480

0 E

74

900

E

7490

0 E

75

000

E

7500

0 E

75

100

E

7510

0 E

75

200

E

7520

0 E

75

300

E

7530

0 E

75

400

E

7540

0 E

75

500

E

7550

0 E

75

600

E

7560

0 E

75

700

E

7570

0 E

75

800

E

7580

0 E

75

900

E

7590

0 E

76

000

E

7600

0 E

76

100

E

7610

0 E

76

200

E

7620

0 E

306100 N 306100 N

306200 N 306200 N

306300 N 306300 N

306400 N 306400 N

306500 N 306500 N

306600 N 306600 N

306700 N 306700 N

306800 N 306800 N

306900 N 306900 N

307000 N 307000 N

Cu ppm

[ ABSENT]

[ 450, 3000]

[ 3000, 6000]

[ 6000, 9000]

[ 9000, 15000]

[ 15000, 19000]

[19000,22000]

Appendix B (b) – Level plan of Copper Leached distribution 10m below top surface

Appendix C QAQC Plots

{ TC “Appendix C – QAQC Plots”\fa }

QA/QC Plot; AMIS0149 Ag

QA/QC Plot; AMIS0149 As

Standard: AMIS0149 No of Analyses: 63Element: Ag Minimum: 0.25Units: Maximum: 36.00Detection Limit: Mean: 30.60Expected Value (EV): 30.10 Std Deviation: 4.19E.V. Range: 27.80 to 32.40 % in Tolerance 74.60 %

% Bias 1.66 %% RSD 13.71 %

0

10

20

30

40

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Ag

ppm

(g

/t)

Lab Batch No

Standard Control Plot(Standard: AMIS0149)

Ag ppm Expected Value = 30.10 EV Range (27.80 to 32.40) Mean of Ag ppm = 30.60

-30

-20

-10

0

10

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

Ag

pp

m -

Me

an

(g

/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0149)

Ag ppm Mean of Cumulative Sum of Ag ppm - Mean (g/t) = -6.13

-20

-10

0

10

20

30

40

S00

33

1

S00

34

8

S00

34

9

S00

38

0

S00

38

1

S00

38

3

Cu

mu

lati

ve S

um

of

Ag

ppm

- E

xp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0149)

Ag ppm Mean of Cumulative Sum of Ag ppm - Expected Value (g/t) = 9.84

Standard: AMIS0149 No of Analyses: 63Element: As Minimum: 0.50Units: Maximum: 256.00Detection Limit: Mean: 208.91Expected Value (EV): 205.00 Std Deviation: 30.87E.V. Range: 182.00 to 228.00 % in Tolerance 80.95 %

% Bias 1.91 %% RSD 14.78 %

0

100

200

300

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

As p

pm

(g/

t)

Lab Batch No

Standard Control Plot(Standard: AMIS0149)

As ppm Expected Value = 205.00 EV Range (182.00 to 228.00) Mean of As ppm = 208.91

-200

-100

0

100

200S

00

331

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

As p

pm

- M

ea

n (

g/

t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0149)

As ppm Mean of Cumulative Sum of As ppm - Mean (g/t) = 5.14

-200

-100

0

100

200

300

S0

033

1

S0

034

8

S0

034

9

S0

038

0

S0

038

1

S0

038

3

Cu

mula

tiv

e S

um

of

As p

pm

- E

xp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0149)

As ppm Mean of Cumulative Sum of As ppm - Expected Value (g/t) = 130.35

QA/QC Plot; AMIS0149 Cu

QA/QC Plot; AMIS0149 Pb

Standard: AMIS0149 No of Analyses: 63Element: Cu Minimum: 3,390.00Units: Maximum: 4,330.00Detection Limit: Mean: 3,948.25Expected Value (EV): 3,769.00 Std Deviation: 184.75E.V. Range: 3,563.00 to 3,975.00 % in Tolerance 57.14 %

% Bias 4.76 %% RSD 4.68 %

3200

3400

3600

3800

4000

4200

4400

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

pp

m (

g/

t)

Lab Batch No

Standard Control Plot(Standard: AMIS0149)

Cu ppm Expected Value = 3,769.00 EV Range (3,563.00 to 3,975.00) Mean of Cu ppm = 3,948.25

-1000

0

1000

2000

3000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

Cu

pp

m -

Me

an

(g

/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0149)

Cu ppm Mean of Cumulative Sum of Cu ppm - Mean (g/t) = 1,301.43

0

2000

4000

6000

8000

10000

12000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

Cu

pp

m -

Exp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0149)

Cu ppm Mean of Cumulative Sum of Cu ppm - Expected Value (g/t) = 7,037.56

Standard: AMIS0149 No of Analyses: 63Element: Pb Minimum: 8.00Units: Maximum: 19,000.00Detection Limit: Mean: 16,141.40Expected Value (EV): 17,100.00 Std Deviation: 2,251.19E.V. Range: 16,300.00 to 17,900.00 % in Tolerance 41.27 %

% Bias -5.61 %% RSD 13.95 %

0

5000

10000

15000

20000

S00

331

S00

348R

S00

349 R

S00

380

S00

381

S00

383

Pb p

pm

(g/t)

Lab Batch No

Standard Control Plot(Standard: AMIS0149)

Pb ppm Expected Value = 17,100.00 EV Range (16,300.00 to 17,900.00) Mean of Pb ppm = 16,141.40

-5000

0

5000

10000

15000

20000S00

331

S00

348R

S00

349 R

S00

380

S00

381

S00

383C

um

ula

tive S

um

of

Pb p

pm

- M

ean (

g/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0149)

Pb ppm Mean of Cumulative Sum of Pb ppm - Mean (g/t) = 7,710.03

-70000-60000-50000-40000-30000-20000-10000

010000

S00

331

S00

348R

S00

349 R

S00

380

S00

381

S00

383

Cum

ula

tive S

um

of

Pb p

pm

- E

xpect

ed V

alu

e (

g/t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0149)

Pb ppm Mean of Cumulative Sum of Pb ppm - Expected Value (g/t) = -22,965.27

( )

QA/QC Plot; AMSI0149 Zn

QA/QC Plot; AMSI0158 Ag

Standard: AMIS0149 No of Analyses: 63Element: Zn Minimum: 1.00Units: Maximum: 178,000.00Detection Limit: Mean: 150,369.86Expected Value (EV): 153,700.00 Std Deviation: 27,359.79

E.V. Range:148,300.00 to

159,100.00 % in Tolerance 50.79 %% Bias -2.17 %% RSD 18.19 %

0

50000

100000

150000

200000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Zn

pp

m (

g/

t)

Lab Batch No

Standard Control Plot(Standard: AMIS0149)

Zn ppm Expected Value = 153,700.00 EV Range (148,300.00 to 159,100.00) Mean of Zn ppm = 150,369.86

-100000

0

100000

200000

300000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

Zn

pp

m -

Mea

n (

g/

t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0149)

Zn ppm Mean of Cumulative Sum of Zn ppm - Mean (g/t) = 127,195.30

-300000

-200000

-100000

0

100000

200000

300000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

Zn

pp

m -

Ex

pecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0149)

Zn ppm Mean of Cumulative Sum of Zn ppm - Expected Value (g/t) = 20,630.73

Standard: AMIS0158 No of Analyses: 56Element: Ag Minimum: 3.50Units: Maximum: 13.00Detection Limit: Mean: 5.94Expected Value (EV): 5.60 Std Deviation: 1.15E.V. Range: 4.70 to 6.50 % in Tolerance 91.07 %

% Bias 6.03 %% RSD 19.36 %

2

4

6

8

10

12

14

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Ag p

pm

(g/

t)

Lab Batch No

Standard Control Plot(Standard: AMIS0158)

Ag ppm Expected Value = 5.60 EV Range (4.70 to 6.50) Mean of Ag ppm = 5.94

-4-3

-2-1

01

23

4S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

mula

tiv

e S

um

of

Ag p

pm

- M

ea

n (

g/

t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0158)

Ag ppm Mean of Cumulative Sum of Ag ppm - Mean (g/t) = -0.05

0

5

10

15

20

25

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cum

ula

tiv

e S

um

of

Ag p

pm

- E

xp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0158)

Ag ppm Mean of Cumulative Sum of Ag ppm - Expected Value (g/t) = 9.57

QA/QC Plot; AMSI0158 Cu

QA/QC Plot; AMSI1058 Pb

Standard: AMIS0158 No of Analyses: 56Element: Cu Minimum: 342.00Units: Maximum: 2,690.00Detection Limit: Mean: 424.21Expected Value (EV): 370.00 Std Deviation: 305.92E.V. Range: 354.00 to 386.00 % in Tolerance 62.50 %

% Bias 14.65 %% RSD 72.11 %

0

500

1000

1500

2000

2500

3000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

pp

m (

g/

t)

Lab Batch No

Standard Control Plot(Standard: AMIS0158)

Cu ppm Expected Value = 370.00 EV Range (354.00 to 386.00) Mean of Cu ppm = 424.21

-2500

-2000

-1500

-1000

-500

0

500

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

mu

lati

ve S

um

of

Cu

pp

m -

Me

an

(g

/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0158)

Cu ppm Mean of Cumulative Sum of Cu ppm - Mean (g/t) = -899.50

-1000

0

1000

2000

3000

4000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

mu

lati

ve S

um

of

Cu

pp

m -

Exp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0158)

Cu ppm Mean of Cumulative Sum of Cu ppm - Expected Value (g/t) = 645.61

Standard: AMIS0158 No of Analyses: 56Element: Pb Minimum: 1,800.00Units: Maximum: 13,100.00Detection Limit: Mean: 2,333.57Expected Value (EV): 2,162.00 Std Deviation: 1,462.98E.V. Range: 1,970.00 to 2,354.00 % in Tolerance 78.57 %

% Bias 7.94 %% RSD 62.69 %

0

2000

4000

6000

8000

10000

12000

14000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Pb p

pm

(g

/t)

Lab Batch No

Standard Control Plot(Standard: AMIS0158)

Pb ppm Expected Value = 2,162.00 EV Range (1,970.00 to 2,354.00) Mean of Pb ppm = 2,333.57

-10000

-8000

-6000

-4000

-2000

0

2000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

mula

tiv

e S

um

of

Pb p

pm

- M

ea

n (

g/

t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0158)

Pb ppm Mean of Cumulative Sum of Pb ppm - Mean (g/t) = -4,224.46

-2000

0

2000

4000

6000

8000

10000

12000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

mula

tive S

um

of

Pb p

pm

- E

xp

ect

ed V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0158)

Pb ppm Mean of Cumulative Sum of Pb ppm - Expected Value (g/t) = 665.32

QA/QC Plot; AMIS0158 Zn

QA/QC Plot; Blank Ag

Standard: AMIS0158 No of Analyses: 56Element: Zn Minimum: 14,200.00Units: Maximum: 19,300.00Detection Limit: Mean: 15,948.21Expected Value (EV): 16,200.00 Std Deviation: 1,034.41E.V. Range: 15,600.00 to 16,800.00 % in Tolerance 35.71 %

% Bias -1.55 %% RSD 6.49 %

14000

15000

16000

17000

18000

19000

20000

S00

33

1

S00

34

8

S00

34

9

S00

38

0

S00

38

3

Zn

pp

m (

g/

t)

Lab Batch No

Standard Control Plot(Standard: AMIS0158)

Zn ppm Expected Value = 16,200.00 EV Range (15,600.00 to 16,800.00) Mean of Zn ppm = 15,948.21

-4000-2000

02000

40006000

800010000

12000

S0

033

1

S0

034

8

S0

034

9

S0

038

0

S0

038

3

Cu

mula

tiv

e S

um

of

Zn p

pm

- M

ea

n (

g/

t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: AMIS0158)

Zn ppm Mean of Cumulative Sum of Zn ppm - Mean (g/t) = 3,686.61

-15000

-10000

-5000

0

5000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

83

Cu

mu

lati

ve S

um

of

Zn

pp

m -

Exp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: AMIS0158)

Zn ppm Mean of Cumulative Sum of Zn ppm - Expected Value (g/t) = -3,489.29

Standard: BLANK No of Analyses: 63Element: Ag Minimum: 0.25Units: Maximum: 2.50Detection Limit: Mean: 0.39Expected Value (EV): 1.50 Std Deviation: 0.43E.V. Range: 1.35 to 1.65 % in Tolerance 0.00 %

% Bias -74.07 %% RSD 109.73 %

0.0

0.5

1.0

1.5

2.0

2.5

S0

033

1

S0

034

8

S0

034

9

S0

038

0

S0

038

1

S0

038

3

Ag p

pm

(g/

t)

Lab Batch No

Standard Control Plot(Standard: BLANK)

Ag ppm Expected Value = 1.50 EV Range (1.35 to 1.65) Mean of Ag ppm = 0.39

-4

-3

-2

-1

0

1

2S

00

331

S00

348

S00

349

S00

380

S00

381

S00

383

Cum

ula

tive S

um

of

Ag

pp

m -

Me

an

(g

/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: BLANK)

Ag ppm Mean of Cumulative Sum of Ag ppm - Mean (g/t) = -0.33

-70

-60

-50

-40

-30

-20

-10

0

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cum

ula

tive S

um

of

Ag

pp

m -

Exp

ecte

d V

alu

e (

g/t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: BLANK)

Ag ppm Mean of Cumulative Sum of Ag ppm - Expected Value (g/t) = -35.88

QA/QC Plot; Blank As

QA/QC Plot; Blank Cu

Standard: BLANK No of Analyses: 63Element: As Minimum: 0.50Units: Maximum: 84.00Detection Limit: Mean: 15.62Expected Value (EV): 3.00 Std Deviation: 12.12E.V. Range: 2.70 to 3.30 % in Tolerance 0.00 %

% Bias 420.63 %% RSD 77.61 %

0

20

40

60

80

100

S00

331

S00

348

S00

349

S00

380

S00

381

S00

383

As p

pm

(g

/t)

Lab Batch No

Standard Control Plot(Standard: BLANK)

As ppm Expected Value = 3.00 EV Range (2.70 to 3.30) Mean of As ppm = 15.62

-250

-200

-150

-100

-50

0

S00

33

1

S00

34

8

S00

34

9

S00

38

0

S00

38

1

S00

38

3

Cum

ula

tive S

um

of

As p

pm

- M

ean

(g

/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: BLANK)

As ppm Mean of Cumulative Sum of As ppm - Mean (g/t) = -114.42

-200

0

200

400

600

800

S0

033

1

S0

034

8

S0

034

9

S0

038

0

S0

038

1

S0

038

3

Cum

ula

tive S

um

of

As p

pm

- E

xp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: BLANK)

As ppm Mean of Cumulative Sum of As ppm - Expected Value (g/t) = 289.39

Standard: BLANK No of Analyses: 63Element: Cu Minimum: 10.00Units: Maximum: 178.00Detection Limit: Mean: 43.49Expected Value (EV): 6.00 Std Deviation: 35.30E.V. Range: 5.40 to 6.60 % in Tolerance 0.00 %

% Bias 624.87 %% RSD 81.16 %

0

50

100

150

200

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

pp

m (

g/

t)

Lab Batch No

Standard Control Plot(Standard: BLANK)

Cu ppm Expected Value = 6.00 EV Range (5.40 to 6.60) Mean of Cu ppm = 43.49

-600

-500

-400

-300

-200

-100

0S

00

33

1

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cum

ula

tiv

e S

um

of

Cu

pp

m -

Mean

(g

/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: BLANK)

Cu ppm Mean of Cumulative Sum of Cu ppm - Mean (g/t) = -321.87

0

500

1000

1500

2000

2500

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mu

lati

ve S

um

of

Cu p

pm

- E

xp

ecte

d V

alu

e (

g/

t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: BLANK)

Cu ppm Mean of Cumulative Sum of Cu ppm - Expected Value (g/t) = 877.87

QA/QC Plot; Blank Pb

QA/QC Plot; Blank Zn

Standard: BLANK No of Analyses: 63Element: Pb Minimum: 0.50Units: Maximum: 344.00Detection Limit: Mean: 77.75Expected Value (EV): 3.00 Std Deviation: 66.18E.V. Range: 2.70 to 3.30 % in Tolerance 0.00 %

% Bias 2,491.80 %% RSD 85.12 %

0

100

200

300

400

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Pb p

pm

(g/

t)

Lab Batch No

Standard Control Plot(Standard: BLANK)

Pb ppm Expected Value = 3.00 EV Range (2.70 to 3.30) Mean of Pb ppm = 77.75

-1000

-800

-600

-400

-200

0

200

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cu

mula

tiv

e S

um

of

Pb

ppm

- M

ea

n (

g/t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: BLANK)

Pb ppm Mean of Cumulative Sum of Pb ppm - Mean (g/t) = -526.17

0

1000

2000

3000

4000

5000

S0

03

31

S0

03

48

S0

03

49

S0

03

80

S0

03

81

S0

03

83

Cum

ula

tiv

e S

um

of

Pb p

pm

- E

xp

ect

ed V

alu

e (

g/t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: BLANK)

Pb ppm Mean of Cumulative Sum of Pb ppm - Expected Value (g/t) = 1,865.96

Standard: BLANK No of Analyses: 63Element: Zn Minimum: 1.00Units: Maximum: 398.00Detection Limit: Mean: 78.62Expected Value (EV): 6.00 Std Deviation: 86.82E.V. Range: 5.40 to 6.60 % in Tolerance 0.00 %

% Bias 1,210.32 %% RSD 110.43 %

0

100

200

300

400

S0

033

1

S0

034

8

S0

034

9

S0

038

0

S0

038

1

S0

038

3

Zn p

pm

(g/

t)

Lab Batch No

Standard Control Plot(Standard: BLANK)

Zn ppm Expected Value = 6.00 EV Range (5.40 to 6.60) Mean of Zn ppm = 78.62

-1400

-1200

-1000

-800

-600

-400

-200

0S00

331

S00

348

S00

349

S00

380

S00

381

S00

383

Cum

ula

tive S

um

of

Zn p

pm

- M

ean

(g/

t)

Lab Batch No

Cumulative Deviation from Assay Mean(Standard: BLANK)

Zn ppm Mean of Cumulative Sum of Zn ppm - Mean (g/t) = -738.32

0

1000

2000

3000

4000

5000

S00

331

S00

348

S00

349

S00

380

S00

381

S00

383

Cum

ula

tive S

um

of

Zn p

pm

- E

xpecte

d V

alu

e (

g/t)

Lab Batch No

Cumulative Deviation from Expected Value(Standard: BLANK)

Zn ppm Mean of Cumulative Sum of Zn ppm - Expected Value (g/t) = 1,585.49

QA/QC Plot; Field Duplicates Ag>5ppm

QA/QC Plot; Field Duplicates As>10ppm

Ag ppm R Ag ppm Units ResultNo. Pairs: 55 55 Pearson CC: 0.79Minimum: 5.50 4.50 g/t Spearman CC: 0.94Maximum: 41.50 140.00 g/t Mean HARD: 5.10Mean: 13.35 15.39 g/t Median HARD: 2.56Median 11.00 11.00 g/tStd. Deviation: 6.64 17.89 g/t Mean HRD: -1.39Coefficient of Variation: 0.50 1.16 Median HRD 0.00

0

20

40

60

1 10 100

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Ag>5ppm)

Mean HARD: 5.10 Median HARD: 2.56Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)

Rank (%)

Rank HARD Plot(Ag>5ppm)

Precision: 10%

90.91% of data are withinPrecision limits

0

20

40

60

-1.0 0.0 1.0

Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(Ag>5ppm)

Mean HRD: -1.39 Median HRD: 0.00Precision: +/-10%

-100

-50

0

50

1 10 100

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Ag>5ppm)

Mean HRD: -1.39 Median HRD: 0.00Precision: +/-10%

0.1

1

10

100

1 10 100

Ab

solu

te D

iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Ag>5ppm)

10% 20% 30% 50%

0.1

1

10

1 10 100

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Ag>5ppm)

10% 20% 30% 50%

-50

0

50

100

150

0 20 40 60 80 100 120 140

R A

g p

pm

(g/t)

Ag ppm (g/t)

Correlation Plot(Ag>5ppm)

P.CC= 0.79 S.CC= 0.94 Ref. Liney = 2.14x -13.15

-50

0

50

100

150

0 20 40 60 80 100 120 140

R A

g p

pm

(g/t)

Ag ppm (g/t)

QQ Plot(Ag>5ppm)

Ref. Line y = 2.17x -13.55

As ppm RAs ppm Units ResultNo. Pairs: 57 57 Pearson CC: 0.97Minimum: 79.00 80.00 g/t Spearman CC: 0.98Maximum: 5,350.00 5,570.00 g/t Mean HARD: 4.51Mean: 1,972.32 1,992.54 g/t Median HARD: 1.92Median 1,960.00 1,980.00 g/tStd. Deviation: 1,059.44 1,028.09 g/t Mean HRD: -1.12Coefficient of Variation: 0.54 0.52 Median HRD -0.76

0

20

40

60

80

1 10 100 1000 10000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(As >10ppm)

Mean HARD: 4.51 Median HARD: 1.92Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)

Rank (%)

Rank HARD Plot(As >10ppm)

Precision: 10%

91.23% of data are withinPrecision limits

0

20

40

60

80

-1.0 0.0 1.0

Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(As >10ppm)

Mean HRD: -1.12 Median HRD: -0.76Precision: +/-10%

-100

-50

0

50

1 10 100 1000 10000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(As >10ppm)

Mean HRD: -1.12 Median HRD: -0.76Precision: +/-10%

1

10

100

1000

10000

10 100 1000 10000

Ab

solu

te D

iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(As >10ppm)

10% 20% 30% 50%

10

100

1000

10000

100 1000 10000

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(As >10ppm)

10% 20% 30% 50%

0

2000

4000

6000

0 1000 2000 3000 4000 5000 6000

RA

s ppm

(g/t)

As ppm (g/t)

Correlation Plot(As >10ppm)

P.CC= 0.97 S.CC= 0.98 Ref. Liney = 0.94x + 140.68

0

2000

4000

6000

0 1000 2000 3000 4000 5000 6000

RA

s ppm

(g/t)

As ppm (g/t)

QQ Plot(As >10ppm)

Ref. Line y = 0.96x + 99.40

QA/QC Plot; Field Duplicates Cu>20ppm

QA/QC Plot; Field Duplicates Pb>10ppm

Cu ppm R Cu ppm Units ResultNo. Pairs: 57 57 Pearson CC: 0.87Minimum: 966.00 990.00 g/t Spearman CC: 0.86Maximum: 13,900.00 11,600.00 g/t Mean HARD: 4.13Mean: 5,043.09 5,023.16 g/t Median HARD: 1.59Median 4,680.00 4,750.00 g/tStd. Deviation: 2,024.69 1,816.24 g/t Mean HRD: -0.04Coefficient of Variation: 0.40 0.36 Median HRD 0.33

0

20

40

60

1 10 100 1000 10000 100000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Cu > 20ppm)

Mean HARD: 4.13 Median HARD: 1.59Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)Rank (%)

Rank HARD Plot(Cu > 20ppm)

Precision: 10%

92.98% of data are withinPrecision limits

0

20

40

60

80

-1.0 0.0 1.0

Fre

qu

en

cy (

%)

HRD (/100)

HRD Histogram(Cu > 20ppm)

Mean HRD: -0.04 Median HRD: 0.33Precision: +/-10%

-100

-50

0

50

1 10 100 1000 10000 100000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Cu > 20ppm)

Mean HRD: -0.04 Median HRD: 0.33Precision: +/-10%

10

100

1000

10000

100 1000 10000 100000

Ab

solu

te D

iffe

ren

ce (

g/

t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Cu > 20ppm)

10% 20% 30% 50%

10

100

1000

10000

1000 10000

Me

dia

n A

D (

g/

t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Cu > 20ppm)

10% 20% 30% 50%

0

5000

10000

15000

0 5000 10000 15000

R C

u p

pm

(g

/t)

Cu ppm (g/t)

Correlation Plot(Cu > 20ppm)

P.CC= 0.87 S.CC= 0.86 Ref. Liney = 0.78x + 1,101.12

0

5000

10000

15000

0 5000 10000 15000

R C

u p

pm

(g

/t)

Cu ppm (g/t)

QQ Plot(Cu > 20ppm)

Ref. Line y = 0.89x + 548.02

Pb ppm R Pb ppm Units ResultNo. Pairs: 57 57 Pearson CC: 0.96Minimum: 842.00 823.00 g/t Spearman CC: 0.88Maximum: 34,400.00 33,400.00 g/t Mean HARD: 3.76Mean: 9,358.46 9,566.89 g/t Median HARD: 1.16Median 8,490.00 8,430.00 g/tStd. Deviation: 5,279.91 5,328.87 g/t Mean HRD: -0.93Coefficient of Variation: 0.56 0.56 Median HRD 0.07

0

20

40

60

1 10 100 1000 10000 100000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Pb > 10ppm)

Mean HARD: 3.76 Median HARD: 1.16Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)

Rank (%)

Rank HARD Plot(Pb > 10ppm)

Precision: 10%

91.23% of data are withinPrecision limits

0

20

40

60

80

-1.0 0.0 1.0

Fre

qu

en

cy (

%)

HRD (/100)

HRD Histogram(Pb > 10ppm)

Mean HRD: -0.93 Median HRD: 0.07Precision: +/-10%

-100

-50

0

50

1 10 100 1000 10000 100000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Pb > 10ppm)

Mean HRD: -0.93 Median HRD: 0.07Precision: +/-10%

10

100

1000

10000

100000

100 1000 10000 100000

Ab

solu

te D

iffe

ren

ce (

g/

t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Pb > 10ppm)

10% 20% 30% 50%

100

1000

10000

1000 10000 100000

Me

dia

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Pb > 10ppm)

10% 20% 30% 50%

0

10000

20000

30000

40000

0 10000 20000 30000 40000

R P

b p

pm

(g

/t)

Pb ppm (g/t)

Correlation Plot(Pb > 10ppm)

P.CC= 0.96 S.CC= 0.88 Ref. Liney = 0.97x + 498.39

0

10000

20000

30000

40000

0 10000 20000 30000 40000

R P

b p

pm

(g

/t)

Pb ppm (g/t)

QQ Plot(Pb > 10ppm)

Ref. Line y = 1.01x + 160.39

QA/QC Plot; Field Duplicates Zn>20ppm

QA/QC Plot; Referee Analysis Bureau Veritas vs ALS Chemex Ag

Zn ppm R Zn ppm Units ResultNo. Pairs: 57 57 Pearson CC: 0.86Minimum: 418.00 470.00 g/t Spearman CC: 0.88Maximum: 30,200.00 22,400.00 g/t Mean HARD: 4.08Mean: 6,695.40 6,923.40 g/t Median HARD: 1.38Median 5,800.00 5,900.00 g/tStd. Deviation: 4,576.01 4,466.08 g/t Mean HRD: -1.36Coefficient of Variation: 0.68 0.65 Median HRD -0.34

0

20

40

60

80

1 10 100 1000 10000 100000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Zn > 20ppm)

Mean HARD: 4.08 Median HARD: 1.38Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)Rank (%)

Rank HARD Plot(Zn > 20ppm)

Precision: 10%

89.47% of data are withinPrecision limits

0

20

40

60

80

-1.0 0.0 1.0

Fre

qu

en

cy (

%)

HRD (/100)

HRD Histogram(Zn > 20ppm)

Mean HRD: -1.36 Median HRD: -0.34Precision: +/-10%

-100

-50

0

50

1 10 100 1000 10000 100000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Zn > 20ppm)

Mean HRD: -1.36 Median HRD: -0.34Precision: +/-10%

10

100

1000

10000

100000

100 1000 10000 100000

Ab

solu

te D

iffe

ren

ce (

g/

t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Zn > 20ppm)

10% 20% 30% 50%

10

100

1000

10000

1000 10000

Me

dia

n A

D (

g/

t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Zn > 20ppm)

10% 20% 30% 50%

0

10000

20000

30000

40000

0 10000 20000 30000 40000

R Z

n p

pm

(g

/t)

Zn ppm (g/t)

Correlation Plot(Zn > 20ppm)

P.CC= 0.86 S.CC= 0.88 Ref. Liney = 0.83x + 1,335.65

0

10000

20000

30000

40000

0 10000 20000 30000 40000

R Z

n p

pm

(g

/t)

Zn ppm (g/t)

QQ Plot(Zn > 20ppm)

Ref. Line y = 0.92x + 761.40

Ag ppm R Ag Units ResultNo. Pairs: 65 65 Pearson CC: 0.96Minimum: 1.00 0.74 g/t Spearman CC: 0.97Maximum: 41.50 60.40 g/t Mean HARD: 5.09Mean: 14.52 14.96 g/t Median HARD: 3.78Median 12.50 12.20 g/tStd. Deviation: 8.28 9.77 g/t Mean HRD: -0.58Coefficient of Variation: 0.57 0.65 Median HRD -0.67

0

10

20

30

0.1 1 10 100

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Ag >0.5)

Mean HARD: 5.09 Median HARD: 3.78Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)

Rank (%)

Rank HARD Plot(Ag >0.5)

Precision: 10%

90.77% of data are withinPrecision limits

0

10

20

30

40

-1.0 0.0 1.0

Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(Ag >0.5)

Mean HRD: -0.58 Median HRD: -0.67Precision: +/-10%

-40

-20

0

20

40

0.1 1 10 100

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Ag >0.5)

Mean HRD: -0.58 Median HRD: -0.67Precision: +/-10%

0.01

0.1

1

10

100

0.1 1 10 100

Ab

solu

te D

iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Ag >0.5)

10% 20% 30% 50%

0.1

1

10

1 10 100

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Ag >0.5)

10% 20% 30% 50%

-50

0

50

100

0 10 20 30 40 50 60 70 80 90 100

R A

g (

g/t)

Ag ppm (g/t)

Correlation Plot(Ag >0.5)

P.CC= 0.96 S.CC= 0.97 Ref. Liney = 1.13x -1.53

-20

0

20

40

60

80

0 10 20 30 40 50 60 70 80

R A

g (

g/t)

Ag ppm (g/t)

QQ Plot(Ag >0.5)

Ref. Line y = 1.15x -1.78

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex As

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Bi

As ppm R As Units ResultNo. Pairs: 65 65 Pearson CC: 0.98Minimum: 20.00 22.90 g/t Spearman CC: 0.97Maximum: 7,160.00 8,520.00 g/t Mean HARD: 6.39Mean: 1,886.77 2,100.47 g/t Median HARD: 5.11Median 1,960.00 2,250.00 g/tStd. Deviation: 1,318.20 1,492.55 g/t Mean HRD: -4.73Coefficient of Variation: 0.70 0.71 Median HRD -4.63

0

10

20

30

1 10 100 1000 10000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(As>1)

Mean HARD: 6.39 Median HARD: 5.11Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)Rank (%)

Rank HARD Plot(As>1)

Precision: 10%

75.38% of data are withinPrecision limits

0

10

20

30

40

-1.0 0.0 1.0

Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(As>1)

Mean HRD: -4.73 Median HRD: -4.63Precision: +/-10%

-20

0

20

40

1 10 100 1000 10000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(As>1)

Mean HRD: -4.73 Median HRD: -4.63Precision: +/-10%

1

10

100

1000

10000

10 100 1000 10000

Abso

lute

Diffe

rence

(g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(As>1)

10% 20% 30% 50%

1

10

100

1000

10000

100 1000 10000

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(As>1)

10% 20% 30% 50%

0

5000

10000

0 2000 4000 6000 8000 10000

R A

s (

g/t)

As ppm (g/t)

Correlation Plot(As>1)

P.CC= 0.98 S.CC= 0.97 Ref. Liney = 1.11x + 2.89

-5000

0

5000

10000

0 2000 4000 6000 8000 10000

R A

s (

g/t)

As ppm (g/t)

QQ Plot(As>1)

Ref. Line y = 1.13x -26.36

Bi ppm R Bi Units ResultNo. Pairs: 42 42 Pearson CC: 1.00Minimum: 0.10 0.10 g/t Spearman CC: 0.97Maximum: 5.70 5.51 g/t Mean HARD: 16.26Mean: 1.03 0.94 g/t Median HARD: 15.32Median 0.30 0.18 g/tStd. Deviation: 1.71 1.69 g/t Mean HRD: 15.09Coefficient of Variation: 1.65 1.80 Median HRD 15.32

0

20

40

60

0.1 1 10

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Bi>0.1)

Mean HARD: 16.26 Median HARD: 15.32Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)

Rank (%)

Rank HARD Plot(Bi>0.1)

Precision: 10%

40.48% of data are withinPrecision limits

0

5

10

15

20

-1.0 0.0 1.0

Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(Bi>0.1)

Mean HRD: 15.09 Median HRD: 15.32Precision: +/-10%

-20

0

20

40

60

0.1 1 10

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Bi>0.1)

Mean HRD: 15.09 Median HRD: 15.32Precision: +/-10%

0.01

0.1

1

10

0.1 1 10

Abso

lute

Dif

fere

nce

(g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Bi>0.1)

10% 20% 30% 50%

0.01

0.1

1

0.1 1 10

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Bi>0.1)

10% 20% 30% 50%

0

2

4

6

0 1 2 3 4 5 6

R B

i (g

/t)

Bi ppm (g/t)

Correlation Plot(Bi>0.1)

P.CC= 1.00 S.CC= 0.97 Ref. Liney = 0.99x -0.08

0

2

4

6

0 1 2 3 4 5 6

R B

i (g

/t)

Bi ppm (g/t)

QQ Plot(Bi>0.1)

Ref. Line y = 0.99x -0.08

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Cd

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Cu

Cd ppm R Cd Units ResultNo. Pairs: 65 65 Pearson CC: 0.99Minimum: 6.00 6.71 g/t Spearman CC: 0.94Maximum: 699.00 708.00 g/t Mean HARD: 4.30Mean: 165.88 165.83 g/t Median HARD: 3.60Median 140.00 139.00 g/tStd. Deviation: 102.66 102.19 g/t Mean HRD: -0.07Coefficient of Variation: 0.62 0.62 Median HRD -0.43

0

10

20

30

1 10 100 1000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Cd>0.5)

Mean HARD: 4.30 Median HARD: 3.60Precision: 10%

0

20

40

60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)Rank (%)

Rank HARD Plot(Cd>0.5)

Precision: 10%

93.85% of data are withinPrecision limits

0

10

20

30

40

-1.0 0.0 1.0

Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(Cd>0.5)

Mean HRD: -0.07 Median HRD: -0.43Precision: +/-10%

-20

0

20

40

1 10 100 1000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Cd>0.5)

Mean HRD: -0.07 Median HRD: -0.43Precision: +/-10%

0.1

1

10

100

1000

1 10 100 1000

Ab

solu

te D

iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Cd>0.5)

10% 20% 30% 50%

1

10

100

10 100 1000

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Cd>0.5)

10% 20% 30% 50%

0

200

400

600

800

0 100 200 300 400 500 600 700 800

R C

d (

g/t)

Cd ppm (g/t)

Correlation Plot(Cd>0.5)

P.CC= 0.99 S.CC= 0.94 Ref. Liney = 0.98x + 2.91

0

200

400

600

800

0 100 200 300 400 500 600 700 800

R C

d (

g/t)

Cd ppm (g/t)

QQ Plot(Cd>0.5)

Ref. Line y = 0.99x + 1.34

Cu ppm R Cu Units ResultNo. Pairs: 65 65 Pearson CC: 0.98Minimum: 364.00 220.00 g/t Spearman CC: 0.97Maximum: 13,900.00 15,800.00 g/t Mean HARD: 3.64Mean: 4,874.65 5,026.00 g/t Median HARD: 2.15Median 4,340.00 4,590.00 g/tStd. Deviation: 2,572.18 2,752.97 g/t Mean HRD: -0.74Coefficient of Variation: 0.53 0.55 Median HRD -1.28

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30

1 10 100 1000 10000 100000

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Cu>10)

Mean HARD: 3.64 Median HARD: 2.15Precision: 10%

0

20

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60

80

100

0 10 20 30 40 50 60 70 80 90 100

HA

RD

(%

)

Rank (%)

Rank HARD Plot(Cu>10)

Precision: 10%

95.38% of data are withinPrecision limits

0

20

40

60

-1.0 0.0 1.0

Fre

qu

en

cy (

%)

HRD (/100)

HRD Histogram(Cu>10)

Mean HRD: -0.74 Median HRD: -1.28Precision: +/-10%

-20

0

20

40

1 10 100 1000 10000 100000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Cu>10)

Mean HRD: -0.74 Median HRD: -1.28Precision: +/-10%

1

10

100

1000

10000

100 1000 10000 100000

Ab

solu

te D

iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Cu>10)

10% 20% 30% 50%

10

100

1000

10000

1000 10000

Me

dia

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Cu>10)

10% 20% 30% 50%

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15000

20000

0 5000 10000 15000 20000

R C

u (

g/t)

Cu ppm (g/t)

Correlation Plot(Cu>10)

P.CC= 0.98 S.CC= 0.97 Ref. Liney = 1.05x -112.91

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20000

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R C

u (

g/t)

Cu ppm (g/t)

QQ Plot(Cu>10)

Ref. Line y = 1.07x -166.54

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Cu LEACH

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Ga

Cu_LEAppm R Cu-LEA Units Result

No. Pairs: 57 57 Pearson CC: 0.93Minimum: 30.00 10.00 g/t Spearman CC: 0.90Maximum: 10,800.00 10,450.00 g/t Mean HARD: 8.61Mean: 3,828.42 3,572.46 g/t Median HARD: 5.74Median 3,330.00 2,930.00 g/tStd. Deviation: 2,348.73 2,185.66 g/t Mean HRD: 4.20Coefficient of Variation: 0.61 0.61 Median HRD 5.19

0

50

100

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HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Cu_LEA>10)

Mean HARD: 8.61 Median HARD: 5.74Precision: 10%

02040

6080

100

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HA

RD

(%

)Rank (%)

Rank HARD Plot(Cu_LEA>10)

Precision: 10%

77.19% of data are withinPrecision limits

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60

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Fre

qu

en

cy (

%)

HRD (/100)

HRD Histogram(Cu_LEA>10)

Mean HRD: 4.20 Median HRD: 5.19Precision: +/-10%

-100

-50

0

50

1 10 100 1000 10000 100000

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Cu_LEA>10)

Mean HRD: 4.20 Median HRD: 5.19Precision: +/-10%

1

10

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1000

10000

10 100 1000 10000 100000

Ab

solu

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iffe

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ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Cu_LEA>10)

10% 20% 30% 50%

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100

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1000 10000

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Cu_LEA>10)

10% 20% 30% 50%

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15000

0 5000 10000 15000

R C

u-L

EA

(g

/t)

Cu_LEA ppm (g/t)

Correlation Plot(Cu_LEA>10)

P.CC= 0.93 S.CC= 0.90 Ref. Liney = 0.87x + 259.28

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R C

u-L

EA

(g

/t)

Cu_LEA ppm (g/t)

QQ Plot(Cu_LEA>10)

Ref. Line y = 0.92x + 32.99

Ga ppm R Ga Units ResultNo. Pairs: 65 65 Pearson CC: 0.97Minimum: 5.40 6.01 g/t Spearman CC: 0.95Maximum: 59.60 55.40 g/t Mean HARD: 3.81Mean: 29.48 30.28 g/t Median HARD: 2.70Median 31.60 31.80 g/tStd. Deviation: 13.33 13.34 g/t Mean HRD: -1.27Coefficient of Variation: 0.45 0.44 Median HRD -1.50

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20

1 10 100

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Ga>0.2)

Mean HARD: 3.81 Median HARD: 2.70Precision: 10%

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60

80

100

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HA

RD

(%

)

Rank (%)

Rank HARD Plot(Ga>0.2)

Precision: 10%

95.38% of data are withinPrecision limits

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60

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Fre

qu

en

cy (

%)

HRD (/100)

HRD Histogram(Ga>0.2)

Mean HRD: -1.27 Median HRD: -1.50Precision: +/-10%

-20

-10

0

10

20

1 10 100

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Ga>0.2)

Mean HRD: -1.27 Median HRD: -1.50Precision: +/-10%

0.01

0.1

1

10

100

1 10 100

Ab

solu

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iffe

ren

ce (

g/

t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Ga>0.2)

10% 20% 30% 50%

0.1

1

10

100

1 10 100

Me

dia

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Ga>0.2)

10% 20% 30% 50%

0

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40

60

0 10 20 30 40 50 60

R G

a (

g/

t)

Ga ppm (g/t)

Correlation Plot(Ga>0.2)

P.CC= 0.97 S.CC= 0.95 Ref. Liney = 0.97x + 1.63

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60

80

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R G

a (

g/

t)

Ga ppm (g/t)

QQ Plot(Ga>0.2)

Ref. Line y = 0.99x + 1.06

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex In

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Pb

In ppm R In Units ResultNo. Pairs: 65 65 Pearson CC: 1.00Minimum: 0.04 0.02 g/t Spearman CC: 0.96Maximum: 6.24 6.41 g/t Mean HARD: 5.94Mean: 0.83 0.89 g/t Median HARD: 5.17Median 0.44 0.46 g/tStd. Deviation: 1.39 1.49 g/t Mean HRD: -3.25Coefficient of Variation: 1.69 1.68 Median HRD -3.78

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30

0.01 0.1 1 10

HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(In>0.02)

Mean HARD: 5.94 Median HARD: 5.17Precision: 10%

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80

100

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HA

RD

(%

)Rank (%)

Rank HARD Plot(In>0.02)

Precision: 10%

83.08% of data are withinPrecision limits

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40

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Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(In>0.02)

Mean HRD: -3.25 Median HRD: -3.78Precision: +/-10%

-40

-20

0

20

40

0.01 0.1 1 10

HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(In>0.02)

Mean HRD: -3.25 Median HRD: -3.78Precision: +/-10%

0.001

0.01

0.1

1

10

0.01 0.1 1 10

Ab

solu

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iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(In>0.02)

10% 20% 30% 50%

0.01

0.1

1

0.1 1 10

Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(In>0.02)

10% 20% 30% 50%

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6

8

0 1 2 3 4 5 6 7 8

R I

n (

g/t)

In ppm (g/t)

Correlation Plot(In>0.02)

P.CC= 1.00 S.CC= 0.96 Ref. Liney = 1.07x + 0.01

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R I

n (

g/t)

In ppm (g/t)

QQ Plot(In>0.02)

Ref. Line y = 1.07x + 0.01

Pb ppm R Pb Units ResultNo. Pairs: 65 65 Pearson CC: 0.99Minimum: 465.00 477.00 g/t Spearman CC: 0.98Maximum: 34,400.00 38,600.00 g/t Mean HARD: 3.38Mean: 9,326.54 9,865.11 g/t Median HARD: 2.70Median 8,980.00 9,340.00 g/tStd. Deviation: 4,846.74 5,361.29 g/t Mean HRD: -2.41Coefficient of Variation: 0.52 0.54 Median HRD -2.29

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HA

RD

(%

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Mean of Data Pair (g/t)

Mean vs. HARD Plot(Pb>1)

Mean HARD: 3.38 Median HARD: 2.70Precision: 10%

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HA

RD

(%

)

Rank (%)

Rank HARD Plot(Pb>1)

Precision: 10%

98.46% of data are withinPrecision limits

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Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(Pb>1)

Mean HRD: -2.41 Median HRD: -2.29Precision: +/-10%

-10

0

10

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HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Pb>1)

Mean HRD: -2.41 Median HRD: -2.29Precision: +/-10%

10

100

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Abso

lute

Diffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Pb>1)

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Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Pb>1)

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R P

b (

g/t)

Pb ppm (g/t)

Correlation Plot(Pb>1)

P.CC= 0.99 S.CC= 0.98 Ref. Liney = 1.10x -349.48

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R P

b (

g/t)

Pb ppm (g/t)

QQ Plot(Pb>1)

Ref. Line y = 1.10x -431.18

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex S

QA/QC Plot; Analysis Bureau Veritas vs ALS Chemex Zn

S ppm R S Units ResultNo. Pairs: 65 65 Pearson CC: 1.00Minimum: 350.00 300.00 g/t Spearman CC: 0.98Maximum: 103,000.00 104,000.00 g/t Mean HARD: 5.22Mean: 10,297.69 10,580.00 g/t Median HARD: 3.70Median 2,500.00 2,500.00 g/tStd. Deviation: 25,192.64 26,100.87 g/t Mean HRD: -0.92Coefficient of Variation: 2.45 2.47 Median HRD -1.82

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HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(S>100)

Mean HARD: 5.22 Median HARD: 3.70Precision: 10%

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HA

RD

(%

)Rank (%)

Rank HARD Plot(S>100)

Precision: 10%

86.15% of data are withinPrecision limits

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Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(S>100)

Mean HRD: -0.92 Median HRD: -1.82Precision: +/-10%

-20

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20

40

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HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(S>100)

Mean HRD: -0.92 Median HRD: -1.82Precision: +/-10%

10

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solu

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iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(S>100)

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Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(S>100)

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R S

(g/t)

S ppm (g/t)

Correlation Plot(S>100)

P.CC= 1.00 S.CC= 0.98 Ref. Liney = 1.03x -47.87

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R S

(g/t)

S ppm (g/t)

QQ Plot(S>100)

Ref. Line y = 1.04x -82.89

Zn ppm R Zn Units ResultNo. Pairs: 65 65 Pearson CC: 1.00Minimum: 316.00 290.00 g/t Spearman CC: 0.96Maximum: 168,000.00 157,500.00 g/t Mean HARD: 5.98Mean: 18,095.54 18,606.15 g/t Median HARD: 5.62Median 6,520.00 7,120.00 g/tStd. Deviation: 39,423.44 39,239.88 g/t Mean HRD: -3.84Coefficient of Variation: 2.18 2.11 Median HRD -4.95

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HA

RD

(%

)

Mean of Data Pair (g/t)

Mean vs. HARD Plot(Zn>10)

Mean HARD: 5.98 Median HARD: 5.62Precision: 10%

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HA

RD

(%

)

Rank (%)

Rank HARD Plot(Zn>10)

Precision: 10%

90.77% of data are withinPrecision limits

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Fre

quen

cy (

%)

HRD (/100)

HRD Histogram(Zn>10)

Mean HRD: -3.84 Median HRD: -4.95Precision: +/-10%

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HR

D (

%)

Mean of Data Pair (g/t)

Mean vs. HRD Plot(Zn>10)

Mean HRD: -3.84 Median HRD: -4.95Precision: +/-10%

10

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Ab

solu

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iffe

ren

ce (

g/t)

Mean of Data Pair (g/t)

T & H Precision Plot (Assay Pairs)(Zn>10)

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Media

n A

D (

g/t)

Grouped Mean of Pair (g/t)

T & H Precision Plot (Grouped Pairs)(Zn>10)

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R Z

n (

g/t)

Zn ppm (g/t)

Correlation Plot(Zn>10)

P.CC= 1.00 S.CC= 0.96 Ref. Liney = 0.99x + 663.24

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R Z

n (

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Zn ppm (g/t)

QQ Plot(Zn>10)

Ref. Line y = 0.99x + 611.80