TECHNICAL REPORT ON THE
NORRLIDEN RESOURCE ESTIMATION,
SWEDEN

By

Adam Wheeler, C.Eng., Eur.Ing.
Consulting Mining Engineer

May 2006

Adam Wheeler,
Mining Consultant,
Cambrose Farm,
Redruth,
Cornwall, TR16 4HT,
England.
Tel/Fax: (44) 1209-890733
E-mail : adamwheeler@btinternet.com

Ref: NORR/AJW/NO03

Adam Wheeler Norrliden Resource Estimation

TABLE OF CONTENTS

			Page
1 SUMMARY			1
	1.1	Introduction and Overview	1
	1.2	Database and Resource Estimation	1
	1.3	Conclusions and Recommendations	2
2 INTRODUCTION			3
	2.1	Introduction	3
	2.2	Terms of Reference	3
	2.3	Sources of Information	3
	2.4	Units and Currency	4
	2.5	Disclaimer	4
3 PROPERTY DESCRIPTION AND LOCATION			4
4 ACCESSIBILITY, CLIMATE, LOCAL RESOURCES			7
5 HISTORY			8
6 GEOLOGICAL SETTING			8
	6.1	Regional Geology	8
	6.2	Local Geology	9
7	DEPOSIT TYPES		10
8	MINERALISATION		10
9	EXPLORATION		11
10 DRILLING			11
	10.1	Drillhole database	11
	10.2	Surveying	12
11 SAMPLING METHOD AND APPROACH			12
	11.1	Sampling Method	12
	11.2	Core logging and recovery	13
	11.3	Bulk Density	13
12 SAMPLE PREPARATION, ANALYSES AND SECURITY			14
13 DATA VERIFICATION			14
	13.1	Standards, Blanks and Duplicates	15
	13.2	Analyses by Independent Laboratories	15
	13.3	Independent Review	15
	13.4	Conclusion with respect to Data Verification	20
14 ADJACENT PROPERTIES			20
15 MINERAL PROCESSING AND METALLURGICAL TESTING			20
16 MINERAL RESOURCE ESTIMATE			22
	16.1	General	22
	16.2	Drillhole Data Processing and Interpretation	23
	16.3	Geostatistical Analysis	32
	16.4	Geological Modelling	34
	16.5	Validation	43
	16.6	Evaluation	45
17 OTHER RELEVANT DATA AND INFORMATION			51
18 CONCLUSIONS AND RECOMMENDATIONS			52
	18.1	Conclusions	52
	18.2	Recommendations	53
19 REFERENCES			53
20 DATE AND SIGNATURE PAGE			53

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LIST OF TABLES
Table 13-1. Summary Statistics For Duplicate Samples	16
Table 13-2. Summary Statistics For Resampling	18
Table 16-1 Derivation of NSR Parameters	27
Table 16-2 Drillhole Summary	28
Table 16-3. Samples' Statistical Summary	32
Table 16-4. Capping Levels	33
Table 16-5. Composites' Statistical Summary	33
Table 16-6. Model Prototype	34
Table 16-7. Interpolation Parameters	34
Table 16-8. Resource Classification Parameters	35
Table 16-9. Comparison of Average Grades	44
Table 16-10. Resource Evaluation- Base Case Parameters	46
Table 16-11. Resource Breakdown - By Elevation	47
Table 16-12. Resource Evaluation - Based On Alternative Economic (LOM) Scenario	48
Table 16-13. Grade-Tonnage Curve - Just Indicated Resources	49
Table 16-14. Grade-Tonnage Table - All Resources	50
LIST OF FIGURES
Figure 3-1. Location of Norrliden Within Sweden	5
Figure 3-2. Location Norrliden Within Local Area	6
Figure 3-3. Western Part of Skelleftea Mining District	6
Figure 16-1. Section Through West Part of Main Zones At X=-60m	25
Figure 16-2. Section Through East Part of Main Zones At X=+60m	26
Figure 16-3. West-East Long Section of Main Zones	29
Figure 16-4. Plan of Drillholes	30
Figure 16-5. 3D View of Main Zones - Viewed From South-East	31
Figure 16-6. 3D View of Main Zones - Viewed From South-West	31
Figure 16-7. Zn Variation, Model Section West, At X= -60m	36
Figure 16-8. Zn Variation, Model Section East, At X= +60m	37
Figure 16-9. Cu Variation, Model Section West, At X= -60m	38
Figure 16-10. Cu Variation, Model Section East, At X= +60m	39
Figure 16-11. NSR Variation, Model Section West, At X= -60m	40
Figure 16-12 NSR Variation, Model Section East At X= +60m	41
Figure 16-13 Extent of Indicated Resources - Long Section of Main Zones	42

APPENDICES

A     Statistical Plots
B     Decile Analyses
C     Model Sections
D     Twinned Hole Sections

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1 SUMMARY

1.1 Introduction and Overview

Adam Wheeler was retained by Lundin Mining (Lundin) to provide an independent technical report on the mineral resources for the Norrliden polymetallic massive sulphide deposit. These mineral resources were estimated by Adam Wheeler during March 2004, and this study was then subsequently updated in April, 2006, reflecting more recent price parameters. A site visit was undertaken by Adam Wheeler in May 2006.

The Norrliden Zn-Cu deposit is located in northern Sweden, approximately 80km west of Skellefteå,. It is also about 40 road km away from the Storliden Zn-Cu mine, and 50 km east of the town of Malå. No mining activity has taken place at this deposit.

The deposit is a volcanogenic massive sulphide (VMS) occurrence, and was discovered and drilled by the Swedish Geological Survey (SGU) in a period from 1958 to 1974. In 1999, North Atlantic Natural Resources (NAN) initiated a second drilling programme to establish the nature and full extent of the mineralisation. NAN today is a wholly owned subsidiary of Lundin Mining.

Norrliden is situated in the centre of the western end of the Skellefteå mining district and displays the classical characteristics of Skellefteå VMS deposits. The deposit is a massive sulphide orebody with associated stringer zone, hosted by tuffite, sediments and pyroclastics.

The mineralisation is characterised by sulphides occurring in numerous lenses which lie sub-parallel the volcanic stratigraphy in a strongly deformed quartz-sericite rich horizon. Ore mineralogy consists mainly of pyrite, fine-grained sphalerite and chalcopyrite with dispersed galena and minor arsenopyrite. Many samples contain gold values of economic interest.

1.2 Database and Resource Estimation

The Norrliden database used to compile this resource estimate consists of 2092 samples from 92 drillholes; consisting of 52 of the 66 drillholes completed by SGU (those with assay and collar/survey data) and a further 42 diamond drillholes completed by NAN.

The data density (spacing and distribution) is sufficient to establish appropriate levels of geological and grade continuity for the resource estimation techniques used and the resource classification system applied.

The orientation of sampling data relative to the geological structures appears to be appropriate and is not believed to be introducing any bias into the sampling. Similarly, there are no apparent reasons to consider that the available survey data is introducing any bias into the estimates produced. There are no concerns over core recovery that would impact on the resource estimate or classification.

Density (specific gravity) determinations on NAN samples were made by the dry immersion method, which is a widely used and appropriate method. Although unconfirmed, it is believed the same method was used for SGU samples and, overall, sufficient, representative density measurements exist to allow calculation of a bulk density factors.

Sample selection, splitting, preparation and assay were all carried out to industry standards and there are no concerns over sample security or probity.

Although a complete, systematic and thorough quality control programme has not been undertaken for the sample set at Norrliden, the data that is available has not highlighted any significant problems that would compromise the integrity of the database used in the resource estimation.

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There is, however, a level of uncertainty in the sample set that makes it inappropriate to use these samples to support measured resources, although sufficient confidence in the assay data does exist to support indicated resources.

Work completed during the original and updated resource estimation studies encompassed:

• Input and validation of drillhole sample data.
• Interpretation and geostatistical analysis of sample data.
• Generation of geological block model.
• Resource evaluation.

There are two distinct zones of mineralization, in the west and east ends of the deposit area. For each of these main zones, sections were interpreted based on a cut-off of SEK120/t. This interpretation was also strongly controlled by previous geological interpretations completed by NAN. The combined SEK value was calculated by consideration of the potential economic contribution of zinc, copper, lead, silver and gold.

Metal grades were interpolated into the block model, using parameters supported by a geostatistical analysis of drillhole composites. This also enabled the definition of pertinent resource classification criteria, relating to search distances, numbers of drillholes and composites, as well as the source of drilling data. Resources were classified according to the JORC code.

1.3 Conclusions and Recommendations

A summary of the resource evaluation is shown in the table below, based on a block cut-off of SEK120/t and a minimum mining width of 3m.

CLASS	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Indicated	568	4.9	0.4	0.8	0.9	59.7	452
Inferred	948	4.0	0.4	0.8	0.7	59.1	399

Notes   . Based on block cut-off of SEK120/t

. NSR calculated using long-term base case prices:

	Zn	Pb	Cu	Au	Ag
	c/lb	c/lb	c/lb	$/oz	$/oz
	/%	/%	/%	/g/t	/g/t
Prices	60	33	120	450	6.5
Coefficients	46.3	20.8	143.2	54.4	0.94

The following recommendations have been made:

• Further drilling would be required in the main zones to increase the proportion of indicated resources and to reinforce the interpretation of peripheral zones.
   
• Further drilling, to give a closer sample spacing, would be required in order to classify any of the deposit in a measured resource category. Corresponding quality control on the sampling and assaying procedures would need to be demonstrated at a higher standard.
   
• To allow a reserve estimate, a mine planning study would be required, together with a more detailed consideration of metallurgical and economic parameters.

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2 INTRODUCTION

2.1 Introduction

This report presents a resource assessment for the Norrliden copper-zinc project located in the Skelleftea mining district in North Western Sweden. Norrliden is owned by North Atlantic Natural Resources AB (NAN), a wholly owned subsidiary of Lundin Mining Corporation (Lundin), a company listed on the Stockholm and Toronto Stock Exchanges.

The resource assessment is related to operational development of Lundin's Storliden mine, whose processing facility (at Boilden) is located approximately 60 km from Norrliden.

2.2 Terms of Reference

This resource estimation study was commissioned by Lundin and completed by Adam Wheeler, an independent mining consultant, with assistance from Lundin geologists. The majority of the computational work utilised the Datamine mining software system.

Adam Wheeler was retained by Lundin to provide an independent technical report on the mineral resources at Norrliden, as of April 30, 2006.This technical report has been prepared for filing pursuant to National Instrument 43-101and provides information with respect to the exploration activities, resource estimations and technical studies and economic analyses which have been undertaken by Lundin and its consultants.

The Qualified Person responsible for the preparation of this report is Adam Wheeler (C.Eng, Eur.Ing) an independent mining consultant.

Adam Wheeler completed the majority of the geological modelling and resource estimation during the first quarter 2006 and undertook a site visit to Norrliden on May 22^nd, 2006. The work has been completed with assistance from Lundin technical personnel. The report was also reviewed internally by Paul Wheeler (BSc) an independent resource estimation geologist with 18 years' industry experience.

2.3 Sources of Information

In conducting this study, Adam Wheeler relied on reports and information prepared by and for Lundin.

The information on which this report is based includes:

• Descriptions of the regional and local geological setting.
   
• Drilling, sampling and assay data from diamond drill holes located on the property, together with details of data verification procedures.
   
• Reports prepared by NAN/Boliden and their consultants reviewing the sampling and assaying protocols, and geological interpretations developed, including a report on Assay Quality Control by Da Silva in November 1999.
   
• Previous reports prepared by Micon International Limited (Micon) and ACA Howe in January 2000; covering respectively the Norrliden Development Concept and a Resource Audit of Norra Norrliden.

Adam Wheeler is pleased to acknowledge the helpful cooperation of the management of Lundin, all of whom made any and all data requested available and responded openly and helpfully to questions and requests for material.

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2.4 Units and Currency

Metric units are used throughout this report unless noted otherwise. Currency is primarily United States dollars ("US$") and Swedish kronor or crowns ("SEK"). The currency exchange rate adopted for this study was 8.0 SEK per US$.

2.5 Disclaimer

Adam Wheeler has reviewed and analyzed data provided by Lundin and its consultants and has drawn his own conclusions therefrom. Adam Wheeler has not performed any independent exploration work, drilled any holes or carried out any sampling and assaying.

Adam Wheeler performed the current estimate of the resources at the Norrliden deposit, as of April 30, 2006. Adam Wheeler has also drawn upon previous reports prepared by Micon and ACA Howe (both 2000), as well on a report on quality control prepared by James DaSilva in 1999.

While exercising all reasonable diligence in checking and confirmation, Adam Wheeler has relied upon the data presented by Lundin, and previous reports on the property by Micon, ACA Howe and DaSilva, noted above, in formulating his opinions.

Title to the mineral lands for the Norrliden deposit has not been investigated or confirmed by Adam Wheeler and Adam Wheeler offers no opinion as to the validity of the exploration or mineral title claimed. A description of the property, and ownership thereof, is provided for general information purposes only

3 PROPERTY DESCRIPTION AND LOCATION

The Norrliden deposit is 90% owned by Lundin Mining through their subsidiary NAN and is being evaluated in association with the ongoing development and mining of the Storliden deposit, also controlled by Lundin.

International Gold Exploration AB (IGE) has a 10% interest in the project, subject to making an equivalent contribution to development costs. If IGE decline to fund their share of the project's development, then this interest reverts to a 1.5% Net Smelter Return(NSR) royalty, although the value of the royalty cannot exceed US$5 million.

The deposit lies in the central Skelleftea mining district and is situated 26km north of Norsjö, Våsterbotten county, Swedish Lappland; approximately 50km east of Malå. Swedish National Grid position is grid location 1 643 185 East and 7 239 750 North.The nearest settlement is at Ortråak, 1.5km to the south-east and the coastal towns of Skellefteå and Umeå are approximately 60km and 90km distant respectively.

The location of Norrliden with reference to Sweden is shown in Fig 3.1. The location of Norrliden with reference to the local area is shown in Fig 3.2. The other Lundin concessions are also shown in a plan of part of the Skelleftea mining district, in Fig 3.3.

Norrliden is situated on the exploration permit Malånäset nr 2. An application for a mining permit named Norrliden K nr 1 is currently being processed. The exploration permit will be valid until the mining permit is granted.

The mine and associated site infrastructure would be located on land currently owned either by the Swedish forestry company, Assi Doman AB or by private individuals. Lundin has not yet completed any agreements for the purchase or use of any of these lands.

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4 ACCESSIBILITY, CLIMATE, LOCAL RESOURCES, INFRASTRUCTURE, PHYSIOGRAPHY

The accessibility, climate, local resources, infrastructure and physiography descriptions in this report are taken from the Micon, 2002 report and various internal NAN reports, with the permission of the Lundin Mining Corporation.

The deposit itself is accessible to Adam Wheeler and a site visit was undertaken on May 22^nd, 2006.

The deposit is located approximately 50km east of Malå and about 40 road km from Storliden. It is also approximately 60km from the existing processing plant in Boliden. Malå is located 100km inland from Skellefteå, the nearest large population centre, which is served by daily flights from Stockholm, and a well-maintained road and rail system which connects it the rest of Sweden and to Norway.

The climate is sub-arctic. The snow cover, which reaches on average from 50 to 75cm, extends from mid-November to mid-April. Spring is characterized by a 2 month thaw during which time severe damage may occur to un-metalled roads. Average temperatures range from +15^o in summer to -15^o in winter. Average summer precipitation is 450mm, with 250mm in winter. The prevailing wind directions are west and east with low average velocities of 1m/s. Summer days are long, and in turn winter days are short. Exploration activities can be carried out year-round with the exception of break-up in late April or early May.

The Norrliden deposit is located between 250m and 350m elevations, midway between two lakes, Kotjärnen and Jungfrutjärnen. There are several significant water features in the immediate vicinity. These include three lakes within a 1km radius of the deposit and two drainage courses, one of which traverses the area likely to be disturbed by mining.

The area surrounding the Norrliden deposit and most of the permitted site consists of forestry lands and largely planted coniferous forest. Stands of trees are interspersed with small hollows containing marshes and swamps. The land surface is established on a generally thick (5-20m) layer of glacial till, consisting of sands, clays, gravels and boulders. The forest floor is made up of ferns, mosses, heathers and small trees, with a saturated boggy nature due to the impeded drainage and clayey nature of the till.

The bedrock is formed of strong hard metamorphosed volcanic rocks, which are generally dry impervious and non-porous. It is possible that shear zones of crushed rock, which may be conduits for groundwater movement, exist.

Plans show several existing roads in the immediate vicinity of the deposit and an existing power line of unspecified voltage runs within 600m of the proposed pit. An aerial ropeway formerly used by Boliden approximately parallels the power line.

Population is sparse with the nearest existing dwellings or other structure some 900m from the centre of the deposit. There is a small village at Örträsk, approximately 1.5km south-east. Ortråak is a small tourist/summer village that hosts a funicular railway. This cableway previously used to transport ore from the mines in the west of the county to the concentrator in the town of Boliden.

There are no known areas of archaeological significance on the property. The area is used, as is most of the surrounding countryside, for grazing reindeer herds by the local Lapplanders or Samis.

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5 HISTORY

The Norrliden deposit is a volcanogenic massive sulphide occurrence discovered by the Swedish Geological Survey (SGU) in the 1960s following drilling of a geophysical electromagnetic anomaly detected in 1958-59. A total of 66 drill holes were completed during the period 1960 to 1974 totalling 13,257 m.

A preliminary NAN resource estimate made from 40 drill holes drilled by SGU resulted in a resource estimate of 1.4Mt at 4.5% Zn, 0.8% Cu, 0.5% Pb, 79g/t Ag, 0.5g/t Au. In 1999, NAN initiated a drilling programme to establish the nature and full extent of the mineralisation, a programme of re-logging and re-sampling the SGU drill core and metallurgical test work.

The NAN drilling was carried out on sections 20m apart aimed at providing better definition of the geology and resource. A total of 42 diamond drill holes totalling 6,148m were completed.

A mineral resource estimate was prepared for NAN in January 2000 by Micon International Ltd. This culminated in a computerised block model.

Subsequent to this, in March 2000, the Micon study was audited by Mr Richard Parker of A.C.A. Howe, which included a review of the geological procedures, database, and methodology used to compile the Micon resource estimate. During this audit, an alternative resource estimation was also completed by A.C.A. Howe, using a cross-sectional method. This geological resource estimation, at a cut-off gross value of $28/t (gross revenue value), was 774,000t at 7.85% Zn, 0.8% Pb, 0.9% copper, 104g/t Ag and 1.3g/t Au. At the time this resource was classed as Inferred according to international standards.

Following on from the recommendations made by A.C.A. Howe, the interpretation of mineralised zones was revised, to correspond much more closely with the overall geological interpretation. These zone definitions were then used in an updated resource modelling and estimation project by Adam Wheeler during March 2004, with subsequent updates during April 2006.

6 GEOLOGICAL SETTING

6.1 Regional Geology

The regional geology descriptions in this report are taken from the Micon, 2002 report and various internal NAN reports, including a Technical Report on the Storliden Mine, February 2005 by Adam Wheeler. These reports are used with the permission of the Lundin Mining Corporation.

Norrliden is situated in the centre of the western end of the Skellefteå mining district. This district consists of an extensively mineralised Palaeo-Proterozoic (c.1.8-1.9Ga.) belt of mainly felsic submarine volcanics, that is partially covered by younger sediments and intruded by late intrusives.

The Skellefteå district covers an area 120km long by 30km wide, extending from the Baltic coast to west of the town of Malå. More than 85 massive sulphide deposits are known from this belt, of which 52 collectively contained 161Mt before mining with average grades of 0.7% Cu, 3.0% Zn, 47 g/t Ag, 1.9 g/t Au, 0.4% Pb and 0.8% As, often with significant amounts of Sb and Hg (Allen et al., 1996).

The district has been Sweden's main copper, zinc and gold producing region for the last 80 years and a number of mines have been, or currently are, operated, most notably at Boliden whose deposit was mined from 1925 to 1967 and spawned the major mining company of the same name. There are currently four Boliden AB mines in operation in the area, three

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underground (Kristineberg, Petiknäs and Renström) and one open pit (Maurliden). In addition, NAN brought the Storliden deposit into production in 2002.

The oldest known rocks in the Skellefte greenstone belt are the 1.88 Ga volcanics of the Skellefte Group, a suite of basaltic to rhyolitic but dominantly felsic extrusive rocks with intercalated, generally fine-grained sediments. Nearly all of the mineral deposits of the Skellefte belt are hosted by this diverse group of volcanic rocks which is overlain by a sedimentary assemblage called the Vargfors Group consisting of fine to coarse-grained sediments and intercalated volcanic rocks.

The Arvidsjaur Group, a younger suite of subaerial volcanics of felsic composition, including ash-fall tuffs, ignimbrites and volcaniclastic sediments, is interpreted to be laterally equivalent to the Vargfors sediments. Intruding these lithologies are various intrusive rocks (Jörn suite) ranging from gabbro to granite in composition but predominantly tonalitic. The late to post-orogenic Revsund granite completes the rock sequence in the Skellefte greenstone belt.

The structure in the Skellefte district is dominated by upright, isoclinal to open folds and numerous shear zones and brittle faults. The main fold axes plunge moderately to the west in the western part, and moderately to steeply to the east in the eastern part, The Skellefte belt was folded and metamorphosed starting at 1.85 Ga, and the metamorphic facies increases outward from greenschist facies in the centre to lower amphibolite grade to the west, south and east, including the Norrlidden area.

The entire area is covered by a persistent veil of glacial deposits, mainly glacial till, that range from a few metres to more than 50m thick and covers not only the low-lying areas but most of the hills as well. As a consequence, outcrop is very scarce, and outside of the mining areas, the regional geology is incompletely known. On a local scale, the accuracy of the published data on bedrock geology is thus subject to change.

6.2 Local Geology

The Norrliden deposit is a massive sulphide orebody hosted by tuffite, sediments and pyroclastics. Narrow dykes and sills of rhyolite and andesite intrude this assemblage. All the lithologies have been regionally metamorphosed to low amphibolite facies and intruded by the Adak granite (ca 1.8 Ga.) which has imparted some contact metamorphic effects.

The deposit is hosted by a volcanic sequence striking about 110° and dipping about 60° south. Rocks within the local volcanic package have been logged as felsites, rhyolites, tuffites and greenstones. Recognition and correlation of these rock types is generally somewhat arbitrary due to their gradational nature and the overprinted alteration. Well-developed alteration halos, mainly above the ore zone, are observed. These are characterised by cordierite, tremolite - actinolite, carbonates, magnetite, silicates and sericite.

Two distinctive rock types do occur, described as very fine grained foliated greenstone, and andesite dyke. The "foliated greenstone" is characterised by delicate laminations which appear to be primary bedding features. It occurs in the immediate hanging wall of the highest massive sulphide lens.

The andesite dyke is recognisable on account of its abundant tabular feldspar phenocrysts. It cross-cuts the central part of the deposit.

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7 DEPOSIT TYPES

The Norrliden deposit is a polymetallic, stratabound and stratiform volcanogenic massive sulphide (VMS) deposit. The ore types and their distribution suggest a massive sulphide mineralised zone with an associated stringer zone.

The deposit consists of sub-vertical lenses of massive sulphide up to 30m thick with an east-west strike length of 400m and a depth extent of at least 300m. The deposit is apparently open on the east side at a depth of 300 m. The depth to the top of the deposit is 15 m from the surface.

Norrliden displays the classical characteristics of Skellefteå VMS deposits and this model type and morphology has been used as the basis of the exploration activity to date; consisting of diamond core drilling from surface, with holes angled to intersect the orebody at as normal an angle as possible. As anticipated in deposits of this type, stringer mineralisation generally underlies the massive mineralisation and this zonation has been used to guide the positioning and depths of holes. Gold and lead enrichment is observed but the typical copper-zinc- lead zonation has not been found to date.

Detailed analysis of the facies of the volcanic host rocks to the sulphide deposits in the the Skellefteå mining district indicate that many of them were emplaced by subsea-floor replacement into porous mass flow volcaniclastics, rather than by exhalation onto the sea floor at the time. As a result, they are generally underlain, and often surrounded by, alteration haloes that tend to be larger than their counterparts in the Canadian Shield. These deposits may have genetic affinities to the sub-volcanic replacement deposits in the South American Andes such as Cerro de Pasco. One major difference, however, is that both host rocks and sulphide deposits in the Skellefte belt were folded and metamorphosed starting at around 1.85 Ga.

8 MINERALISATION

The descriptions in this section are taken from the Micon, 2002 report and various internal NAN reports, including a Resource Audit, January 2000 by A.C.A. Howe. These reports are used with the permission of the Lundin Mining Corporation.

The main deposit lies between surface and 200-300m below surface. It consists of a 400m east-west trending massive sulphide ore-body, which varies in thickness and dips at 80^o to 85^o to the south. The deposit does not outcrop.

The mineralisation is characterised by sulphides occurring in numerous lenses which lie sub-parallel the volcanic stratigraphy, close or at the contact between acid and basic volcanic rocks in a strongly deformed quartz-sericite rich horizon.

The mineralised material consists mainly of pyrite, fine-grained sphalerite and chalcopyrite with dispersed galena and minor arsenopyrite. Many samples contain gold values of economic interest. Pyrite is the dominant sulphide mineral present.

Two main styles of mineralisation are recognised in NAN's geological interpretation: massive to semi-massive sulphides and mineralised, 3-40% sulphides.

The massive to semi-massive sulphides zones comprise banded pyrite and sphalerite +/- minor chalcopyrite, galena and arsenopyrite. Zones categorised as mineralised, 3-40% sulphides includes stringer, disseminated and semi-massive mineralisation, often characterised by silicification and sericitisation. The stringer mineralisation generally underlies the massive mineralisation.

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Some metal zonation is apparent. In the western part of the deposit a zinc rich zone is underlain by copper-enriched stringer mineralisation, a pattern which is reversed to some extent in the eastern part of the deposit.

Two main zones of mineralisation, the form of steeply dipping ore lenses, occur for resource modelling purposes: one to the east and one to the west of a relatively barren region of the deposit. A number of other, peripheral zones or lenses have also been defined by geological modelling.

The larger, western group of mineralised lenses is generally characterised by reasonable geological (physical) continuity, reflected by fairly confident correlation of lenses from drillhole to drillhole. The smaller, eastern group of mineralised lenses show less geological continuity, particularly laterally, although vertical continuity is reasonable. The causes of lateral discontinuity are not known. Folding and faulting of sulphide lenses has apparently been reported in some of the core-logs, but their exact role in controlling the distribution of mineral lenses is uncertain.

9 EXPLORATION

The Norrliden deposit was discovered by the Swedish Geological Survey (SGU) in 1968 following drilling of a geophysical electromagnetic anomaly detected in 1958-59. In a period from 1960 to 1974 a total of 66 drill holes were completed totalling 13,257 m.

In 1999, NAN initiated a drilling programme to establish the nature and full extent of the mineralisation, a programme of re-logging and re-sampling the SGU drill core and metallurgical test work.

The NAN drilling was carried out on sections 20m apart and a total of 42 diamond drill holes totalling 6,148m were completed. 29 of the former SGU cores were re-sampled and re-assayed by NAN.

10 DRILLING

10.1 Drillhole database

The Norrliden database as at April 30, 2006 consisted of 94 diamond drillholes which were drilled from surface; 52 SGU drillholes (of which 29 have duplicate assays taken by NAN) and 42 NAN holes. These 94 drillholes have provided 2092 samples for use in the estimation process. The NAN drilling took place between June 1998 and November 1999.

A further 14 SGU initial exploration drillholes have not been used in this study because they were either not assayed (having been used for geophysical not sampling purposes) or (in the case of one hole) because a collar position was not recorded. Their omission does not impact on the resources estimated.

Diamond drilling used conventional drilling equipment and industry standard practices. All NAN's exploration drillcore was geologically logged at NAN's Malå field office.

The data density (spacing and distribution) is sufficient to establish appropriate levels of geological and grade continuity for the resource estimation techniques used and the resource classification system applied.

The orientation of sampling data relative to the geological structures appears to be appropriate and is not believed to have introduced any bias into the sampling.

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10.2 Surveying

All drill hole collars have been surveyed, including the old SGU casings, with the surveying work completed by an official surveyor. Drill hole collars were surveyed by NAN using a theodolite and stadia rod and a local surveying contractor, who was engaged to re-survey collar positions using a Global Positioning System (GPS) unit.

The quality and adequacy of topographic control has not been assessed, but Lundin have not indicated any concerns over this issue.

The inclination (dip) of the holes has been measured for most holes. For the NAN drilling, this downhole dip surveying was performed by the drilling company, Kati OY, using an electrical device, which picks up the dip from mercury in a measurement tube. For the NAN holes, which are short and relatively straight, azimuths were not measured down the hole.

The SGU holes were fully surveyed but Lundin staff have expressed concerns over some of the azimuth and dip measurements, particularly for the longer holes. A limited number of holes were re-surveyed using a Maxibore system, however, and Lundin report that the results were satisfactory.

Overall there do not appear to be any significant concerns over drillhole deviation and, while the absence of complete verification data for the surveying of samples does introduce an element of technical risk to this study, a sufficient number of survey readings exist to give reasonable confidence that the survey information is providing reliable three-dimensional positioning of samples.

There are no apparent reasons to consider that the survey data is introducing any bias into the estimates produced. The location of data points appears to be robust in three-dimensions. Zones and lenses identified by the samples produce coherent mineralised envelopes, with the geometric shape and continuity expected from this type of deposit. The relative x,y,z coordinate positions of composites are producing robust semi-variograms that can be modelled, which suggests that relative sample locations have been well defined.

11 SAMPLING METHOD AND APPROACH

11.1 Sampling Method

Details of the SGU sampling method are not available but based on previous experience are assumed to have followed similar practices to those outlined below. There is no reason to suspect that the SGU sampling methodology introduced any bias into the database.

NAN holes were drilled to provide 42 mm diameter core samples. These were placed in wooden boxes which were conveyed to the NAN field office in Malá. The core was logged by a geologist and the core recovery was recorded. Drill core was marked for sampling by the geologist according to the rock types, alteration assemblages, and mineralisation observed in the core during logging.

For the SGU sampling, the commonest sample length was approximately 2m. For the NAN drillholes, sample lengths were generally shorter with the commonest and average sample length of approximately 1m, due principally to greater respect of divisions between copper-rich and zinc-rich zones.

All mineralised intervals selected for sampling from NAN's exploration drillcore were sawn in half at the Malå field office, with the remaining half-core retained for reference. The majority of this core is stored in wooden core boxes inside a heated warehouse adjacent and connected

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to NAN's field office and is available for inspection. Bags of core samples were placed in strong boxes and shipped by train to NAN's sample preparation facility in Uppsala.

The SGU re-sampling by NAN was done by taking ¼ of the core, on the same sample lengths. The SGU core is believed to have been retained by the SGU's Malå office and core library.

11.2 Core logging and recovery

Core logging has been carried out by a number of geologists and is of variable quality. Concerns were raised in the A.C.A. Howe report in 2000 that that a lack of consistency and standardisation in logging did not provide an adequate basis for an indicated resource. These comments appear to be of relevance mainly with regard to the SGU drillholes.

Since 2000, further interpretation work and geological modelling has been carried out by NAN geologists and Adam Wheeler is satisfied that the existing geological model and database provides an adequate basis for a resource estimation, including allocation of parts of the main zones as indicated resources (see section 16.4).

Core recovery for the SGU holes was reportedly good and for the NAN holes is over 90% even in the most broken of holes. There are no concerns over core recovery that would impact on the resource estimate or classification.

11.3 Bulk Density

Density (specific gravity) determinations were made for each NAN sample in the database, using a dry immersion method. This is a standard, appropriate method for a project at this stage of exploration and it is believed to have been used for the SGU samples as well.

For NAN samples, density determinations were made by technicians at the Uppsala sample preparation facility using a standard protocol. A representative piece, weighing between 500g-1kg, of sawn drill core was selected from each sample interval and the dry weight of the specimen was recorded. The dry, unsealed specimen was placed in a basket and submerged in a vessel containing water, recording the weight of the specimen in water as quickly as possible to avoid saturation of the sample.

The density of the sample was calculated using the formula:

• Density (t/m³) = dry weight (air) / [dry weight (air) - dry weight (water)]

There is always a concern that density measurements based on core alone may not fully reflect the bulk density of large volumes of rock; due to the inherent variability in fracture spaces and voids and the geological variations in rock masses seen in a bulk mining sense. Massive sulphide deposits, with their variable sulphide mineral contents, also require careful consideration of density in the ore horizons.

Density measurements are available for 1866 out of 2092 samples in the complete database (89%). More importantly, 566 of 579 (98%) samples in the main ore zones and 103 of 106 (97%) samples in the peripheral zones have density measurements. Sufficient measurements clearly exist, therefore, to allow interpolation of density values into blocks (see section 16.4).

Adam Wheeler considers that sufficient, representative density measurements exist to allow calculation of a bulk density factor for the conversion of resource volumes into tonnages.

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12 SAMPLE PREPARATION, ANALYSES AND SECURITY

The assay database includes 1628 samples (NAN drillholes and check samples from SGU holes) which were analysed for gold, silver, copper, lead, zinc, bismuth, antimony and arsenic by Cone Geochemical, Colorado. The database also contains original assays only for 464 half-core samples from SGU's holes.

The sawn core samples from NAN's drilling campaigns were transported to the Uppsala preparation laboratory where they were crushed and pulverised. Preparation of drill core samples for analysis involved initial reduction in a jaw crusher followed by pulverisation in a ring grinder. Drill core samples weighing 2-4 kg were crushed to 60% passing a 2mm sieve. A 500g sub-sample was riffled from the crushed material and pulverised to 90% passing 100µm.

A 200-300g sub-sample was riffled from the pulverised material for shipment to the assay laboratory. Coarse reject material was re-bagged and stored for future reference. The pulverised material was split using a rifle splitter and duplicate pulp samples were prepared.

NAN implemented several practises to minimise the potential for contamination during sample preparation. These measures included use of a powerful dust extraction system in the comminution circuit and the use of barren rock to clean crushing and grinding surfaces between each sample. The pulps and coarse rejects of all samples have been retained for future reference.

The 200-300g pulp samples were then sent for assay at the facilities of Cone Geochemical Inc. (Cone), located in Lakewood, Colorado. Assaying was done by standard atomic absorption spectroscopy (AAS) for copper, zinc, lead and silver following digestion in a solution of aqua regia. Gold analyses were accomplished by standard fire assay fusion using a conventional 30g (1 assay ton) sub-sample with an AAS finish. Arsenic values were determined by AAS following a perchloric/nitric acid digestion. Bismuth values were determined using a KClO₄/HCl digestion, and antimony values were determined using an organic extraction.

No detailed descriptions are available on the procedures or laboratories used to assay the original SGU samples (see section 13.4). SGU samples were reportedly assayed by Kemiska Laboratoriet over three assaying periods. The Da Silva, 1999 report indicates that two of these batches were considered reliable but a third was not. Any drillholes with assay results based solely on this third batch of samples have been excluded from the resource estimate.

Sample selection, splitting, preparation and assay were all carried out to industry standards and there are no concerns over sample security or probity.

13 DATA VERIFICATION

The descriptions of the quality control (QC) regime given in sections 13.1 and 13.2 are taken from the DaSilva, 1999 report and various internal NAN reports. These reports are used with the permission of the Lundin Mining Corporation.

Adam Wheeler has reviewed and discussed the content of these reports with Lundin/NAN staff and is satisfied that they represent a fair and accurate description of the QC procedures used in the exploration and sampling programmes at Norrliden. Adam Wheeler has then, independently, undertaken a review of data verification issues (section 13.3) and drawn conclusions (section 13.4).

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13.1 Standards, Blanks and Duplicates

Quality control (QC) was accomplished by the submission of blank and duplicate samples, totalling some 6.6% of NAN's 1628 sample suite (NAN holes + SGU checks). No details of the QC procedures used to assay the original SGU samples are available (see section 13.4).

QC samples for the NAN suite were inserted at approximately regular intervals into sample batches. Blanks were composed of clean rock (usually unmineralised granite with a low trace element content). Duplicate core samples were chosen at random in the field and the corresponding pulverised reject used to make duplicates with the aid of a Jones splitter.

13.2 Analyses by Independent Laboratories

Within-laboratory repeat assaying was undertaken on duplicates at the facilities of Cone Geochemical Inc. in Colorado. 61 duplicate samples (3.7% of total) were submitted to Cone for re-assay in 1999. Duplicate samples were taken from both SGU-NAN re-sampled holes (16) and NAN's own drillholes (45).

Assay results from duplicates taken from NAN's own drillholes and from SGU holes which NAN re-sampled (i.e. within laboratory repeats), revealed repeatability (precision) of 95% or better for all elements.

No formal, systematic check assaying at a second laboratory was undertaken for samples in the database. For the SGU-NAN re-sampled holes (analysed by Cone), however, results were compared to the original SGU assays (analysed by Kemiska Laboratoriet) to serve as a further quality assurance measure.

The assay results showed repeatability (precision) in excess of 95% for silver, copper and zinc. Gold and lead comparisons revealed a lower degree of repeatability (90%). This is attributed to analytical procedural differences over the 30 plus years between the sets of analyses.

A total of 46 blank samples (3.7% of total), made from preparation lab clean rock, as well as one made from 95% clean rock and 5% high grade material, was also submitted to Cone for within-laboratory check assaying. Results for the suite of blank samples gave an acceptably narrow range of very low or undetectable values. The high grade sample was clearly identifiable in the sample set as an outlier, anomalous to the low background levels of the other blanks.

13.3 Independent Review

Adam Wheeler's review of the Quality Control report by Da Silva, 1999, and discussions with Lundin staff, indicates that drillholes and samples under the control of NAN (including check samples from SGU holes) have been subjected to appropriate quality control procedures and checks with respect to the introduction of duplicates and blanks. A statistical summary of these results is shown in Table 13-1, with corresponding scatter plots in the following charts. For zinc and copper, by far the primary metals for this deposit, 90% of the resampling duplicates have a relative error less or equal to 5%. Very high coefficients of determination are apparent for all metals.

The level of precision within the assay population is good and the accuracy also appears to be good, although a more industry-standard approach would have seen the use of reference materials (standards) as well as blanks in the sample stream to check accuracy. The use of blanks alone has acted as a check for contamination or gross errors in sample handling, rather than specifically checking accuracy.

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Table 13-1. Summary Statistics For Duplicate Samples

	Precision Testing
		Number of
Metal	R2	Pairs	Precision
Zn	96%	61	3%
Cu	99.9%	61	5%
Pb	99.9%	52	9%
Ag	99%	61	11%
Au	99.9%	61	16%
		SGU	NAN
Zn	Mean	2.20	2.30
	SD	4.41	4.45
	Coeff Var	2.00	1.93
	Skewness	2.49	2.35
Cu	Mean	2.20	2.30
	SD	4.41	4.45
	Coeff Var	2.00	1.93
	Skewness	2.49	2.35
Pb	Mean	0.32	0.32
	SD	0.93	0.94
	Coeff Var	2.93	2.96
	Skewness	4.33	4.38
Ag	Mean	34.03	33.05
	SD	66.54	61.58
	Coeff Var	1.96	1.86
	Skewness	4.60	4.27
Au	Mean	1.25	1.21
	SD	5.79	5.52
	Coeff Var	4.64	4.56
	Skewness	7.26	7.25

Notes

. R² = coefficient of determination
. R = Pearson product moment correlation coefficient
. Precision determined such that 90% of the corresponding samples have a % relative error < precision value given
. Relative error = (absolute difference from mean or pair)/mean of pair
. All available data used for precision calculations

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In addition, Adam Wheeler independently analysed data from the 472 samples taken by NAN from the remaining half-core from 29 of SGU's original 66 holes. These re-sampled intervals acted as a type of duplicate sampling to help verify the data quality. A statistical summary of these results is shown in Table 13-2, with corresponding scatter plots in the following charts. For zinc and copper, by far the primary metals for this deposit, 90% of the resampling duplicates have a relative error less than 30%. Although this error level seems fairly high, it must be remembered that in many cases, the SGU core had already been resampled previously by Boliden. This meant that core has been cut twice to leave the remaining ¼ of core. Coupled with the small core size (T46), and core loss due to oxidation, this has added to precision errors associated with resampling. Despite this, very good overall correlations have been obtained between zinc and copper. All metals yield very similar overall mean grade and standard deviation values. These results indicate no significant bias for any of the metals.

Table 13-2. Summary Statistics For Resampling

			Precision Testing
	Total
	Number of		Number of
Metal	Pairs	R2	Pairs	Range	Precision
Zn	367	96%	138	>0.3%	30%
Cu	406	95%	301	>0.03%	25%
Pb	196	92%	196	>0	27%
Ag	359	72%	269	>5g/t	39%
Au	191	46%	80	>0.2g/t	53%

		SGU	NAN
Zn	Mean	1.98	2.03
	SD	5.02	5.19
	Coeff Var	2.54	2.56
	Skewness	3.73	3.49
Cu	Mean	0.52	0.51
	SD	0.80	0.80
	Coeff Var	1.54	1.56
	Skewness	3.07	3.03
Pb	Mean	0.44	0.44
	SD	0.96	0.96
	Coeff Var	2.18	2.17
	Skewness	3.54	4.07
Ag	Mean	38.06	38.43
	SD	68.45	84.97
	Coeff Var	1.80	2.21
	Skewness	3.73	4.92
Au	Mean	0.52	0.55
	SD	0.84	0.67
	Coeff Var	1.62	1.22
	Skewness	3.64	2.34

Notes

. R² = coefficient of determination
. R = Pearson product moment correlation coefficient
. Precision determined such that 90% of the corresponding samples have a % relative error < precision value given
. Relative error = (absolute difference from mean or pair)/mean of pair

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The database also contains original assays only for 464 half-core samples from SGU's drillholes, Given the good correlation between re-sampled intervals indicated above, and the known standard of sampling and analytical procedures used elsewhere by the Swedish Geological Survey (SGU), there is no reason to suspect that the use of these samples is introducing any bias into the database.

NAN specifically drilled three twinned holes (i.e. drilled within a few metres of the previous hole) as a check against the older SGU holes. The pairs obtained are summarised below:

SGU	NAN
63102	99005
60101	99006
63109	99008
63107	99007

Sections displaying the zinc and copper grades obtained with the 4 different sets of twinned holes are shown in Appendix D. These show very good correspondence between the higher grade intersections of both zinc and lead.

13.4 Conclusion with respect to Data Verification

Although a complete, systematic and thorough quality control programme has not been undertaken for the sample set at Norrliden, the data that is available has not highlighted any significant problems that would compromise the integrity of the database used in the resource estimation.

The absence of complete quality control data does, however, create a level of uncertainty in the sample set and, to reflect this, it is considered inappropriate to use these samples to support measured resources. Sufficient confidence in the assay data does exist to support classification of indicated resources where this is also justified by other appropriate factors, such as data density and search parameters.

14 ADJACENT PROPERTIES

There are no exploration or mining properties currently active in the immediate vicinity of Norrliden. There is no data available on adjacent properties that would materially affect the assessment of this resource estimate.

The Storliden VMS deposit is some 45 road km to the northwest of Norrliden, and Lundin has an existing mine there. The mine commenced production in April, 2002 and remains in operation today. Boliden AB is providing milling services for the Storliden ore at its concentrator located near the town of Boliden, some 90km from Storliden. Facilities at Storliden and the Boliden concentrator may be used in development of Norrliden; but information relating to Storliden is not necessarily indicative of the mineralisation on the Norrliden property.

15 MINERAL PROCESSING AND METALLURGICAL TESTING

The descriptions in this section are taken from the Micon, 2002 report and various internal NAN reports. These reports are used with the permission of the Lundin Mining Corporation. The anticipated metallurgical performances have been discussed and agreed with Lundin staff and form the basis of the NSR parameters determined in section 16.2.

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The relatively small size of the deposit does not appear to justify a dedicated concentrator plant to upgrade ore at the site. It is therefore anticipated that ore from Norrliden will be transported to an existing concentrator some distance away.

A limited metallurgical testwork programme conducted by Lakefield Research Limited suggested that Norrliden ore is generally finer grained than Storliden ore. In particular, the degree of liberation of galena and the occurrence of pyrrhotite and arsenopyrite inclusions in sphalerite indicate that the metallurgical response of Norrliden ore is likely to be closer to that of other copper/lead/zinc ore with similar head grades from the SkeIIeftea area, which is currently processed by Boliden AB at their Boliden concentrator..

At the time of writing, the anticipated recoveries to concentrate and concentrate grades are:

Product	Conc. Grade	Recovery
Zinc concentrate	54% Zn	85%
Copper concentrate	29% Cu	85%
Lead concentrate	70% Pb	70%

In addition some silver reports to the lead concentrate; both silver and gold report to the copper concentrate. Only the precious-metal content of the copper concentrate is considered in the NSR calculations (section 16.2). Pyrrhotite and arsenopyrite inclusions will affect concentrate grade and the penalty levels of iron and arsenic but this has not been quantified in this study.

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16 MINERAL RESOURCE ESTIMATE

16.1 General

This resource estimation stems from an initial geological block modelling project complted in March 2004. This study was then subsequently updated in April, 2006, reflecting more recent price parameters. This report section describes the work completed during the original and updated studies, which can be summarised as:

• Input and validation of drillhole sample data.
   
• Interpretation and geostatistical analysis of sample data.
   
• Generation of geological block model.
   
• Resource evaluation.

There are two distinct zones of mineralization, in the west and east ends of the deposit area. For each of these main zones, sections were interpreted based on a cut-off of SEK120/t (combining contributions from all main metals). This interpretation was also strongly controlled by previous geological interpretations completed by NAN (North Atlantic Resources).

Stemming primarily from these main zones' interpretations, a block model was created. Additional peripheral blocks were also created outside of the main structures, based on sectional perimeters as well as three-dimensional projection from other intercepts.

Metal grades were interpolated into the block model, using parameters supported by a geostatistical analysis of drillhole composites. This also enabled the definition of pertinent resource classification criteria, relating to search distances, numbers of drillholes and composites, as well as the source of drilling data.

Resources were classified according to the JORC code. A summary of the resource evaluation is shown in the table below, based on a block cut-off of SEK120/t and a minimum mining width of 3m.

Resource Summary

ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Indicated	568	4.9	0.4	0.8	0.9	59.7	452
Inferred	948	4.0	0.4	0.8	0.7	59.1	399
Total	1,516	4.3	0.4	0.8	0.8	59.3	419

Notes   . Based on block cut-off of SEK120/t

. NSR calculated using long-term base case prices:

	Zn	Pb	Cu	Au	Ag
	c/lb	c/lb	c/lb	$/oz	$/oz
	/%	/%	/%	/g/t	/g/t
Prices	60	33	120	450	6.5
Coefficients	46.3	20.8	143.2	54.4	0.94

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16.2 Drillhole Data Processing and Interpretation

The available drillhole data was compiled in Excel spreadsheets, with separate sheets for assays, survey and collar data. This data was imported into Datamine, combined and then desurveyed, where the central coordinates of each sample were calculated. This data was then examined in plan, section and 3D views.

The drillholes came from two sources - SGU and NAN (North Atlantic Resources AB). Many of the much older SGU holes had also been re-assayed by NAN. All of the data from these sources were imported, and then merged in such a way as to ensure the most recent assay data was utilised. A drillhole collar plot is shown in Fig 16-1.

Based on up-to-date parameters associated with the nearby Boliden processing operations, as well as revised long-term metal prices, coefficients were determined to enable the calculation of contained NSR values for both the sample and model data. These parameters and calculations are summarised in Table 16-1, for the long term base case prices. Similar parameters for an alternative LOM price scenario were also derived. The resultant parameters for these different price scenarios are summarised below:

		Zn	Pb	Cu	Au	Ag
		c/lb	c/lb	c/lb	$/oz	$/oz
		/%	/%	/%	/g/t	/g/t
Long Term	Prices	60	33	120	450	6.5
Base Case	Coefficients	46.3	20.8	143.2	54.4	0.94
LOM	Prices	90	35	180	500	9
Scenario	Coefficients	71.2	22.6	221.4	60.5	1.3

Having used the base case coefficients to calculate an updated NSR value in combined sample data, 20m spaced sections were examined. As well as viewing the sample data, previous NAN geological interpretation strings were also superimposed, imported from MicroStation files.

With this data background, two main zones were interpreted (east and west), based on a cutoff value of SEK120/t (for base case prices). The main east and west zones are either side of a barren corridor. This SEK120/t cut-off level was chosen as being relevant for potential economic considerations. Typical sections showing drillholes and the resultant mineralised zone interpretations are shown in Figs 16-2 and 16-3, for the west and east end, respectively. This zone definition was defined so as to conform to the existing NAN geological interpretation, characterised by numerous lense-type structures sub-parallel to the volcanic stratigraphy. Both the geological interpretations, as well as the mineralised zone models defined in this study, are shown in the model sections shown in Appendix C.

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Table 16-1 Derivation of NSR Parameters

Long Term Metal Prices						Zinc Concentrate Value
	zinc	copper	gold	silver	lead	Zinc recovery (planned)		85.00%
$/tonne	1,322.76	2,645.52			727.52	Zinc Concentrate grade (planned)		54.00%
c/lb	60.00	120.00			33.00	Zinc Concentrate ratio = tonnes Zn concentrate / tonnes feed
$/oz			450.00	6.50		therefore 7.90%*0.85%/0.54%		0.124352
Exchange Rate						Net Smelter Return (NSR) value
Swedish Kroner (SEK)			8.00 SEK/US$			Payment terms = 85% (min deduction 8 units)
						Payment per tonne zinc concentrate in SEK/tonne Zn conc
Average Deposit Feed Grades						payment x price x grade x exchange rate
	zinc	copper	gold	silver	lead	85% x 1,146.39 x 54% x 8 =	4,857	SEK/tonne conc
	% Zn	% Cu	g/t Au	g/t Ag	%Pb	Treatment charge $160/tonne x SEK/$	-1,280
	7.9	0.9	1.3	104	0.8	Escalator if price > $1,000, then add 16c/$
						$1,146-$1,000=$146 x $0.16 x 8.0 SEK/$	-413
Lead Concentrate Value						Penalties, freight, handling, insurance etc	-222
Lead recovery (planned)				70.00%			2,942	SEK/tonne Zn conc
Lead Concentrate grade (planned)				70.00%		multiplied by Zinc Concentrate ratio	366	SEK/tonne feed
Lead Concentrate ratio = tonnes Pb concentrate / tonnes feed						NSR factor for Zinc	46.31	SEK/tonne feed/% Zn
therefore	0.80%*0.70%/0.70%			0.008
						Copper Concentrate Value
Net Smelter Return (NSR) value						Copper recovery (planned)		85.00%
Payment terms = 95% (min deduction 8 units)						Copper Concentrate grade (planned)		29.00%
Payment per tonne lead concentrate in SEK/tonne Pb conc						Gold recovery to Cu concentrates		50.00%
payment x price x grade x exchange rate						Silver recovery to Cu concentrates		60.00%
95% x 661.38x 70% x 8 =			3,870 SEK/tonne conc			Copper Concentrate ratio = tonnes Cu concentrate / tonnes feed
Treatment charge	$130/tonne x SEK/$		-1,280			therefore 0.9% x 85% / 29% =		0.026379
Escalator if price > $500, then add 16c/$						Gold in Cu concs g/t Cu conc		24.64
$1,146-$500=$146 x $0.16 x 8.0 SEK/$			-291			grade (1.3g/t) x recovery (50%) / Cu conc ratio
Penalties, freight, handling, insurance etc			-222			Silver in Cu concs g/t Cu conc		2,365
			2,077 SEK/tonne Pb conc			grade (104g/t) x recovery (60%) / Cu conc ratio
multiplied by Lead Concentrate ratio			17 SEK/tonne feed			Net Smelter Return (NSR) value
NSR factor for Lead (481/11.2% Zn)			20.77 SEK/tonne feed/% Pb			refining charge 101.4 US$/tonne
						payment deduct 1% Cu, pay for balance x copper price(US$) less refining charge
Payment for gold			2,681 SEK/tonne conc			escallator if US$ copper price > $1,984, then additional charge of 10c for every $ over $1,984
(Au in Cu concs - 1g/t) x 98% x price ($350/oz/31.1034) x exch rate						treatment charge $55 per DMT
NSR factor for Gold			54.41 SEK/tonne feed/g Au			gold credit deduct 1 g/t x gold price x 98%
(121 / Au grade (1.3g/t) x Cu conc ratio)						silver credit deduct 30 g/t x silver price x 95%
						gold refining no charge
Payment for Silver			3,709 SEK/tonne conc			silver refining no charge
(Ag in Cu concs - 30g/t) x 95% x price ($5.0/oz/31.1034) x exch rate						Payment for Copper	5,551	SEK/tonne conc
NSR factor for Silver			0.94 SEK/tonne feed/g Ag			Cu conc grade (29-1)% x ((price-refining)-0.1 x (price-1984)) x exch rate (8.0)
(178 / Au grade (104g/t) x Cu conc ratio)						Treatment charge	-440	SEK/tonne conc
						Penalties, freight, handling, insurance etc	-225
						total	4,886.0	SEK/tonne Cu conc
						multiplied by Copper Concentrate ratio	129	SEK/tonne feed
						NSR factor for Copper (417/3.5% Cu)	143.21	SEK/tonne feed/% Cu

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The Norrliden deposit could conceivably be mined by either open-pit or underground. The cut-off grade levels used for subsequent evaluation are discussed in more detail in Section 16.6. Statistics of the contained NSR values (Appendix A) do not show any particularly natural breaks. A minimum thickness of 3m was also applied.

On some sections, internal waste splits were also defined. The strings defining the mineralised envelopes were also snapped directly onto the relevant sample boundaries. This is very important because many of the intercepts are long way off the actual 20m section lines. This can be seen from a long section, shown in Fig 16-4, and a plan view of the drillhole traces, shown in Fig 16-5. These main zone perimeters were then linked together to form three-dimensional wireframe envelopes. There are displayed in 3D views in Figs 16-6 and 16-7.

All of the samples belonging to these main zones were then isolated. A summary of the drillhole data overall, and intersecting the main zones, is shown in Table 16-2. This data summary only pertains to those holes which intersected mineralization.

Some peripheral zones were also defined with individual perimeters on intercepts whose NSR value was greater than SEK120/t.

Table 16-2 Drillhole Summary
		No. of	Re-Assayed	No. of
	Drilled By	Holes	By NAN	Samples
All Zones	SGU	52	29	752
	NAN	42		1340
	Total	94		2092
Main Zones	SGU	20	18	151
	NAN	28		422
	Total	48		573

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16.3 Geostatistical Analysis

A summary of the statistical parameters for the metal grades and derived NSR values, for all samples, the main zones and peripheral zones is shown in Table 16-3. These statistics are both length and density weighted.

Table 16-3. Samples' Statistical Summary

									Log
		Number of	Number				Standard	Geometric	Estimate
ZONE	FIELD	Records	>0	Maximum	Mean	Variance	Deviation	Mean	of Mean
	AU	4072	1847	44.6	0.4	2.1	1.4	0.1	0.5
	AG	4072	1867	1280	30.7	6676.3	81.7	5.9	36.3
ALL	CU	4072	2053	8.1	0.4	0.6	0.8	0.1	0.6
SAMPLES	PB	4072	1924	7.77	0.2	0.5	0.7	0.1	0.3
	ZN	4072	2074	41.9	1.9	24.4	4.9	0.1	1.8
	DENSITY	4072	1886	4.81	3.2	0.3	0.5	3.2	3.2
	AU	563	563	44.6	1.0	5.0	2.2	0.5	1.3
	AG	565	565	1280.0	71.5	15018.1	122.5	28.6	85.0
	CU	566	550	6.6	0.8	1.0	1.0	0.3	1.2
MAIN	PB	566	508	7.8	0.5	1.1	1.0	0.1	0.6
ZONES	ZN	566	566	41.7	5.4	59.2	7.7	1.0	15.0
	DENSITY	579	566	4.81	3.6	0.4	0.6	3.5	3.6
	AU	103	103	5.5	0.7	1.0	1.0	0.3	0.9
	AG	103	103	515.0	58.5	11798.1	108.6	14.0	73.2
PERIPHERAL	CU	103	102	8.1	0.7	1.1	1.0	0.3	1.0
ZONES	PB	103	66	6.7	0.5	0.9	0.9	0.1	1.6
	ZN	103	103	41.9	4.0	39.1	6.2	0.4	10.9
	DENSITY	106	103	4.64	3.3	0.3	0.5	3.3	3.3

Statistical plots were generated for each metal for the main zones' data set. These plots are all shown in Appendix A. Decile analyses of metal grades were also generated, and these results are shown in Appendix B. Marked kinks in the log-probability plots were used to help identify the levels of outlier anomalous grades. This is also shown in the decile analyses. For gold, more than 19% of the sampled metal is contained in just 1% of the samples, above a grade of 7g/t. For silver, more than 12% of the sample metal is contained in 1% of the samples, above a grade of 500g/t. For lead, copper, and zinc, upper outlier levels were also identified, in which more than 10% of the sampled metal was contained in only 1-2% of the analysed samples, indicating logical capping levels. For these reasons, it was decided to apply a top-cut to the metal grades, prior to compositing for grade interpolation purposes. The capping levels used are shown in Table 16-4, along with the number of affected samples.

The log-probability plots for zinc, in particular, two main populations are apparent. However when examining the grade distributions on sections, it was difficult to physically separate these two populations into logical zones. It was therefore decided to apply an indicator approach to zinc interpolation, which is discussed in more detail in Section 16.4.

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Table 16-4. Capping Levels
		Zn	Pb	Cu	Au	Ag
		%	%	%	g/t	g/t
Capping Level		30	4	3.5	7	700
No. of Samples	Main Zone	5	12	16	6	5
Affected	Peripheral Zones	2	4	10	1

After these capping levels had been applied, 3m composites were created of the selected samples within each zone. This gave samples the same support, for consideration of variability. Composites were generated so as to give composite lengths of approximately 3m, with the same lengths within each intersection. This stopped the creation of small composites at the end of each intersection, if a rigid 3m had been applied. Three metres was selected as being reflective of a minimum mining width, and statistical analyses verified that compositing at this length did not drastically alter the statistical features of the captured sample groups.

A summary of the composites' grades statistics is shown in Table 16-5.

Table 16-5. Composites' Statistical Summary

ZONE	FIELD	NUMBER	MAXIMUM	MEAN	VARIANCE	STANDDEV	GEOMEAN	LOGESTMN
	AU	182	5.0	0.9	0.7	0.8	0.6	1.0
MAIN	AG	182	640.2	69.6	8895.1	94.3	38.7	70.1
ZONE	CU	182	3.3	0.8	0.5	0.7	0.4	1.1
	PB	182	4.0	0.5	0.6	0.8	0.1	0.7
	ZN	182	25.8	5.4	40.2	6.3	1.6	12.2
	AU	91	2.8	0.6	0.4	0.6	0.4	0.6
PERIPHERAL	AG	91	308.5	52.5	5467.8	73.9	23.7	55.5
ZONES	CU	91	3.3	0.8	0.5	0.7	0.4	0.9
	PB	91	2.7	0.4	0.3	0.6	0.1	0.7
	ZN	91	18.2	3.2	16.4	4.1	0.8	7.2

Experimental variograms were generated for the composite metal grades in the main zones. The principal directions analysed were along-strike and down-dip (approximately 60 degrees). The zinc grades show a clear bi-model distribution, marked by a strong kink on the log-probability plot at 3% Zn. This was partly due to the metal zonation present. For this reason, a zinc-indicator variable was also introduced, with a value of 0 for all zinc grades<=3%, and a value of 1 for zinc grades greater than 3%. The experimental variogram generated from this zinc indicator variable showed a very clear overall range of influence of 80m, both down-dip and along-strike.

The copper experimental variograms indicated zonal anisotropy, with different sills in different directions. This is fairly common in stratiform-type deposits. The ranges of influence were approximately 60m along-strike and 30m down-dip.

For the lead, an indicator variogram (based on 0.6%Pb) showed a range of influence of approximately 40m.

Based on these variograms, and the greatest economic importance of the zinc and copper grades, a distance of 30m was selected as an initial search distance for grade interpolation. At this distance, both the zinc and copper variograms, show approximately 50% of the overall sill variability. The way in which this search distance was applied in described in more detail in the section 5.

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16.4 Geological Modelling

The three-dimensional wireframe models of the main zones were used to control the generation of blocks within these structures. The parent block sizes and other model parameters are described in Table 16-6.

Table 16-6. Model Prototype

	Origin	Max	Range	Size	Number
X	-305	215	520	10	52
Y	-1500	-1200	300	5	60
Z	-200	260	460	5	92

The X parent block size was chosen as being half the drillhole spacing. For the Y and Z direction, 5m was selected as being more appropriate for the sample spacing within the plane of each section, as well as being potentially of more use for subsequent mine planning purposes.

The generation of blocks was controlled and initiated by three different types of data:

1.    The wireframe model of the two main (east and west) zones.

2.    Individual sectional strings for peripheral zones, projected along-strike +/-10m.

3.    From individual intercepts outside of 1 and 2, where a 3m composite grade greater than SEK120/t could be reached. From such intercepts, sub-blocks were generated for a projection distance of 15m, within the plane of the rest of the structures i.e with a dip of 60 degrees south and a west-east strike.

Composites pertaining to these different zones were then used for the interpolation of metal grades. The model interpolation parameters used are summarised in Table 16-7.

Three progressive searches were used, such that if the conditions of the 1^st search were met for any particular block, then the grade would be interpolated with those samples. If not, the conditions would be relaxed for the 2^nd search criteria, and the procedure repeated. The 3^rd search was used only for those blocks a long way from any samples were interpolated, to ensure that all blocks defined as mineralised did receive grades and interpolated density values.

Table 16-7. Interpolation Parameters

	Search Distance (m)
				Minimum
	Along-	Down-	Cross-	No. of
Search	Strike	Dip	Strike	Composites
1st	30	30	5	3
2nd	60	60	10	2
3rd	150	150	25	1

Notes

1   Ellipsoidal search
2   Maximum of 20 composites
3  Max of 2 composites from each hole
4  Composites only used for the same parent zone
5  Inverse distance squared weighting used for Cu, Pb, Au, Ag and Density
6  For Zn, an indicator approach was used, based on a cut-off of 3%. Indicator variable determined using IPD.

The initial 30m search distance was determined from the geostatistical analysis. The small 5m cross-strike distance was selected due to the stratiform nature of the deposit. Zonal control was used, such that only composites belonging to the same zone could be used for

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interpolation inside that zone. Inverse distance (IPD) weighting (power 2) as well as kriging were tested, but on examination of resultant model sections and grade distributions, it was felt that the IPD-derived sections better reflected the drillhole grades, so IPD was used as the principal means of interpolation for the resource estimate.

Having interpolated metal grades, the resultant block NSR values were re-calculated, using the coefficients shown in Table 16-1. Model sections depicting variations metal grades and NSR values were checked in detail, against sample and composite data. Scaled model sections showing NSR variation, along with sample data, are shown in Appendix C.

A section through the western end, depicting zinc grade variation, is shown in Fig 16-8. This clearly shows the upper zinc-rich zone. The same section, depicting copper grade variation, is shown in Fig 10. This clearly shows the main lower copper-enriched stringer zone.

For the east end, sections showing the zinc and copper grade variation are shown in Figs 16-9 and 16-11, respectively. These show the reversal in metal zonation, as compared with the west end, with higher zinc grades on the footwall and higher copper grades towards the hanging wall. The zinc grades were interpolated using a reduced indicator method, using 3% as the key indicator cut-off level.

Example sections showing the resultant NSR values are shown in Figs 16-12 and 16-13, for the west and east ends, respectively.

Along with grade interpolation, blocks were allocated by resource class. The resource classification parameters used are summarised in Table 16-8. Indicated resources can only belong to the interpreted main zones, which have clear lateral continuity. Additional restrictions were placed on the allocation of indicated resources, such that for the interpolation in any block, at least 3 composites must have been found from at least 2 drillholes (within the 1^st 30m search), and of all the holes being utilised, at least 2 of them must have stemmed from the more recent NAN drilling.

Table 16-8. Resource Classification Parameters

Class	Criteria
	1. Must belong to interpreted principal main zones
Indicated	2. Based on on a search distance along-strike and down-dip of 30m, must have
	found at least three composites for interpolation, from at least two drillholes.
	3. Composites from at least two NAN holes must have been used
	1. Can belong to main zone, or outer peripheral zones.
Inferred
	2. Can use distances >30m, with no restrictions regarding NAN or SGU data.

The extent of the resultant indicated resources are shown in Fig 16-14. The inferred resources in the western end have been defined down to an elevation of -60m, and in the eastern end to an elevation of 70m.

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16.5 Validation

The most recent previous evaluation study for Norrliden, completed by ACA Howe in Jan 2000, produced the following 'overall' resource estimate, based on a cut-off of $20/t (applied to selected intercepts) of:

1,014 kt 6.15 % Zn 0.58 % Pb 0.89 % Cu 1.00 g/t Au 80.87 g/t Ag

At the applied (then estimated underground cost level) of $28/t, this gave the result:

774 kt 7.83 % Zn 0.74 % Pb 0.83 % Cu 1.18 g/t Au 100.43 g/t Ag

This resource estimate was limited to a depth of 176m (r.l.~54m). For the model produced in the current study, and also by limiting the depth to 176m, the evaluation (of all resource classes) at a cut-off of $20/t (SEK170/t at 2000 exchange rate and 2003 prices) yields:

1,223 kt 5.04 % Zn 0.48 % Pb 0.75 % Cu 0.84 g/t Au 67.91 g/t Ag

At the cut-off of $28/t (SEK240/t at 2000 exchange rates and 2003 prices), the evaluation is:

969 kt 5.88 % Zn 0.56 % Pb 0.73 % Cu 0.95 g/t Au 77.98 g/t Ag

These figures tend to indicate a dilution of approximately 20%, with respect to the former evaluation estimate. However, there are important differences between these alternative evaluation estimates, which should be considered when comparing figures the different evaluations. These differences include:

1.    The Howe estimate had no applied minimum width, although 1.4m was described as being the 'effective' minimum.

2.    It is not known precisely how the NSR values were calculated in the Howe estimate, and what assumptions (e.g. metal prices) were used.

3.    The Howe estimate was focussed on a potential underground resource, with corresponding higher cut-off grades from the outset.

4.    The Howe estimate was based completed using a cross-sectional approach. This will inherently tend to give lower tonnages at higher grades. For the Norrliden data set, there are also problems with a cross-sectional approach, as so many of the intercepts are so far off the regular 20m section lines.

5.    It is not known how density values were modelled or assumed in the Howe tonnage calculations.

For the estimates at both cut-off grades, if the overall SEK content is calculated (i.e. tonnes x SEK/t), the former and current evaluations are with 2% of each other, as summarised below:

Cut-Off $20/t
ACA Howe Evaluation	1,014 kt	453 SEK/t	460	MSEK
Current Evaluation	1,223 kt	376 SEK/t	460	MSEK
Cut-Off $28/t
ACA Howe Evaluation	774 kt	538 SEK/t	416	MSEK
Current Evaluation	969 kt	421 SEK/t	408	MSEK

This tends to suggest that the main difference with the revised evaluation is principally connected with the introduction of additional dilution.

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As well as examination of the block model sections, overlaid with drillhole data, as shown on Appendix D, a comparison was made of the average grades from the samples, composites and then the block model contents. These are shown in Table 16-9 below.

Table 16-9. Comparison of Average Grades

			Block Model - Main Zone
	Samples In	Composites
Field	Main Zone	in Main Zone	Indicated	Inferred
AU g/t	1.0	0.9	0.9	0.9
AG g/t	71.5	69.6	59.7	64.6
CU %	0.8	0.8	0.8	0.8
PB %	0.5	0.5	0.4	0.4
ZN %	5.4	5.4	4.9	4.4

This table shows that the average grades compare fairly favourably, in terms of progressing from samples to composites to the block model.

Local statistics were examined in the form of 'swath' plots, as shown below, which shows the average accepted Zn and Cu (derived from IPD) grades on each 5m bench (horizontal slice) through the block model, as compared to the average corresponding bench grades from derived by a nearest neighbour interpolation. These results are shown at a zero cut-off for just the indicated class material. In general, the IPD estimate grades follow the trend of the nearest neighbour grades, but have less pronounced peaks and troughs. These charts do not show any particular evidence of grade bias.

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16.6 Evaluation

Operating cost data for an underground mining study for Norriden (NAN, August, 2000) is shown below.

	Operating
	Cost
Activity	SEK/t
Mining	74.0
Hauling	31.9
ore loading
milling cost	70.0
dewater + reagents
conc transport	4.5
Reclamation	8.6
G&A	34.2
Marketing & Shipping	13.8
Total	236.9

In this 2000 study, and from the operating cost estimates shown above, a cut-off of approximately SEK240/t was applied, which at the time was equivalent to $28/t (8.6SEK=$1). The milling cost levels, in SEK, are still comparable to current cost levels for the mill at Boliden. If an open pit were being considered, the open pit mining cost would not be applied into the cut-off grade calculation (assuming the same cost for mining waste or ore). This would reduce the cut-off to around SEK160/t. When considering all the material that would be mined within an open pit, a marginal cut-off grade would also be required, in which certain fixed cost elements (already being borne by primary ore) would be discounted. This would reduce the cut-off still further to around SEK120/t. This has therefore been used as the cutoff level used in the current resource estimate. It has been chosen so as to quantify material that could potentially be considered as suitable for mill feed. Clearly, further cut-off grade analysis would be required for any more detailed mine planning studies.

Based on the resource classification system described in Section 5, the resultant block model was evaluated, giving the overall results shown in Table 16-10, pertaining to a block cut-off of SEK120/t. In this estimate, no additional dilution has been applied, but it pertains to a minimum width of 3m.

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Table 16-10. Resource Evaluation- Base Case Parameters

	Indicated
ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Main Zone	568	4.9	0.4	0.8	0.9	59.7	452
Peripheral Zones	-
Total	568	4.9	0.4	0.8	0.9	59.7	452
	Inferred
ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Main Zone	571	4.3	0.4	0.8	0.8	63.6	427
Peripheral Zones	378	3.4	0.4	0.8	0.6	52.2	355
Total	948	4.0	0.4	0.8	0.7	59.1	399
	Indicated + Inferred
ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Main Zone	1,138	4.6	0.4	0.8	0.9	61.7	440
Peripheral Zones	378	3.4	0.4	0.8	0.6	52.2	355
Total	1,516	4.3	0.4	0.8	0.8	59.3	419

Notes   . Based on block cut-off of SEK120/t

. NSR calculated using long-term base case prices:

	c/lb	c/lb	c/lb	$/oz	$/oz
	/%	/%	/%	/g/t	/g/t
	Zn	Pb	Cu	Au	Ag
Prices	60	33	120	450	6.5
Coefficients	46.31	20.77	143.21	54.41	0.94

The inferred resources, in the west end, go down to an elevation of -60m, which is considerably deeper than the previous evaluation. A breakdown of the resources, by elevation, is summarised in Table 16-11 (again for a cut-off of SEK120/t). This shows the majority of the indicated resources lie between elevations 130m and 200m.

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Table 16-11. Resource Breakdown - By Elevation

	Indicated							Inferred							Indicated + Inferred
Elev'n	Tons	Zn	Pb	Cu	Au	Ag	NSR	Tons	Zn	Pb	Cu	Au	Ag	NSR	Tons	Zn	Pb	Cu	Au	Ag	NSR
m	kt	%	%	%	g/t	g/t	SEK/t	kt	%	%	%	g/t	g/t	SEK/t	kt	%	%	%	g/t	g/t	SEK/t
-70	-							0	0.4	0.1	1.7	1.7	41.4	389	0.5	0.4	0.1	1.7	1.7	41.4	389
-60	-							4	1.0	0.2	1.5	1.7	42.3	392	4	1.0	0.2	1.5	1.7	42.3	392
-50	-							8	0.8	0.3	1.4	1.5	40.9	358	8	0.8	0.3	1.4	1.5	40.9	358
-40	-							10	0.5	0.2	1.3	1.4	38.3	319	10	0.5	0.2	1.3	1.4	38.3	319
-30	-							11	0.7	0.2	1.1	1.1	35.3	290	11	0.7	0.2	1.1	1.1	35.3	290
-20	-							13	0.5	0.2	1.0	0.9	31.4	249	13	0.5	0.2	1.0	0.9	31.4	249
-10	-							13	0.6	0.1	1.0	0.8	30.9	249	13	0.6	0.1	1.0	0.8	30.9	249
0	-							14	0.7	0.1	0.9	0.7	28.6	234	14	0.7	0.1	0.9	0.7	28.6	234
10	-							16	1.2	0.1	0.9	0.7	27.3	242	16	1.2	0.1	0.9	0.7	27.3	242
20	-							20	2.3	0.1	0.7	0.7	24.1	272	20	2.3	0.1	0.7	0.7	24.1	272
30	-							22	2.9	0.1	0.7	0.7	22.2	295	22	2.9	0.1	0.7	0.7	22.2	295
40	-							29	2.8	0.1	0.8	0.6	25.1	299	29	2.8	0.1	0.8	0.6	25.1	299
50	-							37	2.8	0.2	0.7	0.5	32.2	298	37	2.8	0.2	0.7	0.5	32.2	298
60	-							49	2.7	0.2	0.9	0.5	36.3	315	49	2.7	0.2	0.9	0.5	36.3	315
70	2	4.1	0.3	0.4	0.8	27.0	319	63	3.6	0.3	1.0	0.7	52.6	399	65	3.7	0.3	0.9	0.7	51.8	397
80	5	5.0	0.5	0.3	0.8	36.1	361	67	4.3	0.4	0.9	0.8	64.0	441	72	4.4	0.4	0.9	0.8	62.0	435
90	5	8.1	1.0	0.6	1.4	92.9	639	59	4.8	0.5	0.8	0.8	65.4	455	64	5.1	0.5	0.8	0.9	67.7	470
100	16	6.7	0.8	0.8	1.0	82.3	567	46	4.6	0.5	0.9	0.8	71.2	459	62	5.1	0.6	0.8	0.9	74.0	486
110	21	5.0	0.5	0.9	0.9	65.1	483	53	3.6	0.4	1.0	0.6	63.1	406	74	4.0	0.4	1.0	0.7	63.7	428
120	34	3.7	0.3	1.0	0.8	52.3	406	59	4.1	0.4	0.8	0.6	70.0	416	93	3.9	0.4	0.9	0.7	63.5	412
130	60	4.3	0.4	0.8	0.7	62.5	423	56	5.0	0.6	0.8	0.7	81.5	467	115	4.7	0.5	0.8	0.7	71.6	444
140	66	4.0	0.4	0.8	0.7	56.9	395	49	6.1	0.7	0.7	0.7	103.1	533	115	4.9	0.5	0.7	0.7	76.5	453
150	68	4.9	0.4	0.7	0.8	70.8	449	44	5.6	0.6	0.6	0.8	82.2	478	112	5.2	0.5	0.7	0.8	75.3	460
160	60	5.1	0.4	0.7	1.0	65.4	457	40	4.4	0.5	0.6	0.7	83.1	417	101	4.8	0.5	0.6	0.9	72.5	441
170	60	5.1	0.5	0.8	0.9	63.9	466	40	4.6	0.6	0.5	0.6	81.7	413	101	4.9	0.5	0.7	0.8	71.0	445
180	61	5.0	0.4	0.9	0.9	54.1	477	37	4.8	0.5	0.5	0.6	62.3	402	98	4.9	0.4	0.8	0.8	57.2	449
190	61	5.2	0.4	0.8	0.9	48.6	465	28	5.6	0.5	0.6	0.7	54.3	436	89	5.3	0.4	0.7	0.9	50.4	456
200	40	5.4	0.4	0.7	1.0	48.9	465	33	5.1	0.4	0.5	0.9	44.6	414	73	5.3	0.4	0.6	1.0	47.0	442
210	8	7.5	0.5	0.5	1.3	46.2	545	31	4.2	0.4	0.5	1.0	39.4	369	38	4.9	0.4	0.5	1.1	40.8	405
220	-							0	7.3	1.0	0.2	1.5	70.7	538	0.5	7.3	1.0	0.2	1.5	70.7	538
Total	568	4.9	0.4	0.8	0.9	59.7	452	948	4.0	0.4	0.8	0.7	59.1	399	1,516	4.3	0.4	0.8	0.8	59.3	419

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An alternative evaluation, based on the block model NSR values being determined from more optimistic (LOM) metal prices, is shown in Table 16-12 below.

Table 16-12. Resource Evaluation - Based On Alternative Economic (LOM) Scenario

	Indicated
ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Main Zone	568	4.9	0.4	0.8	0.9	59.7	663
Peripheral Zones	-
Total	568	4.9	0.4	0.8	0.9	59.7	663
	Inferred
ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Main Zone	574	4.3	0.4	0.8	0.8	63.4	623
Peripheral Zones	383	3.3	0.4	0.8	0.6	51.7	518
Total	956	3.9	0.4	0.8	0.7	58.7	581
	Indicated + Inferred
ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Main Zone	1,141	4.6	0.4	0.8	0.9	61.5	643
Peripheral Zones	383	3.3	0.4	0.8	0.6	51.7	518
Total	1,524	4.3	0.4	0.8	0.8	59.1	612

Notes   . Based on block cut-off of SEK120/t

. NSR calculated using long-term base case prices:

	c/lb	c/lb	c/lb	$/oz	$/oz
	/%	/%	/%	/g/t	/g/t
	Zn	Pb	Cu	Au	Ag
Prices	90	35	180	500	9
Coefficients	71.21	22.55	221.37	60.46	1.3

48 May 2006

Adam Wheeler Norrliden Resource Estimation

Grade-tonnage curves were also produced from the geological model, based on the base case metal prices. This information is shown for just indicated resources in Table 16-13, and for all resources in Table 16-14, with the corresponding grade-tonnage curves.

It is important to realise that these grade-tonnage relationship may not necessarily reflect a realistic mining selectivity. This issue requires further analysis in the consideration of mining methods during mine planning and reserve estimation.

Table 16-13. Grade-Tonnage Curve - Just Indicated Resources

		Average
		NSR
		Above
NSR Cut-Off	TONNES	Cut-Off	Zn	Pb	Cu	Au
SEK/t	kt	SEK/t	%	%	%	g/t
0	568	452	4.9	0.4	0.8	0.9
60	568	452	4.9	0.4	0.8	0.9
120	568	452	4.9	0.4	0.8	0.9
180	562	455	5.0	0.4	0.8	0.9
240	534	468	5.1	0.5	0.8	0.9
300	453	503	5.7	0.5	0.8	1.0
360	346	556	6.5	0.6	0.8	1.1
420	261	611	7.4	0.6	0.8	1.2
480	183	680	8.6	0.7	0.8	1.3
540	132	747	9.8	0.8	0.7	1.4
600	88	836	11.4	1.0	0.6	1.5
660	70	888	12.3	1.0	0.6	1.6
720	55	944	13.3	1.1	0.6	1.6
780	42	1001	14.3	1.2	0.5	1.6
840	35	1045	14.9	1.3	0.5	1.5
900	25	1112	15.8	1.6	0.5	1.3
960	17	1194	17.0	1.9	0.3	1.2
1020	14	1249	17.7	2.0	0.3	1.2

49 May 2006

Adam Wheeler Norrliden Resource Estimation

Table 16-14. Grade-Tonnage Table - All Resources

		Average
		NSR
		Above
NSR Cut-Off	Tonnes	Cut-Off	Zn	Pb	Cu	Au
SEK/t	kt	SEK/t	%	%	%	g/t
0	1,528	416	4.3	0.4	0.8	0.8
60	1,524	417	4.3	0.4	0.8	0.8
120	1,516	419	4.3	0.4	0.8	0.8
180	1,452	430	4.5	0.4	0.8	0.8
240	1,260	463	5.0	0.5	0.8	0.9
300	1,006	512	5.8	0.5	0.8	1.0
360	750	574	6.7	0.6	0.8	1.1
420	556	639	7.7	0.8	0.7	1.2
480	410	707	8.8	0.9	0.7	1.3
540	319	764	9.8	1.0	0.6	1.4
600	236	832	11.0	1.1	0.5	1.5
660	186	888	12.0	1.2	0.5	1.5
720	145	943	12.9	1.3	0.4	1.6
780	109	1009	13.9	1.5	0.4	1.6
840	87	1060	14.6	1.6	0.4	1.5
900	61	1142	15.9	1.8	0.4	1.4
960	41	1249	17.6	2.1	0.3	1.2
1020	31	1331	18.6	2.4	0.3	1.2

50 May 2006

Adam Wheeler Norrliden Resource Estimation

17 OTHER RELEVANT DATA AND INFORMATION

Specialists have provided more extensive descriptions of the environment surrounding Norrliden in specific reports. NAN retain an environmental consultancy, MFG, to monitor the environment. They commenced work in September 1999 and have completed a detailed review of the area around the deposit.

Adam Wheeler understands that preliminary work on the mining concession application (suspended at present) included: water sampling, site investigations, archaeological surveys and initial environmental surveys; and that to date nothing has been revealed that would preclude these resources being converted to reserves in due course.

Drilling and exploration of Norrliden have had little impact on the land surface except for minor damage to small trees and shrubs. Each of the borehole holes is marked by steel casing with an identifying number, which protrudes from the ground about one metre.

Exploration boreholes are now being used to sample and measure ground water conditions in the vicinity of the orebody. Prior to mining all boreholes will be filled with cement.

51 May 2006

Adam Wheeler Norrliden Resource Estimation

18 CONCLUSIONS AND RECOMMENDATIONS 18.1 Conclusions

1.    The Norrliden deposit contains potentially economic grades of zinc, copper, lead, gold and silver. Based on parameters associated with the nearby Boliden processing operations, as well as revised long-term metal prices, coefficients were determined, to enable the calculation of contained NSR values for both the sample and model data.

2.    There are two distinct zones of mineralization, in the west and east ends of the deposit area. For each of these main zones, sections were interpreted based on a cut-off of SEK120/t. This interpretation was also strongly controlled by previous geological interpretations completed by NAN (North Atlantic Resources).

3.    Stemming primarily from these main zones' interpretations, a block model was created. Additional peripheral blocks were also created outside of the main structures, based on sectional perimeters as well as three-dimensional projection from other intercepts.

4.    Metal grades were interpolated into the block model, using parameters supported by a geostatistical analysis of drillhole composites. This also enabled the definition of pertinent resource classification criteria, relating to search distances, numbers of drillholes and composites, as well as the source of drilling data.

5.    Resources were classified according to the JORC code. A summary of the resource evaluation is shown in the table below, based on a block cut-off of SEK120/t and a minimum mining width of 3m.

Resource Summary

ZONE	Tonnes	Zn	Pb	Cu	Au	Ag	NSR
	kt	%	%	%	g/t	g/t	SEK/t
Indicated	568	4.9	0.4	0.8	0.9	59.7	452
Inferred	948	4.0	0.4	0.8	0.7	59.1	399
Total	1,516	4.3	0.4	0.8	0.8	59.3	419

Notes   . Based on block cut-off of SEK120/t

. NSR calculated using long-term base case prices:

	Zn	Pb	Cu	Au	Ag
	c/lb	c/lb	c/lb	$/oz	$/oz
	/%	/%	/%	/g/t	/g/t
Prices	60	33	120	450	6.5
Coefficients	46.3	20.8	143.2	54.4	0.94

52 May 2006

Adam Wheeler Norrliden Resource Estimation

18.2 Recommendations

1.    In order to obtain a greater amount and proportion of indicated resources, further drilling would be required in the main zones, as well as further drilling on peripheries to reinforce the interpretation of peripheral zones.

2.    In order to be able to classify any of the deposit to a measured resource categorisation, further drilling would be required to obtain a closer sample spacing. In addition to this, the corresponding quality control on the resultant logging and assaying operations would need to be completed to a higher level.

3.    To allow any sort of reserve estimate, a mine planning study would be required, along with more detailed consideration of the required metallurgical processing and the corresponding economic parameters.

19 REFERENCES

A.C.A. Howe, 2000; Resource Audit, Norra Norrliden, Skelleftea, Sweden, January 2000, 10p.

Da Silva, J.,1999; Norra Norrliden: Assay Quality Control, November 1999.

Lindestrom L. 4/4/2001. Norrliden - Base Case Studies in The Surroundings Before and Regarding Planned Mining.

Micon international, 2000; Norrliden Development Concept (Draft), January 2000.

North Atlantic Natural Resources, 2000; Mining Licence Application for the Norrliden Deposit (Draft), August 2000.

North Atlantic Natural Resources, 2001. Description of project and environmental aspects.

Wheeler, A., 2006; Norrliden Resource Estimate, April 2006, 16p.

Wheeler, A., 2005; Technical Report on the Storliden Mine, Sweden, February 2005. Lundin Mining. Technical Report filed on SEDAR (www.sedar.com) on March 31, 2005, 56p.

20 DATE AND SIGNATURE PAGE

Adam Wheeler     

Date            May 30^th, 2006                       

53 May 2006

Adam Wheeler Norrliden Resource Estimation

CERTIFICATE

To accompany the Report titled
"Technical Report on the Norrliden Resource Estimation, Sweden"

dated May 30th, 2006

I, Adam Wheeler, do hereby certify that:

1.    I reside at Cambrose Farm, Redruth, Cornwall, England, TR16 4HT

2.    I am a graduate from the Camborne School of Mines with a B.Sc. in Mining, as well as from Queens' University in Canada with an M.Sc. in Mining Engineering and I have practised my profession continuously since that time.

3.    I am a member of the Institute of Materials, Minerals and Mining.

4.    I am a Qualified Person for the purposes of NI 43-101 with regard to a variety of mineral deposits and have knowledge and experience with Mineral Reserve and Mineral Resource estimation parameters and procedures and those involved in the preparation of technical studies.

5.    I visited the Norrliden property on May 22, 2006 and have reviewed all of the technical data regarding the property as provided by Lundin. I prepared all sections of this report.

6.    I have no personal knowledge as of the date of this certificate of any material fact or change, which is not reflected in this report.

7.    Neither I, nor any affiliated entity of mine, is at present, under an agreement, arrangement or understanding or expects to become, an insider, associate, affiliated entity or employee of Lundin Mining Corporation or any associated or affiliated entities.

8.    Neither I, nor any affiliated entity of mine own, direct or indirectly, nor expect to receive, any interest in the properties or securities of Lundin Mining Corporation, or any associated or affiliated companies.

9.    Neither I, nor any affiliated entity of mine, have earned the majority of our income during the preceding three years from Lundin Mining Corporation or any associated or affiliated companies.

- 2 -

10.   I have read NI 43-101 and Form 43-101F1 and have prepared this report in compliance with NI 43-101 and Form 43-101F1, and have prepared the report in conformity with generally accepted Canadian mining industry practice.

signed by

Adam Wheeler, C.Eng., Eur.Ing

Consulting Mining Engineer

July 6th, 2006

APPENDIX A

NORRLIDEN STATISTICAL PLOTS

By

Adam Wheeler

April 2006

Adam Wheeler,
Mining Consultant,
Cambrose Farm,
Redruth,
Cornwall, TR16 4HT,
England.
Tel/Fax: (44) 1209-890733
E-mail : adamwheeler@btinternet.com

Norrliden - Statistical Plots 1

A. Wheeler April 2006

Norrliden - Statistical Plots 2

A. Wheeler April 2006

Norrliden - Statistical Plots 3

A. Wheeler April 2006

Norrliden - Statistical Plots 4

A. Wheeler April 2006

Norrliden - Statistical Plots 5

A. Wheeler April 2006

APPENDIX B

NORRLIDEN
DECILE
ANALYSES

By

Adam Wheeler

April 2006

Adam Wheeler,
Mining Consultant,
Cambrose Farm,
Redruth,
Cornwall, TR16 4HT,
England.
Tel/Fax: (44) 1209-890733
E-mail : adamwheeler@btinternet.com

Norrliden - Decile Analyses 1

Zinc - Decile Analysis

% Quantile		No. of	Mean	Minimum	Maximum	Metal	%
From	To	Samples	Grade	Grade	Grade	Content	Metal
0	10	57	0.02	0.01	0.03	1	0.0
10	20	57	0.04	0.03	0.06	2	0.1
20	30	57	0.08	0.06	0.1	5	0.2
30	40	58	0.2	0.1	0.28	9	0.3
40	50	57	0.6	0.3	0.9	38	1.4
50	60	57	1.7	0.9	2.5	95	3.5
60	70	58	3.4	2.5	4.7	204	7.5
70	80	57	6.9	4.7	9.0	379	13.9
80	90	57	12.5	9.2	15.7	684	25.1
90	100	58	22.3	15.9	41.7	1,308	48.0
90	91	5	15.9	15.9	16.0	78	2.9
91	92	6	16.4	16.0	16.6	111	4.1
92	93	6	17.4	16.7	18.2	93	3.4
93	94	6	19.3	18.6	20	145	5.3
94	95	6	20.4	20.2	20.8	93	3.4
95	96	5	21.4	21	22.6	96	3.5
96	97	6	23.7	22.6	24.8	136	5.0
97	98	6	26.1	25.4	27.3	199	7.3
98	99	6	28.4	27.8	29.8	180	6.6
99	100	6	33.0	29.8	41.7	177	6.5
0	100	573	4.8	0.01	41.7	2,725	100.0
Copper - Decile Analysis
% Quantile		No. of	Mean	Minimum	Maximum	Metal	%
From	To	Samples	Grade	Grade	Grade	Content	Metal
0	10	57	0.01	0.00	0.02	0	0.1
10	20	57	0.03	0.02	0.04	1	0.3
20	30	57	0.06	0.04	0.08	2	0.5
30	40	58	0.12	0.08	0.17	7	1.6
40	50	57	0.24	0.17	0.32	15	3.4
50	60	57	0.4	0.3	0.5	28	6.3
60	70	58	0.6	0.5	0.8	34	7.6
70	80	57	1.0	0.8	1.2	63	14.3
80	90	57	1.4	1.2	1.8	93	21.1
90	100	58	2.9	1.8	6.6	199	44.9
90	91	5	1.8	1.8	1.8	12	2.7
91	92	6	2.0	1.9	2.0	12	2.7
92	93	6	2.1	2.07	2.2	14	3.1
93	94	6	2.3	2.23	2.28	16	3.6
94	95	6	2.4	2.32	2.42	18	4.1
95	96	5	2.7	2.53	2.85	18	4.2
96	97	6	3.0	2.86	3.19	13	2.9
97	98	6	3.5	3.23	3.65	30	6.8
98	99	6	4.1	3.7	4.43	33	7.4
99	100	6	5.3	4.47	6.56	33	7.4
0	100	573	0.8	0	6.56	443	100.0

A. Wheeler April 2006

Norrliden - Decile Analyses 2

Lead - Decile Analysis

% Quantile		No. of	Mean	Minimum	Maximum	Metal	%
From	To	Samples	Grade	Grade	Grade	Content	Metal
0	10	57	0.00	0.00	0.00	-	0.0
10	20	57	0.01	0.00	0.01	1	0.3
20	30	57	0.01	0.01	0.01	0	0.2
30	40	57	0.02	0.01	0.02	1	0.4
40	50	58	0.03	0.02	0.04	2	0.7
50	60	57	0.05	0.04	0.08	3	1.2
60	70	57	0.11	0.08	0.18	6	2.3
70	80	57	0.3	0.2	0.6	19	7.6
80	90	57	0.9	0.6	1.4	54	21.1
90	100	58	2.9	1.4	7.8	171	66.4
90	91	5	1.5	1.4	1.5	6	2.2
91	92	6	1.6	1.6	1.7	8	3.1
92	93	6	1.8	1.69	1.93	14	5.3
93	94	6	2.0	1.94	2.09	15	5.8
94	95	6	2.3	2.09	2.41	11	4.3
95	96	5	2.7	2.53	2.88	14	5.5
96	97	6	3.1	3.06	3.21	16	6.2
97	98	6	3.5	3.26	3.88	24	9.2
98	99	6	4.6	4.01	5.21	35	13.5
99	100	6	6.1	5.21	7.77	29	11.1
0	100	572	0.5	0	7.77	257	100.0
Gold - Decile Analysis
% Quantile		No. of	Mean	Minimum	Maximum	Metal	%
From	To	Samples	Grade	Grade	Grade	Content	Metal
0	10	56	0.01	0.00	0.02	0	0.1
10	20	57	0.06	0.02	0.10	3	0.5
20	30	56	0.13	0.10	0.19	7	1.3
30	40	57	0.25	0.19	0.30	16	3.1
40	50	57	0.37	0.31	0.44	20	3.8
50	60	56	0.5	0.4	0.6	35	6.5
60	70	57	0.8	0.6	0.9	43	8.1
70	80	56	1.0	0.9	1.2	59	10.9
80	90	57	1.5	1.2	2.0	95	17.6
90	100	57	4.8	2.0	44.6	259	48.2
90	91	5	2.1	2.0	2.1	12	2.3
91	92	6	2.2	2.1	2.3	19	3.6
92	93	6	2.5	2.37	2.51	15	2.8
93	94	5	2.7	2.51	2.76	16	2.9
94	95	6	3.1	2.95	3.25	13	2.5
95	96	6	3.5	3.28	3.61	20	3.7
96	97	5	4.0	3.61	4.35	13	2.5
97	98	6	4.7	4.48	4.83	16	3.0
98	99	6	5.4	4.89	7	31	5.8
99	100	6	18.6	9.5	44.6	103	19.2
0	100	566	1.0	0.002	44.6	537	100.0

A. Wheeler April 2006

Norrliden - Decile Analyses 3

Silver - Decile Analysis

% Quantile		No. of	Mean	Minimum	Maximum	Metal	%
From	To	Samples	Grade	Grade	Grade	Content	Metal
0	10	57	1.06	0.3	2.0	48	0.1
10	20	57	4.18	2.0	6.6	182	0.5
20	30	57	8.57	6.8	10.2	437	1.2
30	40	57	12.85	10.3	15.3	835	2.3
40	50	58	19.67	15.6	24.1	1,215	3.3
50	60	57	29.0	24.1	36.7	1,899	5.2
60	70	57	44.9	36.9	57.1	2,625	7.1
70	80	57	69.6	58.5	82.7	3,962	10.8
80	90	57	112.3	83.1	142.0	6,944	18.9
90	100	58	326.0	144.0	1280.0	18,675	50.7
90	91	5	150	144	153	813	2.2
91	92	6	159	153	165	956	2.6
92	93	6	176	165	187	690	1.9
93	94	6	203	192	219	1,080	2.9
94	95	6	231	220	238	1,201	3.3
95	96	5	251	242	266	1,187	3.2
96	97	6	286	275	294	2,119	5.8
97	98	6	364	305	402	2,300	6.2
98	99	6	480	411	538	3,666	10.0
99	100	6	875	564	1,280	4,664	12.7
0	100	572	65	0	1,280	36,822	100.0

A. Wheeler April 2006

APPENDIX C

NORRLIDEN RESOURCE
ESTIMATE
-
MODEL SECTIONS

By

Adam Wheeler

April 2006

Adam Wheeler,
Mining Consultant,
Cambrose Farm,
Redruth,
Cornwall, TR16 4HT,
England.
Tel/Fax: (44) 1209-890733
E-mail : adamwheeler@btinternet.com

APPENDIX D

NORRLIDEN RESOURCE
ESTIMATE

TWIN HOLE SECTIONS

By

Adam Wheeler

May 2006

Adam Wheeler,
Mining Consultant,
Cambrose Farm,
Redruth,
Cornwall, TR16 4HT,
England.
Tel/Fax: (44) 1209-890733
E-mail : adamwheeler@btinternet.com

Norrliden - Twin Hole Sections 1

A. Wheeler April 2006

Norrliden - Twin Hole Sections 2

A. Wheeler April 2006

Norrliden - Twin Hole Sections 3

A. Wheeler April 2006

Norrliden - Twin Hole Sections 4

A. Wheeler April 2006

Norrliden - Twin Hole Sections 5

A. Wheeler April 2006

Norrliden - Twin Hole Sections 6

A. Wheeler April 2006