U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2010–5090–J

Global Mineral Resource Assessment

Descriptive Models, Grade-Tonnage Relations, 

and Databases for the Assessment of SedimentHosted Copper Deposits—With Emphasis on 

Deposits in the Central African Copperbelt, 

Democratic Republic of the Congo and Zambia
This page intentionally left blank.
Global Mineral Resource Assessment

Descriptive Models, Grade-Tonnage 

Relations, and Databases for the 

Assessment of Sediment-Hosted Copper 

Deposits—With Emphasis on Deposits in 

the Central African Copperbelt, Democratic 

Republic of the Congo and Zambia

Scientific Investigations Report 2010–5090–J

U.S. Department of the Interior

U.S. Geological Survey

Michael L. Zientek, Jane M. Hammarstrom, and Kathleen M. Johnson, editors

By Cliff D. Taylor, J. Douglas Causey, Paul D. Denning, Jane M. Hammarstrom, 

Timothy S. Hayes, John D. Horton, Michael J. Kirschbaum, Heather L. Parks, 

Anna B. Wilson, Niki E. Wintzer, and Michael L. Zientek
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

For more information on the USGS—the Federal source for science about the Earth,

its natural and living resources, natural hazards, and the environment—

visit http://www.usgs.gov or call 1–888–ASK–USGS

For an overview of USGS information products, including maps, and publications,

visit http://www.usgs.gov/pubprod

Suggested citation:

Taylor, C.D., Causey, J.D., Denning, P.D., Hammarstrom, J.M., Hayes, T.S., Horton, J.D., Kirschbaum, M.J., Parks, H.L., 

Wilson, A.B., Wintzer, N.E., and Zientek, M.L., 2013, Descriptive models, grade-tonnage relations, and databases for 

the assessment of sediment-hosted copper deposits—With emphasis on deposits in the Central African Copperbelt, 

Democratic Republic of the Congo and Zambia: U.S. Geological Survey Scientific Investigations Report 2010–5090–J, 

154 p. and data files. 

Any use of trade, firm, or product names is for descriptive purposes 

only and does not imply endorsement by the U.S. Government.

Although this information product, for the most part, is in the public domain, it also may contain 

copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be 

secured from the copyright owner. 
iii

Contents

Abstract...........................................................................................................................................................1

Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted 

Stratabound Copper Deposits........................................................................................................2

 Introduction.................................................................................................................................................2

 Concise Description ..................................................................................................................................2

Synonyms...............................................................................................................................................2

Commodities (byproducts) ..................................................................................................................2

Importance.............................................................................................................................................2

Associated Deposit Types ...................................................................................................................2

Ore System Components .....................................................................................................................2

Permissive Tract Delineation..............................................................................................................3

Selected References............................................................................................................................3

 Detailed Description..................................................................................................................................3

Types of Sediment-Hosted Stratabound Copper Deposits ............................................................3

Global Distribution ................................................................................................................................3

Regional Geologic Setting and Age Distribution .............................................................................3

Tectonic Settings .........................................................................................................................3

Depositional Environment ..........................................................................................................4

Age Range.....................................................................................................................................4

Timing of Mineralization..............................................................................................................4

Characteristics of Sediment-Hosted Stratabound Copper Deposits ...........................................4

Dimensions....................................................................................................................................4

Host Rocks ....................................................................................................................................5

Structural Control ........................................................................................................................5

Ore Mineralogy.............................................................................................................................5

Ore Textures..................................................................................................................................5

Ore Mineral Zonation ..................................................................................................................5

Hypogene Gangue Minerals ....................................................................................................13

Hypogene Alteration .................................................................................................................13

Weathering and Supergene Ore .............................................................................................13

Geochemical Guides ..........................................................................................................................13

Geophysical Guides............................................................................................................................13

Genesis.................................................................................................................................................14

Exploration and Resource Assessment Guides.............................................................................14

Copper Source Rocks ...............................................................................................................14

Brines...........................................................................................................................................14

Fluid Flow and Pathways..........................................................................................................14

Organic Matter...........................................................................................................................15

Confining Beds and Containment Structures........................................................................15

 Acknowledgments..............................................................................................................................15
iv

 Glossary................................................................................................................................................16

Chapter 2. Grade and Tonnage Relations for Sediment-Hosted 

Stratabound Copper Deposits......................................................................................................17

 Introduction..........................................................................................................................................17

 Definition of SSC Deposit Types .......................................................................................................17

 Reduced-Facies—Nonbrecciated (n.b.) Deposits....................................................................19

 Reduced-Facies—Carbonate Écaille Deposits .........................................................................23

 Sandstone Copper Deposits .........................................................................................................23

 Deposit Definition................................................................................................................................23

 Mineral Endowment .......................................................................................................................32

 Cutoff Grade.....................................................................................................................................32

 Exploration .......................................................................................................................................32

 Spatial Rules for Aggregation.......................................................................................................32

 Data Quality Assessment...................................................................................................................33

 Exploratory Data Analysis .................................................................................................................33

 Grade and Tonnage Model for Sediment-Hosted Stratabound Copper Deposits....................36

 Grade and Tonnage Model for Sediment-Hosted Stratabound Copper Deposits in the 

Central African Copperbelt..................................................................................................36

 Grade and Tonnage Model for Reduced-Facies—Nonbrecciated (n.b.) Deposits .............36

 Grade and Tonnage Model for Reduced-Facies—Carbonate Écaille Deposits...................41

 Grade and Tonnage Model for Sandstone Copper Deposits...................................................44

 Grade and Tonnage Model for Sandstone Copper—Roan Arenite........................................44

 Missing Data........................................................................................................................................51

 Silver.................................................................................................................................................51

 Cobalt................................................................................................................................................54

 Relations Among Surface Area, Tonnage, and Contained Copper.............................................55

 Equations for Sandstone Copper Deposits.................................................................................55

 Equations for Reduced-Facies—Carbonate Écaille Deposits ................................................55

 Discussion and Conclusions.............................................................................................................56

 Acknowledgments..............................................................................................................................58

Chapter 3. Sediment-Hosted Structurally Controlled Replacement and 

Vein Copper Deposits in the Central African Copperbelt, 

Democratic Republic of the Congo and Zambia .......................................................................60

 Introduction..........................................................................................................................................60

 Concise Description ...........................................................................................................................60

 Commodities (byproducts) ............................................................................................................60

 Importance.......................................................................................................................................60

 Associated Deposit Types .............................................................................................................63

 Distribution.......................................................................................................................................63

 Age Range.........................................................................................................................................63

 Representative Deposits in the CACB.............................................................................................63

 Kansanshi, Zambia..........................................................................................................................63

 Kalengwa, Zambia ..........................................................................................................................70

 Dikulushi, DRC .................................................................................................................................70

 Kikonkula, DRC ................................................................................................................................72
v

 Kapulo Area, DRC............................................................................................................................72

 Frontier, DRC....................................................................................................................................72

 Kipoi Project Area, DRC.................................................................................................................74

Kipoi Central................................................................................................................................74

Kileba .........................................................................................................................................76

 Lonshi, DRC......................................................................................................................................76

 Tilwezembe, DRC.............................................................................................................................77

 Other SCRV Deposits and Occurrences ........................................................................................77

 Cashin, Colorado, United States...................................................................................................79

 General Characteristics of SCRV Copper Deposits .....................................................................81

 Dimensions.......................................................................................................................................81

 Host Rocks .......................................................................................................................................81

 Ore Controls.....................................................................................................................................81

 Mineralogy.......................................................................................................................................83

 Alteration and Weathering............................................................................................................83

 Geochemical Signature .................................................................................................................83

 Geophysical Signature...................................................................................................................83

 Genesis................................................................................................................................................83

 Exploration and Resource Assessment Guidelines for SCRV Deposits ...................................83

 Grade and Tonnage Models for SCRV Deposits ...........................................................................84

 Acknowledgments.............................................................................................................................84

References Cited (Chapters 1, 2, and 3)...................................................................................................86

Appendix A. Relational Database of Sediment-Hosted Copper Deposits, 

Resources, and Production in the Central African Copperbelt, 

Democratic Republic of the Congo and Zambia .....................................................................103

 Introduction.......................................................................................................................................103

 Data Discussion and Methodology...............................................................................................103

 Comparison of Total Endowment with Previously Published Values ......................................108

 Sources of Information ...................................................................................................................108

 Database Design..............................................................................................................................108

 Tables..............................................................................................................................................109

Data Tables ...............................................................................................................................109

Look-up Tables .........................................................................................................................113

Junction Tables ........................................................................................................................115

Internally Generated Table for Switchboard.......................................................................115

 Queries............................................................................................................................................115

Deposit_SumTons_qry Query ................................................................................................121

Deposit_TonsxGrade_qry Query ...........................................................................................121

Deposit_SumGradexTons_qry Query ...................................................................................121

Deposit_WgtAvg_qry Query ..................................................................................................121

Queries and Calculations Performed on Groups of Deposits...........................................121

Group_SumTons_qry Query ...................................................................................................121

Group_TonsxGrade_qry Query ..............................................................................................128

Group_SumGradexTons_qry Query ......................................................................................128
vi

Group_WgtAvg_qry Query .....................................................................................................128

Queries Used to Provide Lists of References .....................................................................128

DepRef_qry Query ...................................................................................................................128

ResRef_qry Query....................................................................................................................128

 Forms..............................................................................................................................................128

Database Identification ..........................................................................................................128

Splashscreen Form..................................................................................................................128

Switchboard Form ...................................................................................................................128

1_Deposittbl_frm Form............................................................................................................128

2_Resourcestbl_frm Form ......................................................................................................128

Deposit_WgtAvg_qry_subform Form...................................................................................128

Source Reference Forms........................................................................................................129

DepRef_MM_Subform Form and ResRef_MM_Subform form........................................129

 Macros............................................................................................................................................129

 Users’ Guide.........................................................................................................................................129

 How to use the Access Database..............................................................................................129

Open Access Database ..........................................................................................................129

Browse Database ....................................................................................................................138

Identification Information in 1_Deposittbl_frm...................................................................139

Resource Information in 2_Resourcestbl_frm and 1_Deposits_frm...............................139

Reference Information............................................................................................................139

Calculating Resource Endowments......................................................................................139

Print Records............................................................................................................................139

 Frequently Asked Questions (FAQs) ................................................................................................139

 Acknowledgments..............................................................................................................................143

 References Cited ................................................................................................................................144

Appendix B. Spatial Databases for Sediment-Hosted Stratabound and Structurally Controlled 

Replacement and Vein Copper Deposits and Prospects, Central African Copperbelt, 

Democratic Republic of the Congo and Zambia .....................................................................145

 Introduction..........................................................................................................................................145

 Overview of Spatial Databases ........................................................................................................145

 Deposits and Prospects...............................................................................................................145

 Ore Bodies......................................................................................................................................149

 Open-Pit Mines..............................................................................................................................149

 Acknowledgments..............................................................................................................................154

 References Cited.................................................................................................................................154

Figures 

 1-1. Index maps showing the global distribution of sedimentary rocks 

 hosting sediment-hosted stratabound copper deposits......................................................6 

 1-2. Stratigraphic columns showing the position of reduced-facies 

 type copper mineralization ........................................................................................................8
vii

 1-3. Stratigraphic columns showing the position of sandstone-type 

 copper mineralization............................................................................................................10

 2-1. Distribution of log-transformed values for copper grade of 

 sediment-hosted copper deposits.......................................................................................18

 2-2. Chart illustrating the relations among types of sediment-hosted 

 copper deposits.......................................................................................................................18

 2-3. Variation in log ore, tonnage, and log copper grade by 

 basin for reduced-facies copper deposits..........................................................................20

 2-4. Variation in log ore, tonnage, and log copper grade by 

 basin for sandstone copper deposits ..................................................................................21

 2-5. Distribution of log-transformed values of copper grade 

 and ore tonnage between the sediment-hosted 

 stratabound copper deposits in the Central African 

 Copperbelt and all other areas in the world .......................................................................22

 2-6. Map showing the distribution of the Ore Shale Formation 

 of the Roan Group in Zambia.................................................................................................24

 2-7. Stratigraphic column of the Roan Group exposed in 

 the Zambian portion of the Central African Copperbelt....................................................25

 2-8. Stratigraphic column of the Katangan system, illustrating 

 the location of mineralized strata.........................................................................................26

 2-9. Stratigraphic columns showing distribution of 

 reduced-facies-carbonate écaille copper mineralization 

 in the Mines Subgroup ..........................................................................................................27

 2-10. Map and cross section of the Kamoto-Oliveira-Virgule 

 (KOV) ore body........................................................................................................................28

 2-11. Map of the Tenke-Fungurume area showing exposures 

 of Roan gigabreccia and megabreccia in the 

 Central African Copperbelt...................................................................................................29

 2-12. Stratigraphic column of the Roan Group exposed 

 in the Zambian part of the Central African Copperbelt 

 showing the stratigraphic distribution of reduced-facies 

 (argillite-hosted and mixed argillite-arenite) and 

 sandstone (arenite-hosted) mineralization........................................................................30

 2-13. Distribution of distance and log (distance) between the edges 

 of sediment-hosted copper ore bodies/open pits in the 

 Central African Copperbelt...................................................................................................34

 2-14. Bivariate plot of ore tonnage versus ore body area, 

 projected to the surface........................................................................................................34

 2-15. Bivariate plots of log copper grade versus log ore, 

 in metric tons...........................................................................................................................35

 2-16. Distribution of log-transformed values for tonnage, 

 grade, and contained copper of 170 sediment-hosted 

 stratabound copper deposits ...............................................................................................39

 2-17. Cumulative frequency plots of grade and tonnage for 

 170 sediment-hosted stratabound copper deposits..........................................................40

 2-18. Distribution of log-transformed values for tonnage, grade, 

 and contained copper of 77 sediment-hosted stratabound copper 

 deposits in the Central African Copperbelt........................................................................42
viii

 2-19. Cumulative frequency plots of grade and tonnage for 77 

 sediment-hosted stratabound copper deposits in the 

 Central African Copperbelt...................................................................................................43

 2-20. Distribution of log-transformed values for tonnage, 

 grade, and contained copper of 50 reduced-facies—n.b. 

 copper deposits......................................................................................................................44

 2-21. Cumulative frequency plots of grade and tonnage for 50 

 reduced-facies—n.b. copper deposits ..............................................................................45

 2-22. Distribution of log-transformed values for tonnage, grade, 

 and contained copper of 50 reduced-facies—carbonate-écaille 

 copper deposits......................................................................................................................46

 2-23. Cumulative frequency plots of grade and tonnage for 

 50 reduced-facies—carbonate-écaille deposits..............................................................47

 2-24. Graph showing the variation of copper grade by year for 

 6 for sediment-hosted stratabound copper deposits in the 

 Central African Copperbelt...................................................................................................48

 2-25. Distribution of surface area of Roan gigabreccia 

 fragments on the Likasi and Kolwezi geologic maps .......................................................49

 2-26. Surface area of Roan gigabreccia fragments on the 

 Likasi and Kolwezi geologic maps.......................................................................................49

 2-27. Distribution of log-transformed values of ore tonnage, 

 copper grade, cobalt grade, and contained copper of 

 reduced-facies—carbonate écaille deposits in different 

 tectonic settings, Central African Copperbelt...................................................................50

 2-28. Distribution of log-transformed values for tonnage, grade, 

 and contained copper of 70 sandstone copper deposits ................................................51

 2-29. Cumulative frequency plots of grade and tonnage 

 for 50 sandstone deposits.....................................................................................................52

 2-30. Distribution of log-transformed values for tonnage, grade, 

 and contained copper of 20 sandstone copper—Roan 

 arenite deposits......................................................................................................................53

 2-31. Cumulative frequency plots of grade and tonnage for 

 sandstone copper—Roan arenite deposits.......................................................................53

 2-32. Graphs showing the relative value of metal prices with time ...........................................54

 2-33. Bivariate graphs of ore body area plotted against ore 

 tonnage and contained copper metal for sediment-hosted 

 stratabound copper deposits ...............................................................................................56

 2-34. Bivariate graphs of ore body area plotted against ore tonnage 

 and contained copper metal for sandstone copper deposits.........................................57

 2-35. Bivariate graphs of ore body area plotted against ore tonnage 

 and contained copper metal for reduced-facies—carbonate-écaille 

 copper deposits......................................................................................................................58

 2-36. Box plots, normal quantile plots, and comparison circles for 

 log-transformed values of ore, metric tons, copper grade, and 

 contained copper illustrating differences between reduced 

 facies—carbonate-écaille, reduced-facies—n.b., and 

 sandstone copper deposits ..................................................................................................59

 3-1. Map showing the geology and major tectonic features of the 

 Central African Copperbelt...................................................................................................61
ix

 3-2. Stratigraphic nomenclature and stratigraphy of the Katanga 

 Supergroup throughout the Central African Copperbelt .................................................62

 3-3. Index map showing the distribution of structually controlled 

 replacement and vein deposits and prospects in the 

 Central African Copperbelt...................................................................................................67

 3-4. Kansanshi mine, Zambia ..........................................................................................................68

 3-5. Map and cross-section of the Dikulushi structually controlled 

 replacement and vein deposit..............................................................................................71

 3-6. Map showing location of deposits in the Kapulo area and their 

 distribution along the Kapulo Fault......................................................................................73

 3-7. Simplified geological map of the Kipoi Central deposit ......................................................75

 3-8. Geologic map of the Lonshi deposit.......................................................................................78

 3-9. Generalized stratigraphic section of southeastern Utah and 

 southwestern Colorado.........................................................................................................80

 3-10. Map showing fault patterns in the Cashin Mine area........................................................ 81

 3-11. Northwest-southeast cross section perpendicular to 

 the Cashin Fault showing the distribution of copper........................................................82

 3-12. Distribution of log-transformed values for tonnage and 

 copper grade for 11 structurally controlled replacement 

 and vein copper deposits......................................................................................................85

 3-13. Cumulative frequency plots of grade and tonnage for 

 11 structurally controlled replacement and vein copper deposits ................................85

 A1. Relations among the 11 Access data tables ....................................................................119

A2. List of tables in the database ..............................................................................................120

A3. Deposit_SumTons_qry query design view and SQL........................................................123

 A4. Deposit_TonsxGrade_qry query design view and SQL ..................................................124

A5. Deposit_SumGradexTons_qry query design view and SQL...........................................125

A6. Deposit_WgtAvg_qry query design view and SQL..........................................................126

A7. Group_SumTons_qry query design view and SQL...........................................................127

A8. Group_TonsxGrade_qry query design view and SQL......................................................130

A9. Group_SumGradexTons_qry query design view and SQL..............................................131

A10. Group_WgtAvg_qry query design view and SQL.............................................................132

A11. DepRef_qry query design view and SQL...........................................................................133

A12. ResRef_qry query design view and SQL ...........................................................................134

A13. View of the splashscreen form ...........................................................................................135

A14. View of the switchboard form showing data entry and query options ........................135

A15. Form view of the deposit data-entry form.........................................................................136

A16. View of the resource data-entry form 2_Resourcestbl_frm ..........................................137

A17. View of the deposit tonnage and grade form, Deposit_WgtAvg_qry_subform..........137

A18. View of the deposit references form DepRef_MM_Subform........................................137

A19. View of the resources references form ResRef_MM_Subform ...................................138

A20. Design View of the macro Macro1.....................................................................................138

A21. Deposit entry form, 1_Deposittbl_frm................................................................................140

A22. Upper part of data entry form, 1_Deposit_frm .................................................................141

A23. Lower part of the main 1_Deposittbl_frm..........................................................................141

A24. Record for the Konkola Deposit..........................................................................................142
x

B1. Map showing deposits, grouped deposits, ore bodies, 

 and open pits in the northwestern part of the Central African 

 Copperbelt in the Democratic Republic of the Congo..................................................146

B2. Landsat image showing the areal extent of ore bodies and 

 open pits in the northwestern part of the Central African Copperbelt 

 in the Democratic Republic of the Congo ......................................................................147

 B3. Landsat image showing deposits, grouped deposit, and areal 

 extent of ore bodies for the Konkola-Mutoshi area in the 

 Central African Copperbelt in the Democratic Republic of 

 the Congo and Zambia .......................................................................................................148

Tables

1-1. Copper minerals in sediment-hosted stratabound 

 copper (SSC) deposits...........................................................................................................4

1-2. Representative examples of sediment-hosted stratabound 

 copper deposits....................................................................................................................12

2-1. Tonnage and grade information for sediment-hosted 

 stratabound copper deposits Title doesn’t appear 

 on file copy for this table (This table is on line only) 

2-2. Sediment-hosted stratabound copper deposits containing 

 more than two million metric tons of copper...................................................................31

2-3. Summary statistics for sediment-hosted stratabound 

 copper deposits....................................................................................................................37

2-4. Goodness of fit statistics for sediment-hosted 

 copper deposit types ...........................................................................................................38

2-5. Numbers of deposits reporting cobalt and silver, 

 by deposit type......................................................................................................................38

2-6. Summary of tonnage and grade distributions for 

 sediment-hosted stratabound copper deposits recommendations 

 for their use in resource modeling ....................................................................................41

2-7. Comparison of grades of oxidized ore formed on 

 reduced-facies—carbonate écaille subtype deposits mined early in 

 the 20th century with grades reported for the same deposit 

 area in this compilation.......................................................................................................48

3-1. Selected characteristics of sediment-hosted copper deposits......................................64

3-2. Structurally controlled replacement and vein deposits in 

 the Central African Copperbelt ..........................................................................................66

3-3. Summary statistics for tonnage and grade of structurally controlled 

 replacement and vein copper deposits............................................................................85

A1. Summary of grade, tonnage, and total endowment 

 (pre-mining) of the sediment-hosted copper deposits of the 

 Central African Copper and Vein ......................................................................................104

A2. Comparison of copper production and total copper 

 endowment with previously reported values ................................................................109

A3. List and description of files in the database ....................................................................110

A4. Source tables, queries, and fields for data displayed on 

 the forms as well as any controls or type of data that should be entered ...............111
xi

A5. Design and table structure of mineral deposits data table, 1_Deposittbl...................112

A6. Design and table structure of mineral resources data table, 2_Resourcestbl ..........114

A7. Design and table structure of reference data table, 3_Referencetbl..........................114

A8. Structure and content of deposit-type look-up table, 

 DepositType LU table......................................................................................................115

A9. Structure and content of deposit-subtype look-up table, 

 DepositSubtype_LU ........................................................................................................115

A10. Structure and content of the province and country

 look-up table, Province_LU ...........................................................................................116

A11. Structure, content, and description of terms in the 

 mineral resource categories look-up table, ResourceCat_LU................................117

A12. Structure, content, and description of terms in the mineral 

 resource standards look-up table, ResourceStd_LU................................................118

A13. Structure, content, and description of terms in the site activity 

 look-up table, SiteActivity_LU.......................................................................................118

A14. Structure and content of the deposit reference junction 

 table, DepRef_MM..........................................................................................................119

A15. Structure and content of the resource reference junction 

 table, ResRef_MM ..........................................................................................................119

A16. Structure and content of the Switchboard Items table..................................................121

A17. List of queries and brief description of output and 

 use in other queries ........................................................................................................122

A18. Description of the forms in the Central African Copperbelt (CACB) database ..........129

A19. Description of operations that can be performed using 

 the Switchboard form.....................................................................................................129

B1. Description of digital data files for spatial databases (GIS) ..........................................149

B2. Examples of the types of sources used to compile the 

 CACB_deposits_prospects shapefile ........................................................................150

B3. Definitions of user-defined fields in the attribute table for 

 the shapefile CACB_deposits_prospects ...................................................................151

 B4. Description of Katangan lithologies used in the “Unit” field.........................................152

 B5. Definitions of user-defined attribute fields in the shapefile 

 CACB_orebodies.shp......................................................................................................153

 B6. Definitions of user-defined attribute fields in the shapefile 

 CACB_open_pits.shp......................................................................................................153
xii

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

mile, nautical (nmi) 1.852 kilometer (km)

yard (yd) 0.9144 meter (m)

Area

acre 4,047 square meter (m2

)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2

) 

acre 0.004047 square kilometer (km2

)

square foot (ft2

) 929.0 square centimeter (cm2)

square foot (ft2

) 0.09290 square meter (m2)

square inch (in2

) 6.452 square centimeter (cm2)

section (640 acres or 1 square mile) 259.0 square hectometer (hm2

) 

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2) 

Mass

ounce, avoirdupois (oz) 28.35 gram (g) 

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

ton, short (2,000 lb) 0.9072 megagram (Mg) 

ton, long (2,240 lb) 1.016 megagram (Mg) 

ton per day (ton/d) 0.9072 metric ton per day

ton per day (ton/d) 0.9072 megagram per day (Mg/d)

ton per day per square mile 

[(ton/d)/mi2

] 0.3503 megagram per day per squarekilometer [(Mg/d)/km2]

ton per year (ton/yr) 0.9072 megagram per year (Mg/yr)

ton per year (ton/yr) 0.9072 metric ton per year
xiii

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2

) 0.0002471 acre 

hectare (ha) 2.471 acre

square hectometer (hm2

) 2.471 acre

square kilometer (km2

) 247.1 acre

square centimeter (cm2

) 0.001076 square foot (ft2)

square meter (m2

) 10.76 square foot (ft2) 

square centimeter (cm2

) 0.1550 square inch (ft2) 

square hectometer (hm2

) 0.003861 section (640 acres or 1 square mile)

hectare (ha) 0.003861 square mile (mi2

) 

square kilometer (km2

) 0.3861 square mile (mi2)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

megagram (Mg) 1.102 ton, short (2,000 lb)

megagram (Mg) 0.9842 ton, long (2,240 lb)

metric ton per day 1.102 ton per day (ton/d) 

megagram per day (Mg/d) 1.102 ton per day (ton/d) 

megagram per day per square

kilometer [(Mg/d)/km2

]

2.8547 ton per day per square mile 

[(ton/d)/mi2]

megagram per year (Mg/yr) 1.102 ton per year (ton/yr)

metric ton per year 1.102 ton per year (ton/yr) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Vertical coordinate information is referenced to the World Geodetic System (WGS84).

Horizontal coordinate information is referenced to the World Geodetic System (WGS84).

Altitude, as used in this report, refers to distance above the vertical datum.
xiv

Acronyms and Abbreviations Used in This Report

A.D. Anno Domini—a designation used to label or number years used with the 

 Gregorian calendar. 

ANOVA analysis of variance

ASCII American Standard Code for Information Interchange

B.C. Before Christ—a designation used to label or number years used with the 

 Gregorian calendar.

CACB Central African Copperbelt

CRIRSCO Committee for Mineral Reserves International Reporting Standards

DRC Democratic Republic of the Congo

Esri a software development and services company providing

 geographic information system software and geodatabase management

 applications

FAQ frequently asked questions

g/t grams per metric ton

Gécamines La Générale des Carrières et des Mines,

 a state-owned mining company in the Democratic Republic of the Congo

GIS geographic information system

GUI graphical user interface

IOCG iron oxide-copper-gold

Ma mega-annum or millions of years before the present

MRDS Mineral Resources Data System

SCRV structurally controlled replacement and vein

SHRIMP sensitive high-resolution ion microprobe

SQL Structured Query Language

SSC sediment-hosted stratabound copper

SSIB small-scale digital internal boundaries

USGS United States Geological Survey

UTM Universal Transverse Mercator

δ13C a measure of the ratio of stable isotopes 13C:12C, reported in parts per thousand
Descriptive Models, Grade-Tonnage Relations, and 

Databases for the Assessment of Sediment-Hosted 

Copper Deposits—With Emphasis on Deposits in the 

Central African Copperbelt, Democratic 

Republic of the Congo and Zambia

By Cliff D. Taylor, J. Douglas Causey, Paul D. Denning, Jane M. Hammarstrom, Timothy S. Hayes, John D. 

Horton, Michael J. Kirschbaum, Heather L. Parks, Anna B. Wilson, Niki E. Wintzer, and Michael L. Zientek

Abstract 

The Central African Copperbelt (CACB) is one of the 

most important copper-producing regions of the world. 

The majority of copper produced in Africa comes from this 

region defined by the Neoproterozoic Katanga sedimentary 

basin of the southern Democratic Republic of the Congo 

(DRC) and northern Zambia. Copper in the CACB is mined 

from sediment-hosted stratabound copper deposits associated with red beds and includes the giant deposits in the 

Kolwezi and Tenge-Fungurume districts in the DRC and the 

Konkola-Musoshi and Nchanga-Chingola districts in Zambia. In recent years, sediment-hosted structurally controlled 

replacement and vein (SCRV) copper deposits, such as the 

giant Kansanshi deposit in Zambia have become important 

exploration targets in the CACB region.

In 2011, the CACB accounted for 7.2 percent of the 

estimated global mine production of copper. Global production of copper is principally derived from porphyry and 

sediment-hosted copper deposits (57, and 23 percent, respectively). Almost 50 percent of the copper known to exist in 

sediment-hosted deposits (past production plus identified 

resources) is contained in the CACB, 25 percent is contained 

in the Zechstein Basin of northern Europe, and the remainder 

is contained in an additional 29 sedimentary basins distributed around the globe. 

The U.S. Geological Survey (USGS) led an assessment of undiscovered copper resources in the CACB as part 

of a global mineral resource assessment for undiscovered 

resources of potash, copper, and platinum-group elements 

in selected mineral deposit types. As part of the assessment process, available data for the CACB were compiled 

and evaluated. This report describes the results of that work, 

including new descriptive mineral-deposit and grade and 

tonnage models and spatial databases for deposits and occurrences, ore bodies and open pits. 

Chapter 1 of this report summarizes a descriptive 

model of sediment-hosted stratabound copper deposits. 

General characteristics and subtypes of sediment-hosted 

stratabound copper deposits are described based upon 

worldwide examples. Chapter 2 provides a global database of 170 sediment-hosted copper deposits, along with a 

statistical evaluation of grade and tonnage data for stratabound deposits, a comparison of stratabound deposits 

in the CACB with those found elsewhere, a discussion of 

the distinctive characteristics of the subtypes of sedimenthosted copper deposits that occur within the CACB, and 

guidelines for using grade and tonnage distributions for 

assessment of undiscovered resources in sediment-hosted 

stratabound deposits in the CACB. Chapter 3 presents a 

new descriptive model of sediment-hosted structurally 

controlled replacement and vein (SCRV) copper deposits 

with descriptions of individual deposits of this type in the 

CACB and elsewhere. Appendix A describes a relational 

database of tonnage, grade, and other information for more 

than 100 sediment-hosted copper deposits in the CACB. 

These data are used to calculate the pre-mining mineral 

endowment for individual deposits in the CACB and serve 

as the basis for the grade and tonnage models presented 

in chapter 2. Appendix B describes three spatial databases 

(Esri shapefiles) for (1) point locations of more than 500 

sediment-hosted copper deposits and prospects, (2) projected surface extent of 86 selected copper ore bodies, and 

(3) areal extent of 77 open pits, all within the CACB. 
2 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Chapter 1. Overview of a New Descriptive Model for SedimentHosted Stratabound Copper Deposits

By Michael L. Zientek, Timothy S. Hayes, and Jane M. Hammarstrom 

Introduction

Sediment-hosted stratabound copper deposits that are 

associated with red beds have been mined since the 4th millennium B.C. in the Middle East (Weisgerber, 2006) and 

A.D. 1199 in the Kupferschiefer in central Europe (Beck, 

1905, p. 492). At present, these deposits are mined in the 

Democratic Republic of the Congo and in Zambia, Poland, 

Kazakhstan, China, and the United States. The global distribution of sediment-hosted stratabound copper deposits and 

related sedimentary rocks are shown in figure 1-1.

Sediment-hosted stratabound copper deposits are the 

world’s second most important source of copper (Cu), behind 

porphyry copper deposits, and account for more than 20 

percent of the copper that has been discovered (Singer, 1995). 

Sediment-hosted stratabound copper deposits also represent the 

world’s main source of cobalt (Co) production and rank third 

among all deposit types in silver (Ag) that has been discovered. 

Copper production from sediment-hosted stratabound copper 

deposits forms the basis of the economies of Poland, Zambia, 

and the Democratic Republic of the Congo (DRC).

This chapter is a brief overview of a mineral deposit model 

for sediment-hosted stratabound copper deposits that updates 

previous descriptive models for such deposits (Cox and others, 

2003). The first descriptive model for this deposit type, then 

called “sediment-hosted Cu”, was prepared by Cox (1986). This 

overview describes key attributes of the deposit type that are 

necessary for completing a mineral resource assessment, first in 

a concise format and then in greater detail.

Concise Description

Sediment-hosted stratabound copper mineralization consists of fine-grained copper- and copper-iron-sulfide minerals 

that occur as stratabound to stratiform disseminations in siliciclastic or dolomitic sedimentary rocks. Ore minerals occur as 

cements and replacements, and less commonly, as veinlets. 

The concentration of sulfide minerals conforms closely, but 

not exactly, with the stratification of the host rocks. Typically, 

the ore zones comprise chalcocite and bornite. These deposits 

are characterized by zoning of ore minerals laterally along and 

across bedding, from pyrite to chalcopyrite to bornite to chalcocite to hematite. Deposits are hosted in black, gray, green, 

or white (reduced) sedimentary strata within or above a thick 

section of red (oxidized) beds.

Synonyms

Continental red bed copper, copper-shale, Kupferschiefertype copper, Mansfeld-type copper, marine paralic copper, red 

bed copper, reduced-facies copper, Revett copper, sandstone 

copper, sediment-hosted copper, sediment-hosted stratiform 

copper, shale-hosted copper, stratiform copper.

Commodities (byproducts)

Copper, silver (cobalt, lead, and zinc; rarely gold, 

platinum-group elements, uranium, and vanadium). 

Importance

Sediment-hosted stratabound copper deposits account 

for approximately 20 percent of the world’s past production 

and known resources of copper (Singer, 1995). Although such 

deposits are common throughout the world, economically 

significant deposits are rare (Hitzman and others, 2005).

Associated Deposit Types

Sediment-hosted stratabound copper deposits are transitional to volcanic red bed copper deposits (Kirkham, 1996b) 

and tabular sandstone-hosted uranium deposits. Genetically 

related deposit types include flood basalt-hosted native copper deposits as in the Keweenawan Native Copper District 

of northern Michigan (White, 1968), and massive carbonate 

replacement copper deposits at Kennecott, Alaska (MacKevett 

and others, 1997).

Spatially associated deposit types include evaporites, iron 

oxide-copper-gold (IOCG) deposits, sediment-hosted structurally controlled vein and replacement copper deposits, and 

Kipushi carbonate-hosted deposits (Cox and Burnstein, 1986).

Ore System Components

1. Source rocks for copper, typically oxidized (hematitestable) siliciclastic sediment or mafic subaerial volcanic 

rocks.

2. Hematite-stable (oxidized) subsurface sedimentary brines 

capable of dissolving and transporting copper in solution.
3. The presence of brines moving generally in the direction 

of dewatering of a sedimentary basin.

4. Containment structures such as confining beds, stratigraphic pinchouts, and/or anticlinal traps.

5. A significant organic-rich sequence of sedimentary rocks 

capable of serving as an in situ reductant or of generating 

mobile reductants (natural gas, oil, and H2S) that would 

cause the precipitation of copper from an oxidized subsurface sedimentary brine.

Permissive Tract Delineation

 Mineral-resource-assessment geologists use descriptive 

information on ore deposit types to delineate areas, termed 

“permissive tracts,” in which the presence of as yet undiscovered deposits of a given type is possible. Each deposit 

type has certain fundamental characteristics related to ore 

system components that can be analyzed in concert with 

map data to define units that can in turn be used to delineate 

permissive tracts. The fundamental unit for delineation of 

a permissive tract for sediment-hosted stratabound copper 

deposits in a sedimentary basin is the presence of (1) a flooding surface1

 (typically a disconformity) that has carbonaceous and/or pyritic beds characteristic of a deeper water 

depositional environment, (2) reservoir facies rocks that contained trapped petroleum, or (3) fluvial reservoir facies rocks 

that contain detrital plant fragments that immediately overlie 

or are stratigraphically above and within 10 kilometers (km) 

from a section of sandy or grainy red beds, which are more 

than 300 meters (m) thick, from a fluvial or shallow-water 

depositional environment. Flood basalts may be associated 

with the red beds. 

Selected References

Kirkham (1989); Brown (1997); Cox and others (2003); 

Hitzman and others (2005); Hitzman and others (2010).

Detailed Description

Sediment-hosted stratabound copper deposits are peneconformable concentrations of copper minerals (table 1-1) 

in black, gray, green, or white sedimentary rocks within, or 

overlying, a succession of red beds that may be hundreds to 

thousands of meters thick. The disseminated copper minerals occur as cements and replacements, along with some 

veinlets. These deposits are characterized by zoning of the 

ore minerals laterally along and across bedding, from pyrite 

to chalcopyrite to bornite to chalcocite to hematite. Chalcocite and bornite typically comprise the ore zones; ores with 

1

Words or phrases presented in this bold typeface are defined in the Glossary at the end of this chapter. Additional definitions of geologic terminology 

can be found in the American Geosciences Institute (AGI) Glossary of Geology online at http://www.agiweb.org/pubs/glossary/.

Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted Stratabound Copper Deposits 3

chalcopyrite as the major sulfide reach economic grades at 

places in the Central African Copperbelt (CACB).

Types of Sediment-Hosted Stratabound Copper 

Deposits

Host lithology and the nature of organic material in the 

host rock are used to distinguish three types of sedimenthosted stratabound copper deposits:

1. Reduced-facies copper deposits (Cox, 2003a): black to 

gray to green marine or lacustrine shale, siltstone, mudstone, or carbonaceous dolosiltstone/siliceous dolomite 

containing solid amorphous organic matter (fig. 1-2);

2. Sandstone copper deposits (Cox, 2003b): gray, wellsorted, fine- to coarse-grained sandstone which contained 

petroleum, probably as sour gas in most cases (fig. 1-3); 

and 

3. Red bed copper deposits (Lindsey and Cox, 2003): gray, 

poorly to moderately sorted, commonly conglomeratic 

fluvial sandstone containing carbonized plant fragments 

ranging in size from silt to whole logs.

Representative examples of these types of deposits are 

listed and described in table 1-2.

Global Distribution

Sediment-hosted stratabound copper deposits have been 

found on every continent except Antarctica (fig. 1-1). Two areas, 

however, the Kupferschiefer in the Zechstein Basin in northern 

Europe and the CACB in the Katanga Basin in Zambia and the 

Democratic Republic of the Congo, account for more than 80 

percent of the currently known resources in such deposits. 

Regional Geologic Setting and Age Distribution

Tectonic Settings

Many of the largest sediment-hosted stratabound copper 

deposits are found in failed rifts that subsequently became

major intracratonic basins, such as the Zechstein Basin in 

northern Europe and the Katanga Basin in central Africa (fig. 

1-1; Hitzman and others, 2010). A few copper deposits of this 

type are found in other extensional settings, including transtensional and intermontane basins (Cox and others, 2003). 

Some are found within the bounds of a former intracratonic 

extensional basin but in coarse, molassic sedimentary host 

rocks deposited during or after the subsequent collisional stage 

of a complete Wilson cycle (Wilson, 1966; Cox and others, 

2003). Intracontinental rift basins that formed within 20 to 30 

degrees of the equator are ideal settings for sediment-hosted 

stratabound copper deposits because these basins contain thick 

packages of red beds that formed in hot dry climates, which 

also produce evaporites (Kirkham, 1989). 
4 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Depositional Environment

The stratigraphic record of rift basins records episodic 

pulses of extension that allowed sediment accumulation at 

fast rates followed by longer periods of tectonic quiescence 

when sediment supply exceeded subsidence (Martins-Neto 

and Catuneanu, 2010; Prosser, 1993). The early stage of 

rift initiation is represented by subaerial fluvial and alluvial 

deposits. These deposits are overlain by a major transgression 

(a flooding surface) that begins a depositional sequence that 

displays overall progradational trends and upward coarsening 

vertical stacking sequences (Martins-Neto and Catuneanu, 

2010). Repeated episodes of extension will form vertically 

repeated cycles of a flooding surface overlain by a shaleturbidite sequence that grades upward into shallow water and 

coastal systems, which in turn grade upwards into alluvial 

facies (Martins-Neto and Catuneanu, 2010).

Host beds for many reduced-facies deposits occur at or just 

above the flooding surface that marks the transgression between 

an upward coarsening sag basin depositional sequence and 

underlying synrift, nonmarine red beds. Depositional environments that host reduced-facies mineralization above the transgressive surface include open-marine-shelf black shale, coastal 

sabkha deposits, and subtidal shelf carbonate rocks. Host rocks 

for sandstone copper deposits form in subtidal nearshore, beach, 

eolian, and fluvial settings, all of which make up the upper part 

of coarsening upwards depositional cycles. Mineralization is 

commonly found in well-sorted, fine- to coarse-grained, locally 

conglomeratic sandstone that exhibits cross bedding, parallel 

lamination, mud rip-up clasts, and ripple marks. The host rocks 

of red bed deposits are fluvial or, rarely, deltaic sandstones, 

which typically are conglomeratic, commonly with scour-andfill features and cross bedding.

Age Range

Sediment-hosted stratabound copper deposits are limited 

to sedimentary or metasedimentary formations younger than 

2,300 Ma, when free oxygen first appeared in Earth’s atmosphere (Bekker and others, 2004; Canfield, 2005), and the 

earliest red beds formed (Chandler, 1988; Bekker and others, 

2005). Red bed deposits (Lindsey and Cox, 2003) are Silurian 

or younger, after vascular land plants first appeared.

Timing of Mineralization

The ages of the copper deposits are difficult to determine 

because of a lack of datable minerals that are related to the 

mineralizing event. Isotopic methods that have been applied 

include Re-Os dating of chalcopyrite and bornite, K-Ar dating of illite, and U-Pb dating of xenotime overgrowths on 

detrital zircon. Paleomagnetic dating of hematitic alteration 

(Rote Fäule of the Polish Kupferschiefer system) has also 

been attempted (Jowett and others, 1987; Nawrocki, 2000). 

Large uncertainties, inconsistencies, and large ranges of 

ages, as well as protracted or multistage ore-forming events, 

preclude precise dating of most deposits. Some, but not all, 

of the dating studies indicate that the age of mineralization 

postdates the deposition of the host rocks (Jowett and others, 

1987; Nawrocki, 2000; Aleinikoff and others, 2012). This is 

consistent with petrologic and geochemical studies that indicate that ore deposition occurred during host rock diagenesis 

(Bartholomé, 1962; Brown, 1971; Hayes and Einaudi, 1986; 

Sweeney and Binda, 1989; Bechtel and others, 2001).

Characteristics of Sediment-Hosted 

Stratabound Copper Deposits 

Dimensions

Lateral dimensions are large relative to deposit thickness, and deposit morphology varies by deposit type. 

Reduced-facies deposits have sheet-like geometry with lateral 

dimensions from hundreds to thousands of times greater 

than thicknesses. For example, strike lengths may be on the 

order of 3,000 to 5,000 m, widths from 500 to 2,000 m, and 

ore body thicknesses ranging from a few meters to 50 m. 

Sandstone copper deposits are tabular to lens-like; lateral 

dimensions are from 20 to 100 times their thicknesses. Red 

Mineral Formula

Primary copper ore minerals 

Chalcopyrite* CuFeS2

Covellite CuS

Bornite* Cu5

FeS4

Anilite Cu7S4

Digenite Cu9S5

Djurleite Cu31S16

Chalcocite* Cu2S

Copper Cuo

Primary copper-cobalt ore minerals

Carrollite Cu(Co,Ni)2S4

Secondary copper minerals

Cuprite Cu2

O

Malachite* Cu2

(CO3)(OH)2

Azurite Cu3(CO3)2(OH)2

Chrysocolla (Cu,Al)2H2Si2O5(OH)4nH2O

Planchéite Cu8

Si8O22(OH)4H2O

Tenorite CuO

Brochantite* Cu4

(SO4)(OH)6

Table 1-1. Copper minerals in sediment-hosted stratabound 

copper (SSC) deposits. 

[Primary ore minerals are listed in order of decreasing copper 

oxidation state; *, most common minerals in SSC deposits]
Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted Stratabound Copper Deposits 5

bed copper deposits form lenses of copper-bearing rock. They 

are smaller than the other types of sediment-hosted stratabound 

copper deposits, with lengths and widths of a few tens of meters 

to a few hundred meters and typical thicknesses of ten meters or 

less. For all types of sediment-hosted stratabound copper deposits, bodies of mineralized rock typically are contained within a 

broader zone of anomalously high copper values (Lefebure and 

Alldrick, 1996). Cutoff grades are used to define ore bodies.

Host Rocks

Host rocks for reduced-facies deposits include black 

shale; dark gray to black siltstone; dark gray dolosiltstone, 

silty dolomite, and dolomite; gray shale; or locally, green 

shale or siltstone that contain solid organic material (various 

macerals) (Cox and others, 2003; Hitzman and others, 2005; 

Hitzman and others, 2010).

Sandstone copper deposit host rocks are typically wellsorted siliciclastic sandstones from a variety of deltaic topset 

environments. These rocks were probably reservoir rocks for 

petroleum when copper minerals were deposited. For many 

sandstone copper deposits, the petroleum was probably present 

as sour gas (Cox and others, 2003; Hitzman and others, 2005; 

Hitzman and others, 2010; Hayes and others, 2012).

Host rocks for red bed deposits are fluvial sandstone, 

commonly conglomeratic and containing carbonized vascular 

plant fragments (Cox and others, 2003).

Structural Control

Structural traps that enable the accumulation of hydrocarbons in sedimentary basins may also localize deposition 

of sediment-hosted copper mineralization. These include 

anticlines, and complex combination traps produced by 

pre-ore folding and faulting. Faults at high angles to the host 

beds are found at many sediment-hosted stratabound copper deposits. Evidence for syndepositional fault movement 

includes changes in net sand thickness across structures 

(Boleneus and others, 2005) or the offset of underlying 

red beds but not the slightly younger reduced-facies package 

(Kulick and others, 1986, p. 34; Selley and others, 2005, p. 

972). Fold structures, some of which are fault- or salt-cored, 

localize sediment-hosted copper mineralization in the ChuSarysu (Syusyura and Tyugay, 2008) and Paradox (Hahn and 

Thorson, 2006) Basins.

Salt tectonics are associated with brine migration (Warren, 2000) and the development of structural traps that localize 

some sediment-hosted copper deposits such as at Canfield 

Creek, Maritimes Basin (O’Sullivan, 2006); and Blinman, 

Adelaide Geosyncline, South Australia (Selley, 2000; Dyson, 

2004; Cowley and others, 2009). However, salt tectonics can 

disrupt earlier formed stratabound mineralization, such as the 

reduced-facies deposits associated with the Mines Subgroup 

of the CACB in the Katanga Basin (Jackson and others, 2003; 

François, 2006).

Ore Mineralogy

 The principal copper ore minerals are chalcocite, bornite, 

and chalcopyrite; less common ore minerals include digenite, djurleite, covellite, sulfur-rich bornite±carrollite, Co-rich 

pyrite, and native silver. Pyrite is present in rocks outside the 

ore zones. Galena and sphalerite are found in the zones that 

separate copper ore from pyritic zones. Silver also may be 

present in solid solution in chalcocite, digenite, and/or bornite.

Uranium- and vanadium-oxide and silicate minerals may 

be present in some red bed deposits, for example, those in the 

Colorado Plateau region, United States. Uraniumu (U) in coffinite and vanadium (V) in illite or chlorite is typically present 

in pyritic assemblages (Brookins, 1976; Foster, 1959; Rackley, 1976; Riese, 1980). Uranium in uraninite and vanadium 

in montroseite are more typically found in chalcocite-bearing 

assemblages (Isachsen and Evenson, 1956; Evans, 1959; 

Trites and others, 1959). 

Ore Textures

Copper sulfide minerals are fine grained and occur as 

disseminations concentrated along bedding, particularly the 

coarser grained fractions of the host rocks, and as intergranular 

cement interstitial to detrital silicates or carbonate allochems

(Lefebure and Alldrick, 1996). Sharp-walled cracks or veinlets 

(< 1 centimeter, cm, thick; < 1 meter in length) of chalcopyrite, bornite, chalcocite, galena, sphalerite, or barite with 

quartz and/or calcite occur in some deposits, but are not an 

important component of the ore (Jowett, 1987; Lefebure and 

Alldrick, 1996). Pyrite can be framboidal or colloform.

Copper sulfide minerals replace carbonaceous materials 

in the sedimentary host rocks at every scale. Where organic 

matter or organic carbon compounds were not directly 

replaced by the copper sulfides, the organic materials were 

altered both chemically and physically, by changing from predominantly alginite to bitumen, or by oxidizing to dissolved 

carbonate species and precipitating as carbonates.

Copper minerals also replace pre-ore diagenetic minerals 

in the host rocks, such as pyrite grains, framboids and nodules; in some host rocks, they form pseudomorphs of sulfate 

nodules or blade-shaped gypsum/anhydrite grains (Lefebure 

and Alldrick, 1996).

In unmetamorphosed sediment-hosted stratabound copper 

deposits, pyrite is replaced by chalcopyrite, which is replaced 

in turn by bornite, then by chalcocite. Further, pyrite is 

replaced by magnetite (rarely) or hematite (commonly).

Ore Mineral Zonation

Mineral zonation both laterally and vertically from pyrite 

to chalcopyrite to bornite to chalcocite to hematite is characteristic of reduced-facies and sandstone copper deposits. In many 

deposits, galena and sphalerite may occur with chalcopyrite or 

between the chalcopyrite and pyrite zones. The same minerals 

are found in red bed deposits, but with telescoped zonation.
180° 120°W 60°W 0° 60°E 120°E 180° 30°N 10°S 15°E 

10°S 20°S

70°W 

20°S30°S40°S

0° 20°E

55°N50°N

135°E 140°E

30°S35°S

68°E 76°E

50°N

101°E 103°E

27°N

120°W 1

50°N40°N

112°20'W 112°10'W

27°20'N27°10'N

132°W 126°W

65°N63°N

34°E 

31°N30°N29°N

9°W 6°W

31°N

30°N

116°E 120°E

58°N56°N

90°W 85°W

48°N45°N

23°0'E 24°0'E

70°30'N

70°0'N

65°W 60°W

50°N45°N

0 50 100 MILES0 100 200 KILOMETERS

0 100 200 300 MILES0 200 400 600 KILOMETERS

0 100 200 300 MILES0 200 400 600 KILOMETERS

0 25 50 75 MILES0 50 100 150 KILOMETERS

0 4 8 MILES0 5 10 15 KILOMETERS

0 25 50 75 MILES

0 50 100150 KILOMETERS

0 50 100 150 MILES

0 100 200 300 KILOMETERS

0 50 100 150 MILES0 100 200 300 KILOMETERS

0 25 50 MILES0 50 100 KILOM

0 25 50 75 MILES0 50 100 150 KILOMETERS

0 3,000 6,000 KILOMETERS0 1,000 2,000 3,000 MILES

0 300 600 KILO0 300 MILES 150

Basin

EXPLAN

Sedimecopper 

A

B

C

D

E F G

H

I

J K

L M N O

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

Anti Atlas

Willouran

Trough

Adelaide

Geosyncline

De

G

Dongchuan (shown in blue)

Northwest Bot

Rift/Ghanzi-C

Jafr-Tabuk-Sinai

Katanga

Keewenawan

Kodar-Udokan

Komagfjord-Repparfjord

Greenstone Belt

Kwanza

Paradox Pe

Mackenzie Mountains

Santa Rosalia

Zechstein

Cheshire - Worcester

Neuque

Sa

Belt-Purcell

Teniz

Maritimes

Otavi Mountain

Land

Stuart

Shelf
70°W 

20°S30°S40°S

135°E 140°E

30°S35°S

68°E 76°E

50°N45°N

101°E 103°E

27°N24°N

120°W 1

50°N40°N

27°10'N

132°W 126°W

65°N63°N

29

N

56°N

90°W 85°W

48°N45°N

23°0'E 24°0'E

70°30'N

70°0'N

0 50 100 MILES0 100 200 KILOMETERS

0 25 50 MILES

0 50 100 KILOMETERS

0 50100 MILES

0 100200 KILOMETERS

0 150 300MILES0 300 600 KILOM

0 25 50 75 MILES

0 50 100 150 KILOMETERS

0 4 8 MILES0 5 10 15 KILOMETERS

0 25 50 75 MILES0 50 100150 KILOMETERS

0 10 20 30 MILES

0 20 40 60 KILOMETERS

0 50 100 150 MILES

0 100 200 300 KILOMETERS

0 25 50 MILES0 50 100 KILOME

0 25 50 75 MILES0 50 100 150 KILOMETERS

0 300 600 KILOM0 300 MILES 150

H

I

J K

L M N O

Willouran

Trough

Adelaide

Geosyncline

Chu-Sarysu

Chuxiong

Dongchuan (shown in blue)

Keewenawan

Komagfjord-Repparfjord

Greenstone Belt

Paradox Pe

Mackenzie Mountains

Neuque

Sa

Belt-Purcell

Teniz

Stuart

Shelf

Figure 1-1. Index maps showing the distribution of sedimentary rocks hosting sediment-hosted stratabound copper deposits in basins discussed in cExtent of the Cheshire-Worcester Basin, United Kingdom, (Fugro Robertson, Ltd., 2008) and distribution of the Permian Zechstein Z1 unit in the NortheBasins, northern Europe (Bavarian Geological State Office, 2004; Doornenbal and Stevenson, 2010; Federal Institute for Geosciences and Natural Resand Britze, 1994; Zagorodnykh, 2000); (B) distribution of Paleozoic sedimentary rocks associated with the Maritimes Basin, Canada (Garrity and Soller, Mesozoic Kwanza Basin (Fugro Robertson, Ltd., 2008), and distribution of Proterozoic sedimentary rocks associated with the Otavi Mountain Land, the Rift, the Katanga Basin, and the Dewaras Group, Africa (Andritzky, G., 1998; Haddon, 2001; Key, 1998; Laghmouch, 2008; Schreiber, 1980; Veselinovic-W2003 [2007]; Zimbabwe Geological Survey, 1985); (D) distribution of Paleozoic sedimentary rocks in the Anti Atlas Mountains, Morocco (Veselinovic-W2003 [2007]); (E) distribution of Cenozoic sedimentary rocks associated with the Santa Rosalia Basin, Mexico (Servico Geológico Mexicano, 1997); (F) dsedimentary rocks associated with the Kodar-Udokan trough, Russia (Konnikov and others, 1984; Lagzdina and others, 1978); (G) the extent of Cambriasedimentary rocks of the Araba, Burj, and Timna Formations in the Jafr-Tabuk-Sinai Basins, Egypt, Israel, and Jordan, extended to a depth of 2 kilometSegev, 2004; Bender, 1975; Dardir, 1998; Guiraud, 1999; Khalifa and others, 2006; Klitzsch and others, 1987; Pollastro and others 1997; and Sneh and otheof Proterozoic sedimentary rocks associated with the Keewenawan Rift, Canada and USA (Garrity and Soller, 2009); (I) distribution of Proterozoic sediwith the Redstone Copperbelt, Mackenzie Mountains, Canada (Garrity and Soller, 2009); (J) distribution of Proterozoic sedimentary rocks associated wthe Wilbouran Trough, Australia (Department of Primary Industries and Resources South Australia, 2006); (K) extent of the Mesozoic and Cenozoic Saothers, 2005) and Nequen Basin, Argentina (Fugro Robertson, Ltd., 2008); (L) distribution of Proterozoic rocks associated with the Komagfjord-RepparfNorway (NGU, written commun., 2006); (M) extent of the Mesozoic Chuxiong Basin (Fugro Robertson, Ltd., 2008) and distribution of Proterozoic sedimewith the Dongchuan area, China (Bureau of Geology and Mineral Resources of Yunnan Province, 1990); (N) extent of the Paleozoic and Mesozoic ChuKazakhstan (Fugro Robertson, Ltd., 2008); and (O) distribution of the sedimentary rocks associated with the Paleozoic Permian Basin (Garrity and SolleBelt-Purcell Basin (Garrity and Soller, 2009) and the extent of the Paleozoic and Mesozoic Paradox Basin (American Association of Petroleum Geolog
8 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Figure 1-2. Stratigraphic columns showing the position of reduced-facies type copper mineralization in 

the Redstone Copper Belt, Mackenzie Mountains, Canada (Rainbird and others, 1996); the White Pine area, 

Keweenawan Rift, United States (Nicholson and others, 1997); the Ghanzi area, Northwest Botswana Rift, 

Botswana (Kampunzu and others, 1998); the Kupferschiefer, Zechstein Basin, Poland (Nawrocki, 1997); the 

Cuanza Basin, Angola (Brognon and Verrier, 1966), and the Central African Copperbelt (CACB), Democratic 

Republic of the Congo (François, 2006) and Zambia (Selley and others, 2005).

Jacobsville

Sandstone

Freda

Sandstone

Nonesuch Shale

Copper Harbor

Conglomerate

Porcupine

Volcanics

Portage Lake

Volcanics

Rock color

Lithology Formation

Mineralization

Rock color

Lithology

Mineralization

Lithology Formation

Mamuno

D’Kar

Ngwako Pan

Kgwebe

Rock color

Mineralization

Rock 

color Lithology Formation

and group

Ingta Formation

Risky Formation

Blueflower

Formation

Gametrail Formation

Sheepbed

Formation

Keele/Icebrook 

Formation

Twitya Formation

Upper Carbonate 

Formation

Rusty Shale 

Formation

Gypsum 

Formation

Grainstone 

Formation

Plat/Basinal 

Formation

K7 Formation

K6 Formation

K5 Formation

K4 Formation

K3 Formation

K2 Formation

K1 Formation

H1 Formation

Tsezotene

Formation

Rapitan Group

Mineralization

Coppercap

Formation

Redstone River

Formation

Thundercloud

Formation

Little Dal Basalt

Formation

BF

DG

LG

PC

WT

DG

DG

GG 

GY

GY

GY

VC

PC

RD

RD

RD

RD

RD

RD

RD

RT

RT

BF

VC

GY

DG

White Pine

Kupf

Ghanzi

Redstone
Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted Stratabound Copper Deposits 9

2.2

2.1

1.3

1.2

1.1

1.3

1.2

1.1Formation

Group

Ks 3

Ks 2

Ks 1

Ki 2

Ki 1

R 4

R 3

R 2

R 1

Supergroup

Kundelungu

Superior -

Ks

Kundelungu

Inferior -

Ki

Roan - R

Rock color

Lithology

Mineralization

Gaps in R2-R3 represent position 

of former salt beds

Rock color

U. Buntsandstein

Muschelkalk

M. Buntsandstein

L. Buntsandstein

Zechstein

Upper

Rotliegend

Lower

Rotliegend

Lithology

Unit name

Mineralization

Kupferschiefer

Kirilabombwe

Subgroup

Ore Shale Fm.

Grand Conglomerate

Mwashia

Subgroup

Mindola

Subgroup

Kitwe Subgroup

Basement

Subgroup and 

formation Lithology

Rock color

Mineralization

Formation

Mamuno

D’Kar

gwako Pan

Kgwebe

Luanda and Cacuaco

Quifangondo

Cunga

Gratidão

Rio Dande and Teba

N’golome

Itombe

Cabo Ledo

Quissonde

Catumbela

Tuenza

Binga

Quinga

Loeme

Cuvo

Igneous rocks

Basement complex

Lithology Formation

Rock color

Mineralization

Red

Rust

Grey

Dark grey*

Green grey

White

Buff

Varicolored 

Lilac

BF

DG

GG

GY

LG

LI

PC

RD

RT

VC

WT

GG

VC

Peach

Light green

DG

DG

LI

GY

GY

GY

RD

RD

RD

VC

GY

RD

GY

GY

DG

*Dark grey rock color correlates 

 closely with carbonaceous 

 lithologies 

Cuanza

Kupferschiefer

CACB

CACB

Sandstone

Shale

Siliciclastic and 

 carbonate rocks

Carbonate rocks

Evaporites

Volcanic rocks

Metamorphic rocks

Siltstone Gabbro

Breccia

Conglomerate

Granite

Argillite

Siliciclastic rocks

EXPLANATION

Carbonate and

 siliciclastic rocks

Diamictite

Copper mineralization

1

KILOMETERS

0

0.5

0

0.25 0.5

MILES

Figure 1-2.—Continued
10 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Lithology Formation Group

Mineralization

Rock color

Missoula

Midlde 

Belt 

Carbonate

Ravalli

Lower Belt

McNamara 

Bonner

 Mt. Shields

Shepard

Snowslip

Garnet Range

post-Belt?

Wallace

Helena

Empire

St. Regis

Revett

Burke

Prichard

Western Belt Basin

LI

VC

VC

VC

RD

GY

DG

WT

GR

GG

RD

RD

RD

GY

GY

Upper

Lower

Upper

Lower

Lower

Upper

Naminga

Sakukan

Butun

Aleksandrov

Chitkanda

Inyr

Ayan

Ikaby

Talakan

Kemen

Chinei

Kodar

Formation Group

Mineralization

Subformation

Rock color

Kodar-Udokan

Lithology

Figure 1-3. Stratigraphic columns showing the position of sandstone-type copper mineralization in the Belt Basin, 

United States (Cressman, 1990); the Kodar-Udokan area, Russia (Bogdanov and others, 1966); and the Chu-Sarysu 

Basin, Kazakhstan (Box and others, 2012).
Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted Stratabound Copper Deposits 11

Siliciclastic rocks

Kingir

Zhidelisai

Dzhezkazgan

Taskuduk

Lithology Formation

Mineralization

Rock color

Chu-Sarysu

GY

GY

DG

DG

EXPLANATION

MILES

1

2

KILOMETERS

1

2

3

0 0

Red

GreyGY

RD

DG Dark grey

WhiteWT

GR Green

VC Varicolored 

LilacLI

GG Green grey

Quartzite and argillite

Sandstone

Shale Granite

Copper mineralization

Unconformity

Carbonates

Argillite

Metamorphic rocks

Evaporites

Conglomerate

Volcanic rocks

Carbonate and

 siliciclastic rocks

Figure 1-3.—Continued
Table 1-2. Representative examples of sediment-hosted stratabound copper deposits. [SSC, sediment-hosted stratabound copper; Mt, million metric tons; %, percent; g/t, grams per metric ton; Ma, mega-annum—a period of one million years; km, kilometers; *, grades for hand-sorted ore] Name Location Subtype Geologic setting Age Grade and Tonnage Comment 

Lubin-Sieroszowice (Malomice, Lubin, Sieroszowice, Polko- wice, Rudna, Glogow Gleboki-Przemyslowy, Bytom Odrzanski, Retkow, Gaworzyce, Radwanice Zachod) Poland reduced- facies copper Southern flank of the Zechstein Basin Permian, probably 240±3.8 Ma in host rocks deposited from 258 to 260.4 Ma 3,612.5 Mt, 1.99% Cu, 56.5 g/t Ag Lubin-Sieroszowice is the largest sediment-hosted stratabound copper deposit in the world. Jowe

M(2Pi

OK

Kolwezi Klippe (Kamoto-KOV-Mu- sonie-Mupine) Democratic Republic of the Congo reduced- facies copper Lufilian Arc in Neoproterozoic Katangan (meta) sedimentary rocks Neoproterozoic, probably 816±62 Ma in host rocks deposited between 893 and 746 Ma 416.2 Mt, 4.49% Cu, 0.39% Co Probably supergene enriched. World’s largest known resource of cobalt. Dem

th

ot(1DD

Creta Oklahoma, United States reduced- facies copper Northern flank of the Permian Hollis Basin Unknown; late Permian host rocks 5.4 Mt, 1.9% Cu, 5.5 g/t Ag Creta is underlain by more than 1,000 m of Permian rock, mostly red beds. Hagn

(1(1

Udokan Transbaikalia Russia sandstone copper Southern margin of the Archean Aldan Shield Proterozoic 1,528 Mt, 1.45% Cu, 12.6 g/t Ag Udokan is the second largest known sandstone copper deposit in the world Baku

anotCh

Spar Lake (Troy mine) Montana, United States sandstone copper Belt Basin Proterozoic; 1409±8 Ma in host rocks deposited between 1468 and 1443 Ma 80.6 Mt, 0.63% Cu, 46 g/t Ag Silver is present in solid solution in copper sulfide minerals. Unmetamorphosed analogue is the Dzhezka- zgan district, Kazahkstan. Haye

anBan

Juramento Argentina sandstone copper Folded Mesozoic sedi- ments in the foreland between the Andean continental arc and the Rio de la Plata craton Unknown; late Cretaceous host rocks 44.7 Mt, 0.80% Cu, 21.8 g/t Ag Similar deposits occur within Cretaceous sandstones in the Neuquén Basin, several hundred km south of Juramento. Duri

A

Corocoro Bolivia red-bed copper Bolivian altiplano be- tween eastern and west- ern Andean Cordillera. Intermontane basin in hyperarid climate Unknown; middle Tertiary host rocks 7.8 Mt, 7.1% Cu, 106 g/t Ag * Corocoro is best characterized example of more than 20 deposits and districts on a NNW trend of salt diapirs with related SSC deposits that extends for 200 km. Sing

granC

Nacimiento New Mexico, Unied States red-bed copper Flank between the Nacimiento Precambri- an-cored uplift and the San Juan Basin Unknown; middle Triassic host rocks; likely pre-Tertiary 10.0 Mt, 0.67% Cu, 2.4 g/t Ag Supergene malachite and chrysocolla cements form halos around sulfidized logs and other sulfides in 

very porous sandstones. 

Lind

(1an
Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted Stratabound Copper Deposits 13

Hypogene Gangue Minerals

Gangue minerals include the common rock-forming 

minerals that make up the siliciclastic and carbonate sedimentary rocks that host the sulfide mineralization. Gangue 

also includes ore-stage minerals that form cements and 

replacements of earlier detrital and cementing minerals. 

Examples include authigenic K-feldpar, chlorite, and hematite. Authigenic quartz, tourmaline, manganese carbonate or 

oxide minerals, and barite are common gangue minerals in 

some deposits.

Hypogene Alteration

The mineralogical and textural changes that result from 

rock-fluid interactions that form sediment-hosted stratabound 

copper deposits are similar to those produced by normal 

diagenesis in a sedimentary basin. The alteration involves 

the intergranular replacement of earlier detrital minerals or 

cements or the formation of mineral overgrowths and cements. 

As such, this “alteration” is not distinguished in appearance, 

unless it forms nearly total replacements of the other minerals 

of the rock or occurs in strongly disconformable bodies.

Where it has been studied, the volumes of altered rock that 

are part of the mineralizing system are large, extending tens of 

kilometers and possibly up to 100 km laterally, and commonly 

affecting greater than 1 km of sedimentary rock thickness 

(Hitzman and others, 2005; Hitzman and others, 2010).

Alteration gangue minerals of sediment-hosted stratabound copper deposits are zonally arranged, with their zone 

boundaries parallel to the zonation of sulfide minerals. Authigenic hematite lining and filling pores is present in chalcocite 

zones of most deposits. Authigenic K-feldspar occurs as 

overgrowths on pre-existing detrital K-feldspar grains and as 

cements and replacements in ore zones of some reduced-facies 

and sandstone copper deposits. Other sodium-rich alteration 

phases include the sodic amphibole riebeckite and sodiumsulfate minerals. Chlorite is found as an authigenic mineral in 

many deposits, commonly in association with copper sulfide minerals. Iron-rich and manganese-rich calcite cements 

are found within fringing pyritic zones of sandstone copper 

deposits at Spar Lake, Belt Basin, Montana, and Dzhezkazgan, 

Chu-Sarysu Basin, Kazakhstan (Hayes, 1984, 1990; Lur’ye 

and Gablina, 1972).

All mineral zones of sediment-hosted stratabound copper 

deposits contain leucoxene pseudomorphs of the ilmenite in 

exsolved ilmeno-magnetite or ilmeno-hematite of formerly 

detrital grains.

Weathering and Supergene Ore

Weathered surfaces of rocks containing sediment-hosted 

copper mineralization are commonly coated by oxidized copper and iron minerals. During weathering, primary copper 

sulfide minerals are changed to sulfates, oxides, carbonates, 

or silicates. Oxidized copper and iron minerals include 

cuprite, malachite, azurite, chrysocolla, planchéite, tenorite, 

native copper, brochantite, and limonite. Malachite is typically most abundant. However, hypogene mineral zonation 

will affect weathering products. For example, brochantite 

is found in many places instead of malachite in weathered 

zones of bornite- and chalcocite-bearing rock. In others, 

“beer-bottle” limonite pseudomorphs develop from primary 

copper sulfide minerals (chalcocite, digenite, bornite, or 

chalcopyrite), whereas brown earthy goethite pseudomorphs 

replace pyrite.

In most climates, copper remains fixed in the weathering zone and copper grades are not enriched by weathering 

processes. In some situations, however, copper released by 

weathering reactions can be reprecipitated as the sulfide 

minerals, chalcocite and covellite, where oxidized fluids 

developed by weathering encounter a reducing environment 

at or below the water table, creating a zone of supergene 

enrichment (Taylor, 2011). 

Geochemical Guides

Metasomatic effects from sediment-hosted stratabound 

copper mineralizing systems can be documented on the basis 

of the major-element compositions of mineralized rocks and 

country rocks. Potassium and barium enrichment accompany 

copper deposition (Hayes, 1990; Sutton and Maynard, 2005). 

The altered hematitic source rocks associated with the Western 

Montana Copper Sulfide Belt show depletion of copper, sodium 

metasomatism, and extreme calcium leaching (Hayes, 1990).

Copper is an excellent pathfinder element in soils and 

stream sediment geochemical surveys in many different 

weathering and climatic conditions. Additional pathfinder 

elements are silver and cobalt; however, no cases of anomalous silver have been documented without anomalous copper. Other potentially anomalous elements associated with 

sediment-hosted stratabound copper deposits include lead, 

zinc, antimony, arsenic, mercury, barium, and rarely uranium, 

vanadium, molybdenum, selenium, and germanium.

Soil gas analysis for methane, hydrogen, sulfur dioxide, 

carbon disulfide, and mercury might be a powerful exploration 

tool for sandstone copper deposits, where oxidizing, metalstransporting brines mixed and reacted with hydrogen-sulfide 

(H2

S)-bearing natural gas (McCarthy and Reimer, 1986; Hayes 

and others, 2012).

Geophysical Guides

Geologic framework studies—Gravity, magnetic and 

electromagnetic surveys can be used to map basement topography, bedrock geology, and basin and subbasin margins. 

Seismic reflection or refraction surveys can identify basin and 

subbasin margins, anticlines, stratigraphic traps, and combination traps.

Alteration studies—In basins hosting major sedimenthosted stratabound copper deposits, significant fluid flow 
14 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

occurred and should have produced mappable alteration 

effects. Remote sensing of colors using Landsat imagery or 

remote sensing of ferric oxides using Landsat, ASTER, or 

AVIRIS imagery can be used to map bleaching of red beds 

(Beitler and others, 2003).

Directly targeting mineralization—The sulfide minerals 

of sandstone copper deposits or metamorphosed reducedfacies deposits are mildly conductive and may be detected 

with induced polarization and resistivity surveys providing 

that the local section does not contain highly carbonaceous or 

pyritic shales (Lindsey and others, 1995).

Genesis

Sediment-hosted stratabound copper mineralization is 

derived from hydrothermal fluids generated during diagenesis and lithification in sedimentary basins. On the basis of ore 

and gangue mineral zoning and alteration, mineral paragenesis, fluid inclusion studies, and stable isotope geochemistry, 

the metal bearing fluids are low temperature (75–220 degrees 

Celsius,oC), hematite-stable (oxidized), chloride-rich, 

subsurface sedimentary brines. These brines leach copper 

and other metals from synrift red beds and mafic volcanic 

rocks. The brines move upward toward a hydrologic seal 

where the primary cause of base-metal sulfide precipitation 

is the reduction of sulfate in the brine by organic material for 

reduced-facies or red bed deposits or is direct precipitation 

by the sour gas hydrogen sulfide (H2S) in sandstone copper 

deposits. Thermochemical sulfate reduction probably adds 

additional sulfides to all three sediment-hosted stratabound 

copper deposit types (Hoy and Ohmoto, 1989; Bechtel and 

others, 2001; Hayes and others, 2012).

Exploration and Resource Assessment Guides

The starting point for exploration and resource assessment of sediment-hosted stratabound copper deposits is recognition of a basin that contains both copper source rocks and 

suitable sedimentary host rocks. Factors critical to exploration 

and assessment are described below.

Copper Source Rocks

The basin must contain some minimum thickness, 

perhaps at least 300 m, of oxidized, hematite-stable, permeable source rocks with slightly elevated copper content, 

probably continental red beds. The nearly universal spatial 

association of sediment-hosted stratabound copper deposits with continental red beds indicates that these rocks are 

necessary for the formation of this deposit type. Continental red beds are first-cycle, immature sediments that are 

deposited under oxidizing conditions and owe their red 

coloration to the early diagenetic development of hematite (Metcalfe and others, 1994). Copper in red beds may 

be adsorbed on goethite and hematite. Subaerial basaltic 

or other mafic volcanic rocks are an alternative source of 

copper. The red bed and/or volcanic source rock may be 

distant from the site of ore deposition.

Brines

Hematite-stable (oxidized) subsurface sedimentary brines 

leach copper from labile detrital and authigenic minerals (for 

example, copper adsorbed onto iron-oxide coatings on detrital 

particles) during diagenesis. The association of sediment-hosted 

stratabound copper mineralization with basins that contain 

significant thickness (probably several hundred meters) of 

sulfate- and halite-bearing evaporites suggest that dissolution 

of evaporites may be part of the ore-forming process. Brines 

capable of dissolving and transporting copper in solution could 

be pore fluids developed within the basin (evolved seawater 

brines, residual bittern brines, brines from evaporite dissolution, aqueous fluids derived from dehydration reactions during 

diagenesis) or meteoric waters whose high salinities are generated through dissolution of evaporites (Hitzman and others, 

2005). Relative to the copper mineralized unit, evaporites can 

occur down section within the red bed sequence or in overlying 

marine or lacustrine sequences. Evidence of occult evaporites 

may include concordant and cross-stratal megabreccia zones, 

diapiric structures, breccia-cored and breached anticlines, and 

the presence of chlorine-rich minerals such as chlorine-bearing 

illite or marialitic scapolite (Beales and Hardy, 1977; Michalik, 

1997; Hitzman and others, 2005; Jackson and others, 2003).

Fluid Flow and Pathways

The basin must have undergone subbasin-scale fluid 

flow that allowed for partial to total evaporite dissolution, 

brine formation, and upwards cross-stratal brine migration. 

Possible causes for brine migration include compactiondriven fluid flow (Swenson and others, 2004), topographically driven fluid flow (White, 1971; Garven, 1985; Brown, 

2005, 2009), thermohaline (buoyancy)-driven convection 

induced by salt dissolution (Evans and Nunn, 1989), and 

thermally driven free convection (Jowett, 1986; Cathles and 

others, 1993). Tectono-thermal events, such as the emplacement of magmatic rocks, halokinesis, and basin inversion, 

are capable of initiating convection of subsurface sedimentary brines (Hitzman and others, 2005), but time association 

with magmatic events has not been demonstrated for any 

sediment-hosted stratabound copper deposit.

A flow system for transport of copper from source rocks to 

host rocks by sedimentary brines must have existed. Various types 

of flow systems and hydrologic drivers may have served as transport avenues, but the aquifers, at the time of mineralization, would 

have been confined so that brines migrated upward relative to 

stratigraphy. Transport/migration of copper must occur under artesian heads (by confined aquifer flow), because in almost all cases 

where it has been possible to determine, the zoning and paragenesis indicate that copper-rich, hematite-stable brines have entered 

the host rocks from below. Synsedimentary and postdepositional 
Chapter 1. Overview of a New Descriptive Model for Sediment-Hosted Stratabound Copper Deposits 15

faults were probably critical for many systems in providing 

focused cross-stratal fluid flow (Hitzman and others, 2005).

Most reduced-facies copper deposits and many of the 

other two deposit types appear to have formed on basin edges 

or where irregularities in the geometry of the basin focused 

fluid flow through the red bed package and upward into the 

host beds. Such focusing could be due to thinning of the red 

bed sequence on a basin margin, faults, permeability contrasts 

within specific sedimentary units, paleotopography within the 

basin itself (for example, basement highs, and anticlines), or 

enhanced fluid flow along the margins of salt walls or diapirs 

as in the Paradox Basin (Hahn and Thorson, 2006) and in the 

CACB in the DRC (Jackson and others, 2003).

Patterns of alteration mark pathways of metalliferous 

brine migration (hematite, albite, riebeckite, sodium sulfate 

minerals, epidote in volcanic rocks, sodium- and chlorinebearing illite). Hematite- and albite-rich assemblages found 

in the ore bodies may extend many kilometers into surrounding rock layers; altered rocks depleted in copper, where 

known, extend for kilometers from ore-bearing zones. 

Burial histories derived from petroleum exploration with 

methods such as Lopatin modeling (Lopatin, 1971) can subdivide permissive tracts into more favorable and less favorable 

areas. Only those areas within and adjacent to parts of the tract 

that underwent rapid sedimentation, subsidence, and burial are 

considered favorable.

Organic Matter

The basin must contain some form of organic matter 

that acted as a reductant at the site of copper mineral deposition. Organic-rich, poorly permeable sedimentary beds 

characterize reduced-facies deposits. Permeable beds with 

carbonized plant fragments distinguish red bed deposits. 

The organic reductant in the sandstone-type deposits is 

thought to be a mobile reductant, or in other words, petroleum vapor or liquids that accumulated in reservoir (permeable) beds. Mobile reductants require source beds for 

hydrocarbons in the stratigraphic sequence and a basin history that allowed the maturation and migration of hydrocarbon fluids. Evidence for petroleum that previously charged 

the permeable strata that host sandstone copper deposits 

includes petroleum-bearing fluid inclusions and dead oil 

that coats detrital grains, stains authigenic minerals, and 

may locally form cements.

Carbon isotope studies of ore-associated carbonate 

minerals from both reduced-facies deposits and sandstone 

copper deposits, include some quite low C values. The 

low- C-carbonates reflect oxidation of solid organic matter or petroleum to provide C for deposition of the carbonates (Sweeney and Binda, 1989; Bechtel and others, 2001; 

Hitzman and others, 2005).

Confining Beds and Containment Structures

Containment structures, such as stratigraphic pinchouts 

and anticlinal features with confining beds, are required to 

focus fluid flow of the copper-bearing brines to rocks that 

contain organic material that will cause sulfide mineral 

precipitation.

For reduced-facies deposits, the confining beds could be 

the fine-grained, organic-rich sedimentary host rocks themselves (fig. 1-2). In other basins, confining beds could include 

evaporite layers or shales that overlie permeable units that 

could host sandstone copper deposits (fig. 1-3).

Many types of stratigraphic and structural traps that may 

accumulate hydrocarbons in sedimentary basins may also localize deposition of sediment-hosted copper mineralization. These 

include the onlap of favorable host rocks onto paleotopographic 

features (updip pinch-out stratigraphic trap), unconformity 

traps, facies changes, stratigraphic pinchouts, anticlines, and 

complex combination traps produced by pre-ore folding and 

faulting (Hitzman and others, 2005, 2010).

Acknowledgments

USGS colleagues James Bliss, Pamela Dunlap, and 

Daniel Mosier provided helpful and constructive technical reviews. Heather Parks, Kassandra Lindsey, and Hannah 

Campbell helped prepare illustrations.
16 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Glossary

alginite Organic material, kerogen, of algal or bacterial origin.

allochem2 A collective term introduced by Folk (1959, p. 4) 

for one of several varieties of discrete and organized carbonate 

aggregates that serve as the coarser framework grains in most 

mechanically deposited limestones, as distinguished from 

sparry calcite (usually cement) and carbonate-mud matrix 

(micrite). Important allochems include: silt-, sand-, and gravelsize intraclasts; ooids; pellets; lumps; and fossils or fossil 

fragments (carbonate skeletons, shells, and so on).

bitumen2 A generic term applied to natural inflammable substances of variable color, hardness, and volatility, composed 

principally of a mixture of hydrocarbons substantially free 

from oxygenated bodies. Bitumens are sometimes associated 

with mineral matter, the nonmineral constituents being fusible 

and largely soluble in carbon disulfide, yielding water-insoluble sulfonation products. Petroleums, asphalts, natural mineral 

waxes, and asphaltites are all considered bitumens.

colloform2

 Said of the rounded, finely banded kidney-like 

texture formed by ultra-fine-grained rhythmic precipitation of 

minerals.

cutoff grade The lowest grade, or quality, of mineralized 

material that qualifies as economically mineable and available in a given deposit (Committee for Mineral Reserves and 

Reporting Standards, 2006). 

flooding surface In sequence stratigraphy, a surface separating 

younger from older strata across which there is evidence of an 

abrupt increase in water depth. This deepening is commonly 

accompanied by minor submarine erosion or nondeposition. 

This is not accompanied by subaerial erosion due to stream 

rejuvenation or a basinward shift in facies, including abnormal 

subaerial exposure, with a minor hiatus indicated. The flooding 

surface has a correlative surface in the coastal plain and a correlative surface on the shelf (Van Wagoner and others, 1990).

flysch2

 A marine sedimentary facies characterized by a thick 

sequence of poorly fossiliferous, thinly bedded, graded deposits composed chiefly of marls and sandy and calcareous shales 

and muds, rhythmically interbedded with conglomerates, 

coarse sandstones, and graywackes.

framboid2 A microscopic aggregate of pyrite grains in shale, 

often in spheroidal clusters resembling a raspberry. The tex

ture is linked with the presence of organic materials; sulfide 

crystals fill chambers or cells in bacteria.

kerogen2 Fossilized insoluble organic material found in 

sedimentary rocks, usually shales, which can be converted to 

petroleum products by distillation.

Lopatin model An empirical relationship between vitrinite 

reflectance and petroleum formation developed by N.V. Lopatin (1971) to use both time and temperature to calculate the 

thermal maturity of organic matter in sediments.

maceral2 One of the organic constituents that comprise the coal 

mass; all petrologic units seen in polished or thin sections of 

coal. Macerals are to coal as minerals are to inorganic rock. Maceral names bear the suffix “-inite” (vitrinite, liptinite, and so on).

molasse2 A paralic (partly marine, partly continental or deltaic) sedimentary facies consisting of a very thick sequence 

of soft, ungraded, cross-bedded, fossiliferous conglomerates, sandstones, shales, and marls, characterized by primary 

sedimentary structures and sometimes by coal and carbonate 

deposits. It is more clastic and less rhythmic than the preceding flysch facies. 

peneconformable Almost conformable. The adverb “pene” 

is Latin for almost, nearly, or practically.

salt tectonics Any tectonic deformation involving salt, or 

other evaporites, as a substratum or source layer (Jackson and 

Talbot, 1991).

sour gas Natural gas containing significant amounts of 

hydrogen sulfide.

stratabound2 Said of a mineral deposit confined to a single 

stratigraphic unit. The term can refer to a stratiform deposit, 

to variously oriented ore bodies contained within the unit, or 

to a deposit containing veinlets and alteration zones that may 

or may not be strictly conformable with bedding.

stratiform2 Said of a special type of stratabound deposit in 

which the desired rock or ore constitutes, or is strictly coextensive with, one or more sedimentary, metamorphic, or igneous 

layers; for example, beds of salt or iron oxide, or layers rich in 

chromite or platinum in a layered igneous complex.

Wilson cycle2 A successive recurrence of plate-tectonic 

spreading and convergence with a period generally in the 

100-million-year range. Named after J. Tuzo Wilson, Canadian 

geophysicist.

2

American Geosciences Institute (AGI) Glossary of Geology 

online at http://www.agiweb.org/pubs/glossary/.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 17

Introduction

The USGS methodology to assess undiscovered mineral 

resources has three essential parts: (1) frequency distributions of tonnages and average grades of well explored 

deposits that are used as grade and tonnage models of 

undiscovered deposits of the same type in geologically 

similar settings, (2) mineral resource maps that show tracts 

where geology permits the existence of deposits of one or 

more specified types, and (3) estimates of some fixed, but 

unknown, number of undiscovered deposits that exist in the 

delineated tracts (Singer, 1993; Singer and Menzie, 2010). 

This chapter describes grade and tonnage models developed 

for sediment-hosted stratabound copper (SSC) deposits.

Deposit models specific to mineral deposit types are an 

integral part of the assessment process because they summarize geologic criteria used for classifying the deposits by type 

and for delineating permissive geographic areas (tracts) for the 

occurrence of undiscovered deposits. Deposits of a given type 

have characteristic sizes and grades that can be expressed as 

frequency distributions of tonnage and average grade on the 

basis of thoroughly explored examples of each type of mineral 

deposit. These grade and tonnage models can be illustrated 

with cumulative frequency plots, as well as with histograms, 

quantile box plots, and normal quantile plots (fig. 2-1). The 

grade and tonnage distributions of known deposits are used to 

constrain the probable size and grade of undiscovered deposits 

of the same type—undiscovered deposits are expected to be 

comparable to those in the grade and tonnage model for the 

deposit type.

Grade and tonnage models for various types of SSC 

deposits have been previously published. Mosier and others 

(1986) used data for 57 deposits to create a tonnage and grade 

model for sediment-hosted copper (equivalent to SSC deposits 

as used in this report). The descriptive (Cox, 2003c) and tonnage and grade models (Cox and Singer, 2003a) were revised 

using data for 135 deposits. On the basis of geologic characteristics, those authors distinguished three types of sedimenthosted copper and published tonnage and grade models for (1) 

reduced-facies copper (Cox, 2003a), with 62 deposits (Cox and 

Singer, 2003c); (2) red bed copper (Lindsey and Cox, 2003), 

with 33 deposits (Cox and Singer, 2003b); and (3) Revett copper (Cox, 2003b), with 14 deposits (Cox and Singer, 2003d). 

Silver was included in the models for all three types of deposits; cobalt was included only in the reduced-facies type.

This study extends the work of Mosier and others (1986) 

and that of Cox (2003a,b), and Lindsey and Cox (2003). For 

this report, grade and tonnage information was collected for 

approximately 200 sediment-hosted copper deposits with 

published tonnage and grade information in about 30 sedimentary basins worldwide (fig. 1-1 and table 2-1) (table 2-1 of this 

report is seen online only). The data for the Central African 

Copperbelt (CACB) are based on Wilson and others (appendix 

A, this report) and Parks and others (appendix B, this report). 

After screening the data, 170 SSC copper deposits were 

selected for grade and tonnage modeling.

Definition of SSC Deposit Types 

Mineral deposits must be clearly defined if they are 

going to be used for mineral resource modeling. For inclusion in a tonnage and grade model, a mineral deposit should: 

(1) have economic potential (Cox and others, 1986); (2) form 

by the same genetic process and be the same deposit type 

as other sites used to construct the same model (Barton and 

others, 1995); and (3) be developed using similar mining and 

processing methods as other sites in the model (Bliss and 

others, 1987). 

According to Singer (1995), sediment-hosted copper 

deposits account for more than 20 percent of all copper that 

has been discovered. Production has come from a few large 

districts in the Democratic Republic of the Congo, Germany, 

Kazakhstan, Poland, and Zambia. SSC deposits are mined 

using a variety of mining (open pit, underground room and pillar) and beneficiation (pyro- and hydrometallurgy) methods. 

Shared geologic characteristics form the basis for grouping deposits into types, such as SSC, that formed in the same 

geologic setting and through similar geological processes (fig. 

2-2). SSC deposits are diagenetic in timing and epigenetic in 

origin (Zientek and others, this report, chapter 1). The deposits 

consist of fine-grained copper and copper-iron sulfide minerals that occur as stratabound to stratiform disseminations in 

siliciclastic or dolomitic sedimentary rocks. Ore minerals 

occur as cements and replacements, or rarely, as veinlets. The 

concentration of sulfide minerals conforms closely, but not 

exactly, with the stratification of the host rocks. These deposits 

are characterized by zoning of ore minerals laterally along and 

across bedding: from pyrite to chalcopyrite to bornite to chalcocite to hematite. Chalcocite- and bornite-rich rocks typically 

constitute the ore zones.

Chapter 2. Grade and Tonnage Relations for Sediment-Hosted 

Stratabound Copper Deposits 

By Michael L. Zientek, Timothy S. Hayes, and Cliff D. Taylor
18 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Sediment-hosted

copper deposits

Sediment-hosted stratabound copper deposits

(SSC)

SSC-CACB

Structurally controlled 

replacement and vein 

copper deposits

(SCRV)

Marine flooding suface

and in-situ organic material Reservoir-facies sandstones

Mobile reductant Plant debris

Sandstone copper Red-bed copper

Sandstone copper—

Roan arenite

Unbroken Solution breccia

Reduced-facies—

nonbrecciated

(n.b.)

Reduced-facies—

carbonate écaille

* Regional variant—Central African Copperbelt (CACB)

*

*

Figure 2-2. Chart illustrating the relations among types of sediment-hosted copper deposits.

Normal quantile plot

0.95

-0.5

-0.3

-0.1

0.1

0.3

0.5

0.7

0.9 -2.33 -1.64 -1.28 -0.67 0.0 0.67 1.28 1.64 2.33

0.05 0.2 0.5 0.8

I

H

G

F

H

D

E

A

B

C

Log copper grade, in percent

Probability score

Normal quantile score

EXPLANATION

Upper quartile

Median

Lower quartile

Shortest half

Confidence interval on the mean

Mean is intersection of line with

 normal quantile score = zero

Slope is standard deviation

Confidence interval for normality

Data values

F

E

H

I

C

D

G

B

A

CACB fig 2-1

Figure 2-1. An example of 

histogram, box plot, and normal 

quantile plots illustrating the 

distribution of log-transformed 

values for copper grade of 187 

sediment-hosted copper deposits. 

Shortest half is a bracket showing 

the densest 50 percent of the 

observations. The probability 

scale is the empirical cumulative 

probability for each value. The 

normal quantile scores are 

computed by the formula: 

-1(ri 

⁄ (N+1), where is the 

cumulative probability distribution 

function for the normal 

distribution, r

i

 is the rank of the i th 

observation, and N is the number 

of nonmissing observations.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 19

 Within a type, deposits can be further subdivided into 

smaller groups based on geology or distinct tonnage and grade 

characteristics. For example, the geologic setting between 

groups may be such that they would correspond to different 

areas on mineral potential maps. Previous workers distinguish 

two types of SSC deposits on the basis of the rocks hosting the 

deposits: (1) sandstones (Dzhezkazgan deposits of Bogdanov 

and others, 1973; continental red bed deposits of Kirkham, 

1989 and Kirkham and others, 1994; and red bed deposits of 

Hitzman and others, 2005); and (2) shales and marls (copper 

shale deposits of Bogdanov and others, 1973; paralic marine 

deposits of Kirkham, 1989 and Kirkham and others, 1994; 

reduced-facies deposits of Cox and others, 2003; Kupferschiefer deposits of Hitzman and others, 2005; and reduced 

-facies—nonbrecciated deposits of this study).

The sandstone-hosted deposits have been divided still 

further into two additional types based on the nature of the 

organic material that localizes ore minerals in the rock: (1) 

patchy concentrations of plant remains (the Uralian deposits of 

Bogdanov and others, 1973; red bed deposits of Lindsey and 

Cox, 2003); and (2) a diffusely distributed reductant, probably a 

mobile hydrocarbon (Revett deposits of Cox and others, 2003; 

sandstone copper, this study). Deposits of the red bed copper 

type of Lindsey and Cox (2003) were excluded from this study; 

although they are commonly found as mineral occurrences, few 

sites have formally reported tonnage and grade. Only 3 of the 

20 deposits in the model developed by Lindsey and Cox (2003) 

contain more than 50,000 metric tons contained copper (a significant copper deposit as defined by Singer, 1995). Deposits of 

the red bed copper type of Lindsey and Cox (2003) are interesting because they indicate the presence of copper-bearing fluids 

in sedimentary basins, but their contribution to global mineral 

endowment is negligible and such deposits are not sought out by 

companies conducting minerals exploration.

Deposits of a given type also can be subdivided based 

on regional differences in their tonnage and grade distributions. This has been done for podiform chromite deposits 

(major and minor podiform chromite, Singer, Page, and Lipin, 

1986; Singer and Page, 1986), volcanogenic massive sulfide 

deposits (kuroko massive sulfide and Sierran kuroko massive 

sulfide; Singer and Mosier, 1986; Singer, 1992), and porphyry 

copper deposits (all and giant porphyry copper deposits, 

Singer and others, 2008; Singer, Briskey, and Cunningham, 

2008). Deposit types with different grade and tonnage models 

probably have different economic values. Our colleagues in 

academia and industry suggest that SSC deposits in the CACB 

in the Katanga Basin have higher copper grades than deposits 

found elsewhere (figs. 2-3 and 2-4). The data set was divided 

into two groups—one for SSC deposits found in CACB (78 

deposits) and those found elsewhere (92 deposits). Copper grade data (expressed in logarithms) for each group was 

tested for normality and variance homogeneity before being 

compared using a t-test. The results rejected the assumption 

that both groups have a same copper grade at the 1-percent 

confidence level (fig. 2-5). Median and mean copper grades 

for the CACB deposits are 2.70 and 2.96 percent, respectively, 

compared to median and mean grades of 1.17 and 1.23 percent 

copper, respectively, for deposits elsewhere. Many deposits in 

the CACB contain cobalt, but few report data for silver grades; 

some deposits in other parts of the world contain elevated 

levels of silver but few report data for cobalt grades. Both 

reduced-facies- and sandstone-copper deposits are present in 

the CACB; two regional grade and tonnage models for SSC in 

the CACB were developed.

In this report, SSC deposits are subdivided into types (fig. 

2-2) based on (1) host rocks, reductants, and the effect of salt 

tectonics on the deposit and (2) regional differences in copper 

grade as follows:

• Sediment-hosted stratabound copper deposits 

 (all 170 deposits).

• Reduced-facies deposits that are not in salt solution

 breccias (50 of the 170 SSC deposits; 10 in the

 CACB and 40 elsewhere): reduced-facies—

 nonbrecciated, henceforth “reduced-facies—n.b.”

• Reduced-facies deposits that occur in salt dissolution breccias (49 of the 170 SSC deposits; 47 in the 

CACB and 2 in Australia): “reduced-facies—carbonate écaille.” 1

• Sandstone copper deposits (70 of the 170 SSC 

deposits; 20 in the CACB and 50 elsewhere): “sandstone copper.”

• Sandstone copper deposits in the Roan Series, 

Zambia (20 of the 70 sandstone copper deposits): 

“sandstone copper—Roan arenite.”

Reduced-Facies—Nonbrecciated (n.b.) Deposits

Reduced-facies copper deposits are hosted by black to 

gray to green marine or lacustrine shale, siltstone, mudstone, 

or carbonaceous dolosiltstone/siliceous dolomite containing 

solid amorphous organic matter. Host beds for many reducedfacies deposits occur at or just above the flooding surface that 

marks the transgression between a marine, upward coarsening, sag basin depositional sequence and underlying synrift, 

1

Breccias derived from specific stratigraphic units in the Roan Group in the 

Democratic Republic of the Congo are spectacular because the clasts range 

between 1 meter (m) and 10 kilometers (km) in size. For a “megabreccia,” the 

largest dimension of clasts is 100 to 400 m (American Geosciences Institute 

(AGI) Glossary of Geology online at http://www.agiweb.org/pubs/glossary/). 

Jackson and others (2003) coined the term “gigabreccia” for breccias in which 

the clasts are 1 km or more in size. In French geologic literature, these large 

breccia fragments are referred to as “écailles,”meaning “scales.”
20 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

5

6

7

8

9

10

−0.2

−0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Adelaide Geosyncline/

Stuart Shelf

Adelaide Geosyncline/

Willouran Trough

Anti Atlas

Chu-Sarysu

Dongchuan

Ghanzi-Chobe

Jafr-Tabuk-Sinai

Katanga

Keewenawan

Permian

Redstone

Santa Rosalia

Zechstein

Kwanza

Guanxi-Guizhou

Log copper grade, in percent

Adelaide Geosyncline/

Stuart Shelf

Adelaide Geosyncline/

Willouran Trough

Anti Atlas

Chu-Sarysu

Dongchuan

Ghanzi-Chobe

Jafr-Tabuk-Sinai

Katanga

Keewenawan

Permian

Redstone

Santa Rosalia

Zechstein

Kwanza

Guanxi-Guizhou

Log ore, in metric tons

Basin

Basin

CACB g 2-3

Figure 2-3. Quantile box plots showing the variation in log ore, tonnage, and log copper grade by basin for 

reduced-facies copper deposits.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 21

5.5

6

6.5

7

7.5

8

8.5

9

9.5

Basin

Log ore, in metric tons

Adelaide Geosyncline/Stuart Shelf

Belt

Chu-Sarysu

Chuxiong

Damara

Deweras Group

Ghanzi-Chobe

Guanxi-Guizhou

Hengyang

Jafr-Tabuk-Sinai

Jiangna-South Jiangsu Fold Belt

Katanga

Kodar-Udokan

Komagfjord-Repparfjord Greenstone Belt

Neuquen

Paradox

Salta

−0.5

−0.3

−0.1

0.1

0.3

0.5

0.7

Basin

Log copper grade, in percent

Adelaide Geosyncline/Stuart Shelf

Belt

Chu-Sarysu

Chuxiong

Damara

Deweras Group

Ghanzi-Chobe

Guanxi-Guizhou

Hengyang

Jafr-Tabuk-Sinai

Jiangna-South Jiangsu Fold Belt

Katanga

Kodar-Udokan

Komagfjord-Repparfjord Greenstone Belt

Neuquen

Paradox

Salta

CACB g 2-4

Figure 2-4. Quantile box plots showing the variation in log ore, tonnage, and log copper grade by basin 

for sandstone copper deposits.
22 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

5

6

7

8

9

10

CACB Not CACB

CACB/Not CACB

All Pairs

Tukey-Kramer

0.01

−0.5

−0.3

−0.1

0.1

0.3

0.5

0.7

0.9

CACB Not CACB

CACB/Not CACB

All Pairs

Tukey-Kramer

0.01

Log ore, in metric tons Log copper grade, in percent

Figure 2-5. Plot showing mean diamonds and comparison circles for the distribution of logtransformed values of copper grade and ore tonnage between the sediment-hosted stratabound 

copper deposits in the Central African Copperbelt (CACB) and all other areas in the world. If the 

confidence intervals shown by the means diamonds do not overlap, the groups are significantly 

different. See Sall and others (2007) for explanation of comparison circles.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 23

nonmarine red beds. Depositional environments hosting 

reduced-facies mineralization above the transgressive surface 

include open marine shelf black shale, coastal sabkhas, and 

subtidal shelf carbonates. Reduced-facies deposits have sheetlike geometry with lateral dimensions from hundreds to thousands of times greater than thicknesses. For example, strike 

lengths may be on the order of 3,000 to 5,000 meters (m), with 

widths of 500 to 2,000 m and ore thicknesses ranging from a 

few meters to 50 m. Examples of giant or world-class deposits 

are summarized in table 2-2. Permissive tracts for reducedfacies deposits should be based on the extent of a major flooding surface that immediately overlies red beds.

Reduced-facies deposits in the CACB occur in the Ore 

Shale Formation in the Zambian portion of the CACB (fig. 

2-6; Annels, 1984 and 1989) and have elevated copper grades 

relative to many reduced-facies deposits in other sedimentary 

basins. These deposits occur in the Ore Shale Formation of the 

Kitwe Subgroup (fig. 2-7) and form large, continuous, highgrade deposits that have been affected by lower greenschist to 

upper amphibolite facies metamorphism and complex folding 

(Selley and others, 2005). Like other reduced-facies deposits, 

the deposits in Zambia are associated with the major flooding surface that deposited marine black shales on continental red beds and are localized at stratigraphic pinchouts, at 

basement highs, and in structural traps. A separate grade and 

tonnage model cannot be created because there are not enough 

examples of this style of mineralization. They are included in 

the reduced-facies—n.b. model.

Reduced-Facies—Carbonate Écaille Deposits

Reduced-facies deposits hosted by Kamoto, Dolomitic 

Shales, and Kambove Formations of the Mines Subgroup, of 

the Roan Group, CACB (figs. 2-8 and 2-9) occur in gigabreccia 

fragments ranging in size from about a meter to 10 kilometers 

(figs. 2-10 and 2-11; François, 1973; François and Cailteux, 

1981; Jackson and others, 2003). In French, these gigabreccia 

fragments are referred to as “écailles”, meaning “scales”. The 

primary stratabound ore body geometry is preserved in the breccia fragments and pre-dates folding and brecciation.

The stratigraphic section hosting the mineralized layers 

appears to have been interlayered with salt beds (Jackson and 

others, 2003). After the copper-mineralizing event, deformation of the salt layers formed diapirs, salt walls, extrusions, 

thrust sheets, and fault-cored anticlines above a regional 

detachment surface produced by thrust faulting during the 

Lufilian orogeny (Garlick and Fleisher, 1972; Jackson and others, 2003). During halokinesis, rock units hosting the mineralized layers, dolomitic formations or other competent units, 

were broken into fragments and the salt was dissolved. The 

resulting dissolution breccias host the mineralized strata.

Compared to reduced-facies deposits outside the CACB, 

the reduced-facies deposits hosted by the Mines Subgroup 

breccias have higher copper grades. The occurrence of the 

deposits in gigabreccia fragments imparts a secondary control 

on the tonnage distribution of these reduced-facies deposits. 

A separate reduced-facies grade and tonnage model, reducedfacies—carbonate écaille, was created for use in mineral 

resource assessment. These deposits are excluded from the 

reduced-facies—n.b. model. Examples of giant or world-class 

deposits are summarized in table 2-2.

Sandstone Copper Deposits

Sandstone copper deposits are hosted in gray, wellsorted, fine- to coarse-grained, locally conglomeratic 

sandstone, which is characterized by cross bedding, parallel 

lamination, mud rip-up clasts, and ripple marks. Sandstone 

copper host rocks are typically well-sorted siliciclastic 

sandstones from a variety of deltaic topset environments that 

make up the upper part of the coarsening upwards depositional cycles. Sandstone copper deposits are tabular to 

lens-like; lateral dimensions are from 20 to 100 times their 

thicknesses. These rocks were probably reservoir rocks for 

petroleum when the copper minerals were deposited. For 

many sandstone copper deposits, petroleum was probably 

present as sour gas (Hayes and others, 2012). Structural traps 

that allow the accumulation of hydrocarbons in sedimentary 

basins may localize deposition of sediment-hosted copper 

mineralization. Permissive tracts for sandstone copper deposits should delineate reservoir rocks within a basin hosting 

red beds, hydrocarbon source beds, and evaporites. Worldclass deposits include Dzhezkazgan and Zhaman-Aibat in 

Kazakhstan, Udokan in Russia, and Rock Creek/Montanore 

in Montana (table 2-2).

In the CACB, sandstone copper deposits are found in 

coarser-grained siliciclastic rocks above and below the Ore 

Shale Formation of the Kitwe Subgroup (fig. 2-12), and in 

dolomitic siltstone that is a lateral facies equivalent to the 

Ore Shale Formation. Like other sandstone copper deposits, they occur in reservoir facies rock types in stratigraphic 

and structural traps similar to those that collect oil and gas. 

Compared to other sandstone deposits outside the CACB, they 

have higher copper grades. A regional variant of the sandstone 

copper grade and tonnage model, sandstone copper—Roan 

arenite, was created for use in mineral resource assessment of 

undiscovered deposits in the Roan Series in Zambia. These 

deposits are not excluded from the sandstone copper model. 

Mufulira, Zambia, is the only giant or world-class deposit in 

this regional model (table 2-2). 

Deposit Definition

For grade and tonnage models, the grade and tonnage data associated with a deposit should represent similar 

sampling units. The tonnage and grade data should (1) be an 

estimate of pre-mining, in-situ mineral endowment; (2) use 

a consistent cutoff grade; and (3) represent a well-explored 

deposit (Singer and Menzie, 2010). Finally, rules are used to 

consistently define how ore bodies are spatially grouped into 
24 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

27°45'E 28°00'E 28°15'E 28°30'E

12°45'S

12°30'S

12°15'S

13°00'S

0 5 10 MILES

0 10 20 KILOMETERS

Kalulushi

Mufulira

MOKAMBO

DOME

K A F U E A N T I C L I N E

ROAN BASIN

Kitwe

Chabwanyama Gap

ZAMBIA

DEMOCRATIC REPUBLIC 

OF THE CONGO

KONKOLA BASIN

Luanshya

CHAMBISHI

BASIN

Chingola

Chililabombwe

EXPLANATION

Political boundary

Roan-basement unconformity

City

Nchanga red granite

Littoral facies

Basement

Transition facies

Carbonaceous facies

Ore Shale Formation

Figure 2-6. Geologic map showing the distribution of the Ore Shale Formation of the Roan Group in Zambia. Modified from Annels (1984).
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 25

EXPLANATION

Siltstone-shale

Diamictite

Carbonate

Breccia

Gritty siltstone

Mixed carbonate-

 siliciclastic

Sandstone

Basement gneiss

Conglomerate

Intrusive gabbro

Mixed sandstone-

 siltstone-carbonate

Nchanga red granite

Main orebearing

Kirilabombwe

Subgroup

Ore Shale Formation

Nguba Group

500

877+/-11Ma

~740Ma

interval

Grand

Conglomerate

Mwashia

Subgroup

Mindola

Subgroup

Kitwe

Subgroup Basement

Evaporitic depositional environments

0

Group Subgroup Lithology Other information Roan Group

METERS

0

800

1,600

FEET

250

CACB g 2-7

Figure 2-7. Stratigraphic column of the Roan Group exposed in the Zambian part of the Central African 

Copperbelt. Reduced-facies copper mineralization is associated with the Ore Shale Formation. Modified from 

Selley and others (2005).
26 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits Mineralization

0

500

1,000

0

2,640

METERS

FEET

1,320

EXPLANATION

Mixtite 

Coarse sandstone 

Shale

Dolomite/limestone

Siltstone/fine sandstone

Cu mineralization

Local names

Calcareous

cherts

Oolitic limestone

Kakontwe limestone

Grand conglomerate

Mwashya

Dipeta

C.M.N.

R.A.T.

Petite conglomerate

Pink limestone

Sandstone plateaus

Ribbon shales

R.S.F. and R.S.C.

S.D.

Description

Shale and dolomitic sandstone

Arkose and dolomitic sandstone

Dolomitic shales and fine sandstone

Mixtite

Dolomitic shales and 

fine sandstone

(Greywacke)

Shale with massive geodes

Limestone or dolostone

(Greywacke)

Mixtite

Dolomitic shales and carbonates

and siliceous dolomites

Mix of dolomite and dolomitic

argillaceous-siltstone

Argillaceous-silty dolomite

Dolomitic shales

Dolomitic argillaceous-siltstone

Thin shales

Argillaceous-silty dolomite

Feldspathic sandstone

2.2

2.1

1.3

1.2

1.1

1.3

1.2

1.1

4.2

4.1

2.3

2.2

2.1Formation

Group

Ks 3

Ks 2

Ks 1

Ki 2

Ki 1

R 4

R 3

R 2

R 1

Supergroup

Kundelungu

Superior -

Ks

Kundelungu

Inferior -

Ki

Roan - R

Lithology

Figure 2-8. Stratigraphic column of the Katangan system, illustrating the location of 

mineralized strata. The reduced-facies-carbonate écaille mineralization is associated with the 

Mines Group (R2) in the Roan Supergroup. Gaps in the Roan section indicate where evaporate 

may have been present. Stratigraphic abbreviations: C.M.N.—“cálcaire á minerais noirs” (black 

limestone ore); S.D.—“schistes Dolomitiques” (dolomitic shales); R.S.F.— “roches siliceuses 

feuilletées“ (laminated siliceous rocks), and R.S.C.— “Roches Siliceuses Cellulaires“ (cellular 

siliceous rocks), and R.A.T.— “roches argilo-talqueuses” (clayey talcose rocks). Modified from 

François (2006).
5% 5 10% 5% 5 10% 5% 

5 5 10

Cobalt grade, 

in percent

Coper grade, 

in percent

SOUTH

Irregular Ni and Co 

mineralization

Shinkolobwe Kambove Fungurume Kabwe 

Subgroup

Kamoto

R 2.1

R.A.T.

R 1

Mines R 2

Dolomitic 

Shales (S.D.)

R 2.2

2.1.22.1.32.2.12.2.22.2.32.3.1 Kambove R 2.3 C.M.N.

R.S.C.

R.S.F.

D. Strat.

R.A.T.

R.A.T. grises

Formation Code

Group Roan R

Dark grey argillaceous sandstoneBlack argillaceous sandstoneGrey or greyish green  siltstone-sandstone, Finely layered siliceous dolomiteStratified dolomiteStromatolitic dolomiteSiliceous dolomite-massive breccia

Arkosic dolomitic sandstone

Thin grey chloritic-dolomitic  sandstone

Lilac or red hematitic  dolomitic sandsoneCo mineralizationCu mineralization

EXPLANATION

Figure 2-9. Stratigraphic columns showing distribution of reduced-facies-carbonate écaille copper mineralization in the Mines Subgroup into an uin the Central African Copperbelt in the Democratic Republic of the Congo. Stratigraphic abbreviations: C.M.N.— “cálcaire á minerais noirs” (black “Roches Siliceuses Cellulaires“ (cellular siliceous rocks), R.S.F.— “roches siliceuses feuilletées“ (laminated siliceous rocks), D. strat—“dolomies sdolomites), R.A.T. grises—“roches argilo-talqueuses grises” (gray clayey talcose rocks), and R.A.T.— “roches argilo-talqueuses” (clayey talcose roFrançois (2006).
B A A B Oliveira Variante FNSR OEUF Virgule Oliveira VarianteFNSR Musonoi OEUF Virgule Kamoto East Kamoto North Kamoto Principal 25°25'E 25°26'E 10°42'S 10°43'S 0 1,000 2,000 FEET 0 400 800 METERS Dipeta F

Kambove DolomitiUpper orLower o

EXP

Cover Roan bre

20°E 

6°S 12°S DEMOCRA

OF TH

ANGOLA 

Figure 2-10. Geologic map and cross section of the Kamoto-Oliveira-Virgule (KOV) ore body that shows large gigabreccia fragments (écaille) of Roareduced-facies mineralization. On the map and section, each fragment is named (for example, Musonoi or Virgule). See figure 2-7 for stratigraphic nModified from Dixon (2007).
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 29

Figure 2-11. Geologic map of the Tenke-Fungurume area showing exposures of Roan gigabreccia and megabreccia in the 

Central African Copperbelt. The uppermost Roan (R4) is concordant with the overlying Nguba and Kundelungu Groups. In the 

center of the map, large breccia fragments consisting of the R2 stratigraphic unit occur in a matrix of pelite or a dolomitic, 

chloritic, talcose siltstone (labeled R). Modified from Jackson and others (2003).

Area of map
Roan Group EXPLANATION Siltstone-shale Carbonate Gritty siltstone Sandstone Basement gneiss Conglomerate Mixed sandstone- siltstone-carbonate Nchanga red granite Argillite-hosted Arenite-hosted Mixed argillite-arenite Basement-hosted Cu ± Co Mineralization Ore Shale Formation (and equivalents) Reduced-facies subtype Sandstone subtype " Sediment-hosted stratabound copper deposit Roan Group Mindola Subgroup Kitwe Subgroup Basement 5000 METERS 0800 1,600 FEET 250

Baluba

Chambishi Basin Luanshya Basin Nchanga-Chingola district Konkola district 

Luanshya

Mindola

Nkana Area K

Chambishi SE

Chambishi

Chibuluma East

Chibuluma West

Chibuluma South

Mwambashi B

Pitanda

Fitula

Mimbula

Chingola A and C

Chingola B

Chingola D

Chingola E

Chingola F

Nchanga

Kirila Bombwe 

South No. 1

Konkola West

Musoshi

Bwana Mkubwa

Group Subgroup Lithology

"

"

"

"

""""""

"

"

"

"

"

"

"

"

"

"

"

"

"

"

Chingola areas 

A, B, C, D, E, 

and F

Fitula

Balu

Mimbula Pitanda

Nchanga

Musoshi

Mindola

Lubembe

Muf

Luan

Chambishi

Mwambashi B

Nkan

Konkola West

Chibuluma

East

Chibuluma West

Chibuluma South

KasariaLuansobe

Chambishi Sou

Kirila Bomwe

South No.1

Chambishi

Basin

Nchanga-Chingola

district

Konkola

district

0 10 20 KILOMETERS0 5 10 MILES

28°0'E 

12°30'S

13°0'S

D

Figure 2-12. Stratigraphic column of the Roan Group exposed in the Zambian part of the Central African Copperbelt showing the stratigraphic distri(argillite-hosted and mixed argillite-arenite) and sandstone (arenite-hosted) mineralization. Modified from Selley and others (2005).
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 31

Table 2-2. Sediment-hosted stratabound copper deposits containing more than two million metric tons of 

copper (equivalent to giant deposit category of Singer, 1995).

[t, metric tons; DRC, Democratic Republic of the Congo; n.b., nonbrecciated]

Name Basin Country Contained copper metal (t)

Reduced-facies—carbonate écaille

DIMA Katanga DRC 7,800,000

Fungurume Katanga DRC 2,800,000

Kambove Principal-Kambove West Katanga DRC 3,100,000

Kamoto-KOV-Musonie-Mupine Katanga DRC 19,000,000

Kansalawile-Mambilima Katanga DRC 2,800,000

Kimbwe Katanga DRC 2,000,000

Kinsevere Katanga DRC 2,100,000

Kwatebala Katanga DRC 2,200,000

Mutanda Ya Mukonkota Katanga DRC 3,700,000

Tenke Katanga DRC 2,500,000

Reduced-facies—n.b.

Baluba-Muliashi-Luanshya Katanga Zambia 10,000,000

Boleo (0.5 cutoff) Santa Rosalia Mexico 3,600,000

Chambishi Main and West Katanga Zambia 2,900,000

Chambishi Southeast Katanga Zambia 3,800,000

Chingola-Nchanga Katanga Zambia 16,000,000

Kalumbila Katanga Zambia 2,700,000

Konkola-Musoshi Katanga Zambia 22,000,000

Lubin-Sieroszowice, Zechstein Poland 72,000,000

Mansfeld Zechstein Germany 2,000,000

Mindola-Nkana N-S Katanga Zambia 15,000,000

White Pine Keewenawan United States 8,300,000

Sandstone copper

Dzhezkazgan Chu-Sarysu Kazakhstan 22,000,000

Mufulira Katanga Zambia 8,900,000

Rock Creek/Montanore Belt United States 2,400,000

Udokan Kodar-Udokan Russia 19,000,000

Zhaman-Aibat Chu-Sarysu Kazakhstan 2,700,000
32 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

a deposit for modeling purposes (Singer and Menzie, 2010). 

Unfortunately, data about mineral deposits rarely meet all of 

these requirements. 

Mineral Endowment

For modeling purposes, the original mineral deposit size 

and grade is estimated by combining past production with 

estimates of remaining in-place mineral resources. Published 

production information includes data such as the mass of ore 

mined or processed, average grade, and/or total amount of 

material produced. Information on mining and beneficiation 

losses is seldom reported; therefore, the production information used to estimate pre-mining mineral endowment is not 

adjusted for these losses. Estimates of remaining, in-place 

mineral resources are based on reported mineral inventory for 

a deposit. The inventory is a formal quantification of naturally 

occurring materials, estimated by a variety of empirically or 

theoretically based procedures (Sinclair and Blackwell, 2006). 

These resources exist for a specified economic condition and 

currently feasible or near-feasible technology of production 

(Harris, 1984).

Mineral inventories reported before the late 1990s generally do not report the quality and quantity of data, the procedures used to make the estimate, or the economic assumptions. 

Beginning in the late 1990s, international standards require 

detailed reporting of the assumption and methods used in 

estimating mineral inventory (Committee for Mineral Reserves 

International Reporting Standards, 2006, or Securities and 

Exchange Commission Industry Guide 7 (http://web.cim.org/

standards/documents/Block474_Doc32.pdf, accessed February 28, 2012). The data used in this compilation are a mix of 

historical information with little or no supporting material 

and modern, regulatory compliant reports that provide good 

documentation. For deposit data that conform to Committee for Mineral Reserves International Reporting Standards 

(CRIRSCO) standards, the weighted average is calculated 

using all exclusive reserve and resource categories, including 

inferred resources.

Cutoff Grade

Cutoff grade is the lowest grade, or quality, of mineralized material that qualifies as economically mineable and 

available in a given deposit (Committee for Mineral Reserves 

and Reporting Standards, 2006). Cutoff grade is used to 

separate two courses of action, to mine or to leave, to mill or 

to dump; also, cutoff grade is any of a series of grades used to 

truncate a frequency distribution, or to separate mineralized 

materials into graded fractions (Taylor, 1972). In order to economically evaluate mineral deposits, grades and tonnages may 

be reported at various cutoff grades. In addition, different mining methods based on different cutoff grades may be employed 

on the same deposit and will affect the production tonnages.

Ideally, estimates of deposit grades and tonnages used in 

models would be based on the same cutoff grade. Commonly, 

various values have been used for cutoff grade, which introduces ambiguity in model development. When possible, tonnage and grade at the lowest cutoff grade are used for modeling 

grade and tonnage distributions (Singer and Menzie, 2010). 

For SSC deposits, the cutoff can be based on copper 

grade, silver grade, or net-smelter return (table 2-1). For most 

of the deposits where cutoff is reported, copper grade is used; 

values range from about 0.3 to greater than 1.0 weight percent 

copper. The Rock Creek/Montanore deposit in Montana uses a 

cutoff grade of 1 ounce per ton of silver. Other sites use cutoff 

grades based on the values of all metals, expressed either 

as copper equivalent values (Boleo, Mexico) or net-smelter 

return (Troy, Montana). 

Exploration

The sites with modern CRIRSCO-compliant mineral 

inventories are well-explored by surface sampling and drilling. 

The historical resource numbers, before enhanced reporting 

requirements were established in the late 1990s, are probably 

based on drilling data. Most sites in the compilation probably 

have potential for reserve growth.

Spatial Rules for Aggregation

Grade and tonnage data are available to varying degrees 

for districts, deposits, mines, and shafts. Spatial aggregation 

rules are developed to try to insure that deposits in grade and 

tonnage and spatial density models correspond to deposits as 

geologic entities. These rules are essential in order to ensure 

an internally consistent assessment system in which the estimated number of undiscovered deposits is consistent with the 

grade and tonnage model (Singer and Menzie, 2010).

Spatial rules are used in the development of several grade 

and tonnage models. For the volcanogenic-massive sulfide 

deposit model, all mineralized rock within 500 m is combined 

into one deposit (Mosier and others, 2009). For the porphyry 

copper deposit and the sediment-hosted lead-zinc deposit models, all mineralized rock or alteration within 2 kilometers (km) is 

combined into one deposit (Singer and others, 2008; Singer and 

others, 2009). For the purposes of grade and tonnage modeling, 

Cox and other (2003) defined a sediment-hosted copper deposit 

as one or more separate ore bodies separated from its nearest 

neighbor by more than 2,000 m. However, these studies did not 

define what is meant by mineralized rock, alteration, or ore body, 

or explain how the value for spatial aggregation was determined.

The presence of mineralized rock and an associated 

alteration zone is a difficult criterion to apply to sedimenthosted copper deposits. Masses of rock for which mineral 

inventory has been reported are typically contained within 

broad zones of weakly mineralized rock that extend hundreds 

to thousands of meters away from the ore body. Alteration 

associated with sediment-hosted copper deposits affect large 
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 33

volumes of the enclosing rocks and form systems that may 

extend tens of kilometers and possibly as much as 100 km 

laterally, and commonly affect more than 1 km of sedimentary rock thickness.

To determine spatial rules for aggregation, the ore body 

is defined as the volume of mineralized rocks for which a 

tonnage and grade has been determined. Using this definition, 

the shape of an ore body reflects geologic contacts, economic 

cutoff limits, and property boundaries. Maps showing the surface projection of the volume of rock associated with a given 

tonnage and grade estimate were found for approximately 30 

percent of the deposits considered in this study; these sites are 

biased towards large deposits and those found in the CACB. 

Ore body outlines were found for approximately 40 sites in 

the CACB and approximately 20 sites in 6 other basins. For 

the remainder of the sites, a point is used to approximate the 

location of the deposit. 

The spatial aggregation rule is constructed on the basis 

of deposits in the CACB, which has the highest density of 

sediment-hosted stratabound deposits in the world. The location of deposits was estimated from the spatial database of the 

surface projection of ore bodies (appendix B, this report). If 

an ore body was not specifically represented by a polygon in 

the GIS, open pit outlines were used as a surrogate (appendix 

B, this report). The nearest distance between the edges of all 

pairs of ore body/open pit polygons that occurred within a 5 

kilometer radius of each other in the CACB was calculated 

using spatial analysis tools in ArcGIS. Histograms and normal 

quantile plots showed a maximum in the histogram and a slope 

break in the quantile plots that was used to select an aggregation distance of 500 m between ore body polygons (fig. 2-13). 

The same aggregation distance for ore body polygons is used 

in other sedimentary basins.

The diameter of the median ore body areas should 

provide a rough approximation for the aggregation distance 

between points representing a deposit location. The median 

area of deposits with ore body polygons is 1.27 square 

kilometers (km2

). Using the positive correlation between ore 

tonnage and the area of an ore body, values for ore body area 

were imputed where that information is missing (fig. 2-14). 

Integrating the imputed values into the calculation lowers the 

median size of a sediment-hosted copper ore body to 0.38 km2. 

If a circular ore body outline is assumed, the estimated median 

diameter is 700 m, similar to the 500-m value determined 

when measuring edge to edge of deposit polygons. 

For the global dataset, the 500-m aggregation rule was 

used, measuring either from the edge of a deposit polygon or 

between points representing deposit locations. Aggregated 

locations were given a new point location for the group (see 

site status in table 2-1). The sensitivity of the aggregation 

process was tested by determining how many additional sites 

would be aggregated if a spatial rule of 700 m and 1,000 m 

was applied to the deposit points. At 700 m, no additional 

points would be aggregated. At 1,000 m, only one additional 

pair of deposits would be aggregated.

Data Quality Assessment

Just as 95% of research efforts are devoted to data 

collection, 95% of the time remaining should be 

spent ensuring that the data collected warrant 

analysis (Good and Hardin, 2009, p. 51).

The tonnage and grade database review includes (1) 

calculating the minimum and maximum values of the data 

to ensure that they are geologically feasible; (2) checking 

deposit type classification using descriptive information 

and geologic maps and excluding deposits that are not of 

the appropriate type; (3) eliminating duplicates from the 

database; (4) identifying sites that are explicitly described 

as being incompletely explored; and (5) verifying that 

the spatial aggregation rule of 500 m is correctly applied. 

Deposits that are not SSC deposits (for example, the Nama 

cobalt-copper deposits in the CACB, appendix A, this report) 

and sites that could not be characterized by type due to 

lack of information (such as Aynak, Afghanistan; Abdullah 

and others, 1980; Peters and Bawiec, 2007) were excluded. 

Two partially explored sites in the Kodar-Udokan area were 

excluded because the formal mineral inventory established 

by drilling and sampling (C category resources) was less 

than the predicted undiscovered mineral estimate (prognostic 

resource; Diatchkov, 1994; Jakubiak and Smakowski, 1994 

Arkhangel’skaya and others, 2004).

Qieke and Yaojianzi (Yan and others, 2010); Lochaber 

Lake (Kirkham and others, 1994; Cox and others, 2003); 

Shangolowe, Etoile Extension, and Nundo (appendix A, this 

report); and the Kona Dolomite (Wilband, 1978) were identified as outliers that fell outside the 99th density ellipses on 

bivariate plots of log tonnage versus log copper grade 

(fig. 2-15). The most likely reasons that these points are 

outliers are incomplete delineation of resources or the use 

of a cutoff grade that is substantially different than that used 

for the rest of the deposits in the database. The Snowstorm 

deposit, a high-copper-grade outlier for the sandstone copper 

deposits, was also excluded because the limited information 

on this deposit suggests that high-grade material was selectively mined in the early 1900s (Timberline Resources, 2012; 

Boleneus and others, 2005).

Exploratory Data Analysis

Models are more likely to be stable if (1) data from at 

least 20 deposits are used in model construction, (2) tonnage 

and grades of commodities that constitute less than 10 percent 

of the ore are not significantly different from a lognormal 

distribution, (3) standard deviations for tonnage (expressed in 

logarithms) are less than 1.0, and (4) tonnage and grade are 

not significantly correlated (Singer and Menzie, (2010).

In order to prevent undue influence of one or more 

failures in the data, a large number of deposits in the models 
34 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

−2

−1

0

1

2

3

4 -2.33 -1.64 -1.28 -0.67 0.0 0.67

0.05 0.2 0.5 0.8 0.95

Normal quantile plot

Log nearest distance, in meters

1.28 1.64 2.33

Nearest distance, in meters

0

1,000

2,000

3,000

4,000

5,000 -2.33 -1.64 -1.28 -0.67 0.0 0.67 1.28 2.33

0.05 0.2 0.5 0.8 0.95

Normal quantile plot

1.64

0.001

0.01

0.006

0.004

0.002

0.1

0.06

0.04

0.02

1

0.6

0.4

0.2

10

6

4

2

100

60

40

20

1000

500

300

200

Ore, in metric tons

Orebody area, imputed 

Orebody area, measured

Area, in square kilometers

1.27 

0.38 

1e+4 1e+5 1e+6 1e+7 1e+8 1e+9 1e+10 1e+11

EXPLANATION

Figure 2-13. Histogram, box plot, and normal quantile plot 

illustrating the distribution of the nearest distance and log 

(nearest distance) between the edges of sediment-hosted copper 

ore bodies/open pits in the Central African Copperbelt. Highlighted 

histogram intervals and points show ore bodies that are within 500 

meters of each other.

Figure 2-14. Bivariate plot of ore 

tonnage versus ore body area, 

projected to the surface. Median 

area of measured values is 1.27 

square kilometers (km2 ); median 

area of measured and imputed 

values is 0.38 km2

.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 35

0

1

95

55

160

4 5 6 7 8 9 10

Log ore, in metric tons

−0.5

0

0.5

1

8

50

4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Reduced-facies—carbonate écaille

−0.4

−0.2

0

0.2

0.4

0.6

0.8

100

120

5 6 7 8 9 10

Reduced-facies—n.b.

Log copper grade, in percent

Log ore, in metric tons

Log copper grade, in percent

Log ore, in metric tons

Log copper grade, in percent

All sediment-hosted stratabound

copper deposits (SSC)

Figure 2-15. Bivariate plots of log copper grade versus log 

ore, metric tons for all sediment-hosted stratabound copper, 

reduced-facies—carbonate écaille, and reduced-facies—n.b. 

deposits. Numbered points are outliers: 8, Etoile Extension 

(DRC); 50, Nundo (DRC); 55, Shangolowe (DRC); 95, Kona 

Dolomite (USA); 100, Locaber Lake (Canada); 120, Yaojianzi 

(China); 160, Qieke (China). The curved red lines are the 99th 

percentile density ellipses.
36 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

will help insure the sample mean and standard deviation are an 

unbiased estimate of the mean and standard deviation of the 

true population. At the minimum, a grade and tonnage model 

should be based on 20 deposits (Singer and Menzie, 2010).

Classical hypothesis tests assume that the observations 

are (1) independent; (2) come from populations with the same 

variance, and, for parametric tests; and (3) follow a normal 

distribution (Van Belle, 2008). Homogeneous populations of 

variables representing weights, lengths, volumes, and grades 

of trace quantities of a commodity (less than 10 percent) are 

positively skewed and usually deviate from a normal distribution. These variables can be represented with a lognormal 

distribution; in other words, log-transformed values of these 

variables follow a normal distribution (Singer, 2011). Logtransformed values of tonnage and grade were tested to determine if they are not significantly different than the normal 

distribution. If they were not, the distributions can be used in 

parametric statistical tests. Plots and statistics were used to 

discover if the data contained multiple populations or outliers 

and the data was screened to determine if tonnage and grade 

are significantly correlated.

After removing outliers, the standard deviation of log 

tonnage for all stratabound sediment-hosted deposits was 

0.98. In order to reduce the standard deviation, deposits 

with less than 10,000 metric tons of contained copper were 

excluded. Most of the excluded sites belong to the sandstone copper deposit type. These small sites may not be fully 

explored or of economic interest in current market conditions. 

The standard deviation for the distribution of log tonnage of 

the remaining 170 SSC is 0.78.

For this report, five grade and tonnage models are 

described below. The distribution of values in each model is 

characterized by a histogram, an outlier box plot, a normal 

quantile plot, and cumulative frequency plots; summary statistics for each model are given in table 2-3.

Normal models were fit to each log-transformed distributions of tonnage and grade and goodness of fit tested using the 

Shapiro-Wilk test for the normal model (Scholtzhauer, 2007; 

table 2-4). Distributions of log-transformed values of ore tonnage, grade, and contained copper are not rejected at the 99th 

percent confidence limit and fall within the confidence interval 

for normality on normal quantile plots. For the purposes of 

comparing populations and testing correlations, log-transformed values of ore tonnage and grade will be used. Pearson 

correlation coefficients (r) were calculated between tonnage 

and grade; for all the sediment-hosted stratabound deposits, r

values between tonnage and grade are low and not significant 

at the 99th percent confidence limit.

Histograms for some of the frequency distributions have 

multiple modes (a distribution with two modes is bimodal; 

multiple modes is multimodal). If the log-transformed data 

are normally distributed, they should follow a straight line 

on the normal quantile plots. The patterns of distributions 

with multiple modes on the corresponding quantile plots 

deviate from the straight line, forming curved patterns or line 

segments with different slopes. Multiple modes may indicate 

that the sample is not homogeneous and that the observations 

are from two or more overlapping distributions. However, 

none of the multimodal distributions observed in this study 

were pronounced enough to cause the assumption of normality for log-transformed values to be rejected when using a 

Shapiro-Wilk goodness of fit test.

Grade and Tonnage Model for 

Sediment-Hosted Stratabound Copper 

Deposits

The grade and tonnage model is based on 170 SSC 

deposits (figs. 2-16 and 2-17); summary statistics are given in 

table 2-3. Median and mean values for (1) ore tonnage are 14 

and 98 million metric tons and for (2) copper grades are 1.6 and 

2.0 percent, respectively. Distributions of ore tonnage, copper grade, and contained copper are all positively skewed and 

consistent with a normal model (table 2-4). Cobalt and silver 

data are missing for 72 and 78 percent of the samples, respectively (table 2-5). The standard deviation of log-transformed 

value of deposit tonnage is less than one for this model (0.78). 

Log-transformed values of copper grades do not show significant correlation with log-transformed values of deposit tonnage 

(table 2-6). 

Grade and Tonnage Model for Sediment-Hosted 

Stratabound Copper Deposits in the Central 

African Copperbelt

The grade and tonnage model is based on 77 SSC deposits in the CACB (figs. 2-18 and 2-19); summary statistics 

are given in table 2-3. Median and mean values for (1) ore 

tonnage are 14 and 72 million metric tons and for (2) copper 

grades are 2.7 and 3.0 percent, respectively. Distributions of 

ore tonnage, copper grade, and contained copper are all positively skewed and consistent with a normal model (table 2-4). 

Cobalt and silver data are missing for 48 and 99 percent of the 

samples, respectively (table 2-5). The standard deviation of 

log-transformed value of deposit tonnage is less than one for 

this model (0.79). Log-transformed values of copper grades do 

not show significant correlation with log-transformed values 

of deposit tonnage (table 2-6). Histograms for log tonnage and 

log copper are bimodal (fig. 2-18).

Grade and Tonnage Model for ReducedFacies—Nonbrecciated (n.b.) Deposits

The grade and tonnage model is based on 50 reducedfacies—n.b. deposits (figs. 2-20 and 2-21); summary statistics 

are given in table 2-3. Median and mean values for (1) ore 

tonnage are 34 and 180 million metric tons and for (2) copper 

grades are 1.5 and 1.6 percent, respectively. Distributions 
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 37

Table 2-3. Summary statistics for sediment-hosted stratabound copper deposit models. 

[SSC, sediment-hosted stratabound copper; CACB, Central African Copperbelt; n.b., nonbrecciated; –, no data or not applicable]

Deposit type Number 

of 

deposits

Mean Quantile 

5th

Quantile 

10th

Quantile 

25th

Median Quantile 

75th

Quantile 

90th

Quantile 

95th

Ore, million metric tons

SSC 170 98 1.0 1.6 4.4 14 48 170 430

SCC in CACB 77 72 0.54 1.5 4.4 14 47 280 430

Reduced-facies—carbonate écaille 50 42 0.42 1.0 2.9 10 42 110 290

Reduced-facies—n.b. 50 180 1.1 1.6 6.2 34 97 550 730

Sandstone copper 70 77 1.1 1.9 4.5 10 39 91 310

Sandstone copper—

Roan arenite 20 34 2.0 3.9 6 11 39 47 320

Copper grade, percent

SSC 170 2.0 0.5 0.7 1.1 1.6 2.7 4.2 4.9

SCC in CACB 77 3.0 1.2 1.6 1.9 2.7 4.0 4.9 5.5

Reduced-facies—carbonate écaille 50 3.3 1.3 1.7 2.4 2.9 4.3 5.0 5.9

Reduced-facies—n.b. 50 1.6 0.8 0.9 1.0 1.5 2.1 2.5 2.8

Sandstone copper 70 1.4 0.5 0.5 0.8 1.2 1.7 2.6 3.7

Sandstone copper—

Roan arenite 20 2.4 0.8 0.8 1.5 1.7 3.3 4.9 5.5

Silver grade, grams per metric ton

SSC 38 35 5 7 12 22 52 73 110

SCC in CACB

Reduced-facies—carbonate écaille 1 8.1 8.1 1.0 8.1 8.1 8.1 8.1 8.1

Reduced-facies—n.b. 19 33 2.4 5.0 10 17 45 110 140

Sandstone copper 18 38 8.0 11 13 32 64 73 93

Sandstone copper—

Roan arenite 0 – – – – – – – –

Cobalt grade, percent

SSC 48 0.4 – – 0.1 0.3 0.6 1.1 1.7

SCC in CACB 44 0.5 – – – 0.3 0.6 1.1 1.8

Reduced-facies—carbonate écaille 36 0.6 0.0 0.1 0.2 0.4 0.7 1.2 2.0

Reduced-facies—n.b. 9 0.1 – – 0.03 0.1 0.1 0.3 0.3

Sandstone copper 3 0.1 – – – – 0.2 0.2 0.2

Sandstone copper—

Roan arenite 3 0.1 – – – – 0.2 0.2 0.2

Contained copper metal, million metric tons

SSC 170 1.8 0.017 0.25 0.023 0.067 0.94 2.8 9.5

SCC in CACB 77 2.0 0.021 0.051 0.11 0.34 1.4 4.6 15

Reduced-facies—carbonate écaille 50 1.3 0.016 0.031 0.077 0.36 1.3 2.8 5.5

Reduced-facies—n.b. 50 3.5 0.016 0.023 0.1 0.46 1.4 10 19

Sandstone copper 70 1.0 0.016 0.018 0.054 0.12 0.41 1.0 5.5

Sandstone copper—

Roan arenite 20 0.81 0.059 0.062 0.11 0.28 0.54 1.8 8.5
38 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table 2-4. Goodness of fit statistics (based on the Shapiro-Wilk W test) for stratabound sediment-hosted copper deposits.

[Log-transformed values; fitted normal. SSC, sediment-hosted stratabound copper deposits; CACB, Central African Copperbelt; n.b., nonbrecciated;–, no data or not applicable; Prob<W, probability less than W * indicates values of probability very close to zero that may indicate that the data are not a sample from a normal distribution]

Deposit 

subtype

Tonnage Copper grade Silver grade Cobalt grade Contained copper

W Prob<W W Prob<W W Prob<W W Prob<W W Prob<W

All SSC 0.989488 0.2404 0.990006 0.2776 0.976119 0.5807 0.967535 0.2470 0.977633 0.0076*

All SSC—

CACB 

0.985722 0.5448 0.978185 0.2708 0.983795 0.8257 0.982705 0.3796

Reducedfacies—

n.b.

0.981011 0.5953 0.971594 0.2684 0.983219 0.9730 – – 0.980919 0.5913

Reducedfacies—

carbonate 

écaille

0.983658 0.7127 0.973828 0.3289 – – 0.986108 0.9285 0.979055 0.5128

Sandstone 

copper

0.955071 0.0135* 0.0.980641 0.3515 0.919479 0.1266 – – 0.952190 0.0095*

Sandstone 

copper—

Roan 

arenite

0.942759 0.2702 0.959034 0.5247 – – – – 0.922274 0.1096

Table 2-5. Numbers of deposits reporting cobalt (Co) and silver (Ag) by subtype.

[SSC, sediment-hosted stratabound copper deposits; CACB, Central African Copperbelt; n.b., nonbrecciated]

Deposit type or subtype Number of 

deposits

Number of deposits 

reporting Co

Number of deposits 

reporting Ag

Co, percent 

missing

Ag, percent 

missing

All SSC deposits 170 48 38 72 78

SSC—CACB deposits 77 40 1 48 99

Reduced-facies—carbonate écaille 50 36 1 28 98

Reduced-facies—n.b. 50 9 19 82 62

Sandstone copper 70 3 19 96 73

Sandstone copper—

Roan arenite 20 3 0 85 100
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 39

5

6

7

8

9

10

-2.33 -1.64-1.28-0.67 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

−0.5

−0.3

−0.1

0.1

0.3

0.5

0.7

0.9

-2.33 -1.64-1.28-0.67 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

1

2

-2.33 -1.64-1.28-0.67 0.0 0.671.28 1.64 2.33

0.05 0.2 0.5 0.8 0.95

3

4

5

6

7

8

-2.33 -1.64-1.28-0.67 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

Log ore, in metric tons

Log silver grade, in percent

Log copper grade, in percent

Log contained copper, in metric tons

−1

0

-2.33 -1.64-1.28-0.67 0.0 0.671.28 1.64 2.33

0.05 0.2 0.5 0.8 0.95

Log cobalt grade, in percent

Normal quantile plot

Normal quantile plot

Normal quantile plot

Normal quantile plot

Normal quantile plot

Figure 2-16. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for tonnage, grade, 

and contained copper of 170 sediment-hosted stratabound copper deposits.
40 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.01 0.10.05 10.5 2 3

Cobalt grade, in percent

Probability

0.45 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 108765432 1007050403020 200

Silver grade, in grams per metric ton

Probability

30

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.80.60.40.30.2 10765432

Copper grade, in percent

Probability

0.72 1.6 4.2

n=170

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1e+4 1e+5 1e+6 1e+7 1e+9

Ore, in metric tons

Probability

1e+8 1e+10

1.6 Mt 14 Mt 170 Mt

n=170

n=38 n=48

Figure 2-17. Cumulative frequency plots of grade and tonnage for 170 sediment-hosted stratabound copper deposits. Each red 

circle is a data point for a deposit; the blue curve is the calculated lognormal distribution based on the population parameters of the 

data. Values for tonnage and grade for the 90th, 50th, and 10th probability values of the distribution are illustrated by extending a 

horizontal line from the vertical axis to the data curve, then drawing a vertical line to the horizontal axis. The value for the point where 

the vertical line intersects the horizontal axis is labeled. For some deposits, values for some metals are not reported, resulting in a 

censored or truncated dataset. For these metals, only the probability values for the data points with reported values are illustrated. 

Mt, million metric tons.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 41

Table 2-6. Summary of tonnage and grade distributions for sediment-hosted stratabound copper deposits with recommendations for 

their use in resource modeling.

[CACB, Central African Copperbelt; n.b., nonbrecciated]

Deposit type 

or 

subtype

Lognormal 

distribution

At least 20 

deposits

Standard deviations 

for 

log tonnages less 

than 1.0

No significant 

correlation between log tonnage 

and log copper 

grade

Appropriate usage

Sediment-hosted 

stratabound 

copper deposits

yes 170 0.7844376 – 0.1002 A frequency distribution using all 

sediment hosted deposits. May 

overestimate copper outside 

CACB and underestimate 

copper within the CACB. Silver 

and cobalt numbers may also be 

biased. 

Sediment-hosted stratabound copper in the 

CACB

yes 77 0.7935138 – 0.1602 A frequency distribution using 

all CACB sediment hosted 

deposits. For use in the Katanga 

Basin, where separate tracts for 

reduced-facies and sandstonetype copper deposits cannot be 

distinguished.

Reduced-facies—n.b. yes 50 0.8627252 0.0533 Reduced-facies copper 

mineralization (nonbrecciated) 

in any sedimentary basin other 

than the Katanga

Reduced-facies—

carbonate écaille

yes 50 0.7856822 – 0.1845 Katanga Basin, for reduced-facies 

deposits associated with salt 

dissolution breccias.

Sandstone copper yes 70 0.6881622 – 0.0903 Sandstone copper deposits in 

sedimentary basins other than 

the Katanga

Sandstone copper—

Roan arenite

yes 20 0.5215564 – 0.1469 Sandstone copper deposits in 

Katanga Basin

of ore tonnage, copper grade, and contained copper are all 

positively skewed and consistent with a normal model (table 

2-4). Cobalt and silver data are missing for 82 and 62 percent 

of the samples, respectively (table 2-5). The standard deviation 

of log-transformed value of deposit tonnage is less than one 

for this model (0.86). Log-transformed values of copper and 

cobalt grades do not show significant correlation with logtransformed values of deposit tonnage (table 2-6). 

Grade and Tonnage Model for ReducedFacies—Carbonate Écaille Deposits

The grade and tonnage model is based on 50 reducedfacies—carbonate écaille deposits (figs. 2-22 and 2-23); summary statistics are given in table 2-3. Median and mean values 

for (1) ore tonnage are 10 and 42 million metric tons and for 

(2) copper grades are 2.9 and 3.3 percent, respectively. Distributions of ore tonnage, copper grade, and contained copper 

are all positively skewed and consistent with a normal model 

(table 2-4). Cobalt and silver data are missing for 28 and 98 

percent of the samples, respectively (table 2-5). The standard 

deviation of log-transformed value of deposit tonnage is less 

than one for this model (0.78). Log-transformed values of copper and cobalt grades do not show significant correlation with 

log-transformed values of deposit tonnage (table 2-6). The 

histogram for log copper is bimodal (fig. 2-22); log tonnage 

may have multiple modes, but more data is required to be sure.

The bimodal distribution of copper grades may reflect 

the difference in copper grade between primary (hypogene) 

and supergene-enriched ores. Supergene processes result in 

the replacement of bornite by chalcocite, at or near the water 

table. For deposits with carbonate-rich host rocks, such as 

those that make up the carbonate-écaille deposits, weathering may produce oxide ores that are substantially enriched in 

copper relative to hypogene or supergene sulfide ores. During 

the Pliocene, oxidation and leaching formed cobalt caps in lateritic profiles over the carbonate-écaille deposits (Decree and 
42 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

others, 2010). The same event created dissolution voids in the 

carbonate-rich lithologies which were filled by malachite in 

the form of laminated crusts and speleothems (De Putter and 

others, 2010). These malachite-rich rocks developed on the 

carbonate-écaille deposits were the principal ore type mined 

up to the late 1950s (Theys and Lee, 1958). Grades ranging up 

to 16 percent copper are reported early in the history of development of this type of deposit (table 2-7). Weed (1907) reports 

grades of 10 to 14 percent copper for the Kolvezi (Kolwezi), 

Musonoi, and Dikurwe mines. By the 1970s, mines in this 

same area (Dikuluwe and Mashamba East) were producing 

ores with 5 to 9 percent copper (fig. 2-24); current grades are 3 

to 6 percent copper (table 2-7).

The normal quantile plots of tonnage for the reducedfacies, carbonate écaille show linear segments characterized 

by different slopes (fig. 2-22). The variation shown on the 

histograms and normal quantile plots may reflect size differences of gigabreccia fragments in different tectonic settings. 

The mineralized layer appears to have been interlayered with 

salt beds (Jackson and others, 2003). Halokinentic deformation of the salt layers occurred after the copper-mineralizing 

event and formed two distinct styles of structures—(1) salt 

welds3

 along thrusts and (2) salt diapirs and walls (Garlick and 

Fleisher, 1972; Jackson and others, 2003). During halokinesis, the mineralized layer, in dolomitic formations or other 

competent units, was broken into fragments ranging in size 

from about 1 to 10 km. The breccia matrix is a pelite or a 

dolomitic, chloritic, talcose siltstone (François and Cailteux, 

1981; Jackson and others, 2003). These breccia fragments are 

3

salt weld Surface or zone joining strata originally separated by salt. The 

weld is a negative salt feature resulting from the complete or nearly complete 

removal of the intervening salt. The weld consists of brecciated, insoluble 

residue containing halite pseudomorphs or salt too thin to be resolved in 

reflection seismic data. The weld is usually but not always marked by structural discordance. Another distinctive feature of welds is a structural inversion 

above them (Jackson and Talbot, 1991). 

5

5.5

6

6.5

7

7.5

8

8.5

9

0.05 0.2 0.5 0.8 0.95

− 0.2

− 0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0.05 0.2 0.5 0.8 0.95

−1.5

−1

− 0.5

0

0.5

0.05 0.2 0.5 0.8 0.95

4

4.5

5

5.5

6

6.5

7

7.5

0.05 0.2 0.5 0.8 0.95

−2.33−1.64−1.28−0.67 0.0 0.67 1.28 1.64 2.33

−2.33−1.64−1.28−0.67 0.0 0.67 1.28 1.64 2.33 −2.33−1.64−1.28−0.67 0.0 0.67 1.28 1.64 2.33

−2.33 −1.64−1.28−0.67 0.0 0.67 1.28 1.64 2.33

Log copper grade, in percent

Log contained copper, in metric tons

Normal quantile plot

Normal quantile plot Normal quantile plot

Normal quantile plot

Log ore, in metric tons

Log cobalt grade, in percent

Figure 2-18. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for tonnage, grade, and 

contained copper of 77 sediment-hosted stratabound copper deposits in the Central African Copperbelt.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 43

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.80.60.40.30.2 10765432

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.01 0.10.050.030.02 10.80.60.40.30.2 2 3

n=77 n=77

n=41

1.5 Mt 14 Mt 302 Mt 1.5 2.7 5.0

0.04 0.77

Probability

Probability

Ore, in metric tons Copper grade, in percent Probability

Cobalt grade, in percent

1e+4 1e+5 1e+6 1e+7 1e+8 1e+9 1e+10

Figure 2-19. Cumulative frequency plots of grade and tonnage for 77 sediment-hosted stratabound copper deposits in the Central 

African Copperbelt. Each red circle is a data point for a deposit; the blue curve is the calculated lognormal distribution based on the 

population parameters of the data. Values for tonnage and grade for the 90th, 50th, and 10th probability values of the distribution are 

illustrated by extending a horizontal line from the vertical axis to the data curve, then drawing a vertical line to the horizontal axis. The 

value for the point where the vertical line intersects the horizontal axis is labeled. For some deposits, values for some metals are not 

reported, resulting in a censored or truncated dataset. For these metals, only the probability values for the data points with reported 

values are illustrated. Mt, million metric tons.
44 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

5.5

6

6.5

7

7.5

8

8.5

9

9.5

10

0.05 0.2 0.5 0.8 0.95

− 0.2

− 0.1

0

0.1

0.2

0.3

0.4

0.5

0.05 0.2 0.5 0.8 0.95

0.5

1

1.5

2

0.05 0.2 0.5 0.8 0.95

4

4.5

5

5.5

6

6.5

7

7.5

8

0.05 0.2 0.5 0.8 0.95

−2.33−1.64−1.28 −0.67 0.0 0.67 1.28 1.64 2.33

0.0 0.67 1.28 1.64 2.33

0.0 0.67 1.28 1.64 2.33

−2.33−1.64−1.28 −0.67

Log copper grade, in percent

Log contained copper, in metric tons

Normal quantile plot

Normal quantile plot Normal quantile plot

Normal quantile plot

Log ore, in metric tons

Log silver grade, in percent

−2.33−1.64−1.28 −0.67 0.0 0.67 1.28 1.64 2.33

−2.33−1.64−1.28 −0.67

Figure 2-20. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for tonnage, grade, and 

contained copper of 50 reduced-facies—n.b. copper deposits.

of ore tonnage, copper grade, and contained copper are all 

positively skewed and consistent with a normal model (table 

2-4). Cobalt and silver data are missing for 96 and 73 percent 

of the samples, respectively (table 2-5). The standard deviation of log-transformed value of deposit tonnage is less than 

one for this model (0.69). Log-transformed values of copper 

and cobalt grades do not show significant correlation with 

log-transformed values of deposit tonnage (table 2-6). Log 

tonnage and log copper grade are still positively skewed after 

transforming the values using logarithms. The 5 giant sandstone copper deposits deposits contribute to the positive skew 

for tonnage (table 2-2). The high copper grade values are 

associated with the CACB deposits.

Grade and Tonnage Model for Sandstone 

Copper—Roan Arenite

The grade and tonnage model is based on 20 sandstone 

copper deposits in the CACB (figs. 2-30 and 2-31); summary 

shown on the 1:100,000-scale geologic maps of the Likasi and 

Kolwezi areas (Musée Royal de l’Afrique Centrale, 2006a,b). 

Using GIS, the areas of the breccia fragments were measured. 

The large mineralized breccia fragments in the salt welds are 

larger than the fragments in the salt diapirs and salt walls (fig. 

2-25). The size distribution of fragments associated with salt 

welds (thrust sheets) is statistically larger than fragments that 

occur in diapirs or anticlines (fig. 2-26). As a result, the larger 

breccias fragments in the salt welds can host larger tonnage 

deposits (fig. 2-27). 

Grade and Tonnage Model for Sandstone 

Copper Deposits

The grade and tonnage model is based on 70 sandstone 

copper deposits (figs. 2-28 and 2-29; summary statistics 

are given in table 2-3. Median and mean values for (1) ore 

tonnage are 10 and 77 million metric tons, and (2) copper 

grades are 1.2 and 1.4 percent, respectively. Distributions 
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 45

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1e+4 1e+5 1e+6 1e+7 1e+9

Ore, in metric tons

1.6Mt 34 Mt 550 Mt

Probability

1e+8 1e+10

n=50

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.80.60.40.30.2 10765432

Copper grade, in percent

Probability

n=50

0.88 1.5 2.5

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 108765432 1007050403020 200

Silver grade, in grams per metric ton

45

Probability

n=19

Figure 2-21. Cumulative frequency plots of grade and tonnage for 50 reduced-facies—n.b. copper deposits. Each red circle 

is a data point for a deposit; the blue curve is the calculated lognormal distribution based on the population parameters of the 

data. Values for tonnage and grade for the 90th, 50th, and 10th probability values of the distribution are illustrated by extending a 

horizontal line from the vertical axis to the data curve, then drawing a vertical line to the horizontal axis. The value for the point 

where the vertical line intersects the horizontal axis is labeled. For some deposits, values for some metals are not reported, 

resulting in a censored or truncated dataset. For these metals, only the probability values for the data points with reported values 

are illustrated. Mt, million metric tons.
46 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

5.5

6

6.5

7

7.5

8

8.5

0.20.05 0.5 0.8 0.95

− 0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0.20.05 0.5 0.8 0.95

−1.2

−1

− 0.8

− 0.6

− 0.4

− 0.2

0

0.2

0.4

0.20.05 0.5 0.8 0.95

4

4.5

5

5.5

6

6.5

7

7.5

0.20.05 0.5 0.8 0.95

Log copper grade, in percent

Log contained copper, in metric tons

Normal quantile plot

Normal quantile plot Normal quantile plot

Normal quantile plot

Log ore, in metric tons

Log cobalt grade, in percent

−2.33−1.64−1.28−0.67 0.0 0.67 1.281.64 2.33

0.0 0.67 1.281.64 2.33 0.0 0.67 1.28 1.64 2.33

−2.33−1.64−1.28−0.67 0.0 0.67 1.28 1.64 2.33

−2.33−1.64−1.28−0.67 −2.33−1.64−1.28−0.67

Figure 2-22. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for tonnage, grade, and 

contained copper of 50 reduced-facies—carbonate-écaille copper deposits.

statistics are given in table 2-3. Median and mean values for 

(1) ore tonnage are 11 and 34 million metric tons, and (2) copper grades are 1.7 and 2.4 percent, respectively. Distributions 

of ore tonnage, copper grade, and contained copper are all 

positively skewed and consistent with a normal model (table 

2-4). Cobalt and silver data are missing for 96 and 73 percent 

of the samples, respectively (table 2-5). The standard deviation 

of log-transformed value of deposit tonnage is less than one 

for this model (0.52). Log-transformed values of copper and 

cobalt grades do not show significant correlation with logtransformed values of deposit tonnage (table 2-6). 

Supergene processes result in the replacement of bornite 

by chalcocite at or near the water table in many sandstone 

copper deposits. Oxidation of the deposits in Zambia formed 

two zones, one in which copper has been leached to form a 

barren outcrop or gossan, and another in which there has been 

nearly complete transformation of sulfide minerals to oxidized 

copper compounds, with grades similar to or slightly less 

than those of the original sulfide ores (Bateman, 1935). In the 

Zambian part of the CACB, supergene chalcocite is found in 

sandstone copper deposits such as Chibuluma West (Sweeney and Binda, 1994), Mufulira (Gray, 1932), and Bwana 

Mkubwa (Notebaart and Vink, 1972). 

At Mufulira, the distribution of chalcocite shows an obvious relation to the surface and to horizons of deep leaching and 

oxidation (Gray, 1932). The grade of copper ores produced at 

Mufulira decreases from greater than 5 percent in the 1930s to 

slightly more than 2 percent in the 1990s. This trend probably 

reflects changing cutoff grades as the mine was developed but 

also records the mining of high grade supergene-enriched sulfide ores early in the production history of the mine (fig. 2-24).
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 47

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.01 0.10.05 10.5 2 3

Cobalt grade, in percent

Probability

1.1

n=36

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.60.40.30.2 10765432

Copper grade, in percent

Probability

2.91.7 5

n=50

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1e+4 1e+5 1e+6 1e+7 1e+8

Ore, in metric tons

1e+9 1e+10

Probability

1 Mt 10 Mt 110 Mt

n=50

Figure 2-23. Cumulative frequency plots of grade and tonnage for 50 reduced-facies—carbonate-écaille deposits. Each red circle is a 

data point for a deposit; the blue curve is the calculated lognormal distribution based on the population parameters of the data. Values 

for tonnage and grade for the 90th, 50th, and 10th probability values of the distribution are illustrated by extending a horizontal line 

from the vertical axis to the data curve, then drawing a vertical line to the horizontal axis. The value for the point where the vertical line 

intersects the horizontal axis is labeled. For some deposits, values for some metals are not reported, resulting in a censored or truncated 

dataset. For these metals, only the probability values for the data points with reported values are illustrated. Mt, million metric tons.
48 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table 2-7. Comparison of grades of oxidized ore formed on reduced-facies—carbonate écaille deposits mined early in the 20th 

century with grades reported for the same deposit area in this compilation.

Deposit Copper, in 

percent, historic 

records

Material Reference Deposit in this 

compilation

Copper, in 

percent, this 

compilation

Kambove 14.8 to 16.0 Unsorted ore from 

shaly sandstone 

and high-grade 

carbonate ore

Weed (1907) Kambove PrincipalKambove West6.58

Kambove 11.80 Mill feed of oxidized 

ores (with 

malachite and 

chrysocolla) to 

Panda concentrator 

Newton and Wilson (1942)

Kolvezi, Musonoi, 

and Dikurwe

10.0 to 14.0 Quartz reefs and 

laminated 

sandstones

Weed (1907) DIMA

Kolwezi

2.78

6.0

Fungurume 6.0 to 8.0 Sandstone ore Weed (1907) Fungurume 4.32

Likasye 15 to 16.5 Weed (1907) Likasi Mined out

Figure 2-24. Graph showing the variation of copper grade by year for six sediment-hosted stratabound copper 

deposits in the Central African Copperbelt.

1930 1940 1950 1960 1970 1980 1990 2000

1

2

3

4

5

6

7

8

9

10

Copper grade, in percent

Year

Nkana

Mufulira

Kamoto

Dikuluwe

Mashamba E

Mashamba W

EXPLANATION

Deposits
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 49

−1

0

1

2

3

4

5

6

7

8

9

10

11

12 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

Normal quantile plot

−8

−7

−6

−5

−4

−3

−2

−1

0

1

2

3 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

Diapiric

−1

0

1

2

3

4

5

6

7

8

9

10

11

12 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

−8

−7

−6

−5

−4

−3

−2

−1

0

1

2

3 0.0 0.67 1.281.64 2.33

0.05 0.2 0.5 0.8 0.95

Not diapiricLog area, in square kilometers Log area, in square kilometers

Area, in square kilometers Area, in square kilometers

Normal quantile plot Normal quantile plot

Normal quantile plot

−2.33 −1.64−1.28−0.67 −2.33 −1.64−1.28−0.67

−2.33 −1.64−1.28−0.67 −2.33 −1.64−1.28−0.67

Figure 2-25. Histogram and normal quantile plots showing the distribution of surface area of Roan gigabreccia fragments on the Likasi 

and Kolwezi geologic maps. Classification of fragments into “diapiric” and “not diapiric” groups based on the polygons showing the 

limit of the diapir province illustrated on figure 12 of Jackson and others (2003).

−7

−6

−5

−4

−3

−2

−1

0

1

2

Diapiric Not diapiric

Tectonic style

All pairs

Tukey-Kramer

0.01

Diapiric

Not diapiric

0.0 0.67 1.28 1.64 2.33

Normal quantile

Log area, in square kilometers

0.010.05

0.2

0.50.8

0.95

0.99

−2.33 −1.64−1.28−0.67

Figure 2-26. Quantile plots, comparison circles, and normal quantile plots comparing the surface area of Roan gigabreccia fragments 

on the Likasi and Kolwezi geologic maps. Classification of fragments into “diapiric” and “not diapiric” groups based on the polygons 

showing the limit of the diapir province illustrated on figure 12 of Jackson and others (2003).
50 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

5

5.5

6

6.5

7

7.5

8

8.5

Other structures

Thrust sheet

0.0 0.67 1.28 1.64 2.33

Normal quantile

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8 0.0 0.67 1.28 1.64 2.33

Normal quantile

−1.2

−1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4 0.0 0.67 1.28 1.64 2.33

Normal quantile

4

5

6

7 0.0 0.67 1.28 1.64 2.33

Normal quantile

Log metric tons of ore

Other structures

Thrust sheet

0.010.05

0.20.50.8

0.950.99

Log copper grade, in percent

Other structures

Thrust sheet

0.010.05

0.20.50.8

0.950.99

Other structures

Thrust sheet

0.010.05

0.20.50.8

0.950.99

Log cobalt grade, in percent Log copper metal, in metric tons

Other structures

Thrust sheet

0.010.05

0.2

0.50.8

0.950.99

EXPLANATION

Reduced-facies—carbonate 

 écaille

−2.33−1.64−1.28−0.67

−2.33 −1.64−1.28−0.67

−2.33−1.64−1.28−0.67

−2.33 −1.64−1.28−0.67

Figure 2-27. Box plot and normal quantile plot comparing the distribution of log-transformed values of ore 

tonnage, copper grade, cobalt grade, and contained copper of reduced-facies—carbonate écaille deposits in 

different tectonic settings, Central African Copperbelt. Thrust sheet includes salt welds; other structures includes 

salt diapirs and walls.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 51

Missing Data

Missing data can cause bias to be introduced into studies, and statisticians note that missing data takes many forms 

(Schuenemeyer and Drew, 2011). When grade and tonnage 

models have been input into simulation software (Root and 

others, 1992; Bawiec and Spanski, 2012), missing grade data 

here have been coded as “zero.” This approach assumes that 

the data are not missing at random, but rather indicates little 

or no concentration of the metal of interest. However, the data 

could be missing for other reasons. In the following sections, 

possible reasons for missing data for cobalt and silver in the 

SSC models are discussed. 

Cobalt and silver grades are reported for about 28 and 22 

percent of SSC deposits, respectively (table 2-5). However, different types of SSC deposits have different proportions of missing data. Silver is rarely reported for all of the SSC deposits of 

the CACB. Most of the reported cobalt grades are associated 

with the reduced-facies—carbonate-écaille deposits of the 

CACB; cobalt is rarely reported for reduced-facies deposits 

outside the CACB or for any sandstone copper deposits. 

Silver

Many other workers have noted the silver-poor character 

of the deposits in the CACB. The low concentration of silver, 

however, is hard to verify because few trace element analyses 

of CACB ores are published. The information that is available 

supports an interpretation that the missing values reflect low 

concentrations of silver in the mineralized rocks. Analyses 

of selected ore samples from the Bwana Mkubwa sandstone 

copper—Roan arenite deposit contain 5 to 9 grams per metric 

ton (g/t) silver (Pinaar, 1961). The silver grade of the reducedfacies deposit in the Konkola North area is 0.42 g/t, with a 

maximum single sample result of 14.62 g/t (Simposya and 

Hart, 2008). Three hundred seventy-five core composites 

from 35 boreholes in the Chambishi Southeast reduced-facies 

deposit were analyzed for silver. In 200 of those samples, the 

Log copper grade, in percent

Log contained copper, in metric tons

Normal quantile plot

Normal quantile plot Normal quantile plot

Normal quantile plot

Log ore, in metric tons

6

6.5

7

7.5

8

8.5

9

9.5

0.20.05 0.5 0.8 0.95

−0.5

−0.4

−0.3

−0.2

−0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.20.05 0.5 0.8 0.95

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

0.20.05 0.5 0.8 0.95

4

4.5

5

5.5

6

6.5

7

7.5

0.20.05 0.5 0.8 0.95

Log silver grade, in percent

0.0 0.67 1.28 1.64 2.33

0.0 0.67 1.28 1.64 2.33 0.0 0.67 1.28 1.64 2.33

0.0 0.67 1.28 1.64 2.33

−2.33 −1.64−1.28−0.67 −2.33 −1.64−1.28−0.67

−2.33 −1.64−1.28−0.67 −2.33 −1.64−1.28−0.67

Figure 2-28. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for tonnage, grade, and 

contained copper of 70 sandstone copper deposits.
52 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 108765432 1007050403020 200

Silver grade, in grams per metric ton

Probability

46

n=18

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.80.60.40.30.2 10765432

Copper grade, in percent

Probability

0.5 1.2 2.6

n=70

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1e+4 1e+5 1e+6 1e+7 1e+9

Ore, in metric tons

1e+8 1e+10

Probability

n=70

1.9 Mt 10 Mt 91 Mt

Figure 2-29. Cumulative frequency plots of grade and tonnage for 70 sandstone deposits. Each red circle is a data point for a deposit; 

the blue curve is the calculated lognormal distribution based on the population parameters of the data. Values for tonnage and grade 

for the 90th, 50th, and 10th probability values of the distribution are illustrated by extending a horizontal line from the vertical axis 

to the data curve, then drawing a vertical line to the horizontal axis. The value for the point where the vertical line intersects the 

horizontal axis is labeled. For some deposits, values for some metals are not reported, resulting in a censored or truncated dataset. 

For these metals, only the probability values for the data points with reported values are illustrated. Mt, million metric tons.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 53

6.5

7

7.5

8

8.5 0.0 0.67 1.28 1.64

0.1 0.2 0.5 0.8 0.90.95

− 0.2

− 0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8 0.0 0.67 1.28 1.64

0.1 0.2 0.5 0.8 0.9 0.95

5

5.5

6

6.5

7 0.0 0.67 1.28 1.64

0.1 0.2 0.5 0.8 0.90.95

−1.64 −1.28 −0.67 −1.64 −1.28 −0.67

−1.64 −1.28 −0.67

Log copper grade, in percent

Log contained copper, in metric tons

Normal quantile plot

Normal quantile plot Normal quantile plot

Log ore, in metric tons

CACB 2-30

Figure 2-30. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for 

tonnage, grade, and contained copper of 20 sandstone copper—Roan arenite deposits.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.80.60.40.30.2 10765432

n=20 n=20

Probability

Probability

Ore, in metric tons Copper grade, in percent

1e+4 1e+5 1e+6 1e+7 1e+8 1e+9 1e+10

3.1 Mt 14 Mt 66 Mt 1.0 2.0 4.1

Figure 2-31. Cumulative frequency plots of grade and tonnage for sandstone copper—Roan arenite deposits. Each 

red circle is a data point for a deposit; the blue curve is the calculated lognormal distribution based on the population 

parameters of the data. Values for tonnage and grade for the 90th, 50th, and 10th probability values of the distribution 

are illustrated by extending a horizontal line from the vertical axis to the data curve, then drawing a vertical line to the 

horizontal axis. The value for the point where the vertical line intersects the horizontal axis is labeled. For some deposits, 

values for some metals are not reported, resulting in a censored or truncated dataset. For these metals, only the probability 

values for the data points with reported values are illustrated. Mt, million metric tons.
54 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits Value ratio Value ratio, silver98/copper98

Year

Year

300

250

200

150

100

50

0

1890 1920 1940 1960 1980 2000

Silver98/copper98

Cobalt98/silver98

300

250

200

150

100

50

1890 1920 1940 1960 1980 2000

25

20

15

10

5

0

EXPLANATION

Value ratio, cobalt98/silver98

Figure 2-32. Graphs showing the relative value of metal prices 

with time. Upper graph shows the ratio of silver/copper and cobalt 

/silver prices, in constant 1998 dollars, using a uniform scale. 

Lower graph shows the ratio of silver/copper and cobalt /silver 

prices, in constant 1998 dollars, with independent scales.

concentration of silver is below the detection limit of 0.5 g/t; 

an additional 125 samples have silver values below the detection limit of 5 g/t. Fifty samples had detectable silver; most 

values are less than 5 g/t; the highest value is 14 g/t (Japan 

International Cooperation Agency and Metal Mining Agency 

of Japan, 1996a, b). Kipoi North, a reduced-facies—carbonate 

écaille deposit, has a silver grade of 4.4 g/t (Reidy and others, 

2009). In his monograph on the central part of the Katanga 

copper arc, François (2006) describes silver only once, where 

it occurs in trace amounts at the Kapulo copper occurrence in 

the Upper Kundelungu Supergroup. Silver minerals are not 

described in literature on the ore-mineralogy of the CACB 

deposits (GECO Project, 2009).

Silver is reported for about 30 to 35 percent of the 

deposits that make up the reduced-facies and sandstone copper 

deposits found outside the CACB. Although the percentage 

of missing data is high, missing values may represent notreported data rather than no values. For some regions, silver 

data are available for part of the resource base, a group of 

deposits, or production, but cannot be partitioned to individual 

deposits. Examples include the Kupfershiefer in Germany 

and Poland; Chu Sarysu Basin, Kazakhstan; and the Redstone 

Copperbelt, Canada. In other cases, silver may not have been 

reported because of its value relative to copper. The relative 

value of silver to copper has fluctuated dramatically in the last 

40 years (fig. 2-32). At current metal prices, silver represents 

about 20 to 30 percent of the value of the metal in reducedfacies—n.b. and sandstone copper deposits. At times when 

silver has relatively low value (as in the 1990s), it may not be 

reported. When it is worth more (as in the 1980s), silver is a 

significant part of the value of the deposit and is more likely to 

be reported. Although data are not available for each deposit 

in the grade and tonnage model, silver may be an important 

commodity for all reduced-facies—n.b. and sandstone copper 

deposits. However, the number of deposits with missing values is too high to make statistical inferences using imputation 

techniques. Schuenemeyer and Drew (2011) suggest that any 

inference made when the proportion of missing data is greater 

than 15 percent should be interpreted with great caution.

Cobalt

Economically significant quantities of cobalt are documented for the reduced-facies deposits of the CACB. Missing 

cobalt data for the reduced-facies—carbonate-écaille deposits, 

however, most likely represent nonreporting rather than low 

concentration. Techniques to estimate missing values would 

be appropriate to apply, particularly for the carbonate-écaille 

deposits. Cobalt grade typically is not reported for reducedfacies deposits in other parts of the world and sandstone 

copper deposits, in general. Missing values appear to reflect 

low concentrations of cobalt in these deposits. Reserves 

of the Boleo reduced-facies deposit in Mexico have cobalt 

grades of 0.07 percent, roughly an order of magnitude less 

than the mean values for reduced-facies–carbonate écaille 

deposits (Dreisinger and others, 2010). Cobalt concentrations 

in mineralized sections of the reduced-facies Kupferschiefer 

range from 10 to 270 g/t (0.001 to 0.027 percent), with a 

mean of 125 g/t (0.0125 percent) (Wedepohl, 1964). These 

low values are consistent with the distribution of cobalt 

(generally <0.001 percent or 10 g/t) shown in the Dachow 

M24 drill hole (Oszczepalski, 1999) and the values of 28 to 

140 g/t cobalt at Mansfeld (Knitzchke, 1995). In a study of 

minor and trace elements of the Spar Lake sandstone copper 

deposit, only a single sample out of 205 analyzed had cobalt 

exceeding the 10 g/t (0.001 percent) detection limit. Mineralized samples from the Kodar-Udokan sandstone copper 

deposits have less than 25 g/t (0.0025 percent) cobalt (Bakun 

and others, 1966; Boris Syusyura, Mining and Economic 

Consulting Ltd.,written commun., 2009).
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 55

Relations Among Surface Area, 

Tonnage, and Contained Copper

In USGS mineral assessments, geologists create mineral 

resource maps that show tracts where geology permits the 

existence of deposits of one or more specified types, and 

make estimates of the number of undiscovered deposits 

that exist in the delineated tracts. The undiscovered deposit 

estimates need to be consistent with the grade and tonnage 

models for the deposit type being assessed and not with 

the population of mineral occurrences (Singer and Menzie, 

2010). Specifically, the estimated number of deposits must 

match the percentile values of the grade- and tonnage- model. 

Summary statistics can be derived from the grade and tonnage model to assist the assessment geologist in making 

deposit estimates that are consistent with the model. During 

assessments, knowing the area of deposits that comprise the 

grade and tonnage models is also useful. It helps in selecting 

a spatial rule for aggregation of deposits but also allows the 

assessment geologist to know the spatial constraints on how 

many deposits can fit inside of a tract. If the geologist knows 

the extent of the area that may correspond to a deposit, the 

relations between area and tonnage and contained metal 

allow undiscovered estimates to be made. 

For this study, areas of deposits were measured and 

compiled along with tonnage and grade data. The area of the 

surface projection of ore bodies was measured for 55 of the 170 

deposits in the grade and tonnage models. Areas range from 

0.05 to 375 km2

, with mean and median values of 19.4 and 1.55 

km2, respectively. The distribution of values for area is positively skewed and the assumption that log-transformed data can 

be represented as a normal distribution was not rejected at the 

1-percent confidence level. The dataset is biased: small deposits 

(less than 2 million metric tons of ore) are not well represented 

in the dataset (fig. 2-14) and deposits in the CACB are overrepresented. CACB deposits make up about 45 percent of the 

deposits database (table 2-1) but constitute 69 percent of the 

deposits for which an area was estimated. Never-the-less, the 

data for all deposits show a positive correlation between area 

(square kilometers) and ore tonnage (metric tons) and contained 

copper (metric tons) for SSC deposits (fig. 2-14).

Regression equations can be used to estimate tonnage 

and contained copper from the deposit areas for 55 SSC 

deposits (fig. 2-33). The regression equation for tonnage is:

log (ore, metric tons) = 7.51 + 0.78×log (area, km2), 

where both tonnage and area have values for which the lognormal distribution was not rejected at the 99th percent confidence 

limit. The regression equation is significant at the 99th percent 

confidence limit and 77 percent of the variability in deposit tonnage can be explained given knowledge of deposit area. Contained copper can be estimated using the following equation:

log (contained copper, metric tons) = 5.80 + 0.71×log (area, km2),

where both contained copper and area have values for which 

the lognormal distribution was not rejected at the 99th percent 

confidence limit. The regression equation is significant at the 

99th percent confidence limit and 66 percent of the variability in contained copper can be explained given knowledge of 

deposit area.

Equations for Sandstone Copper Deposits

Regression equations can be used to estimate tonnage and 

contained copper from the deposit areas for 28 sandstone copper deposits (fig. 2-34). The regression equation for tonnage is: 

log (ore, metric tons) = 7.35 + 0.85×log (ore body area, km2),

where both tonnage and area have values for which the lognormal distribution was not rejected at the 99th percent confidence limit. The regression equation is significant at the 99th 

percent confidence limit and 78 percent of the variability in 

deposit tonnage can be explained given knowledge of deposit 

area. Contained copper can be estimated using the following 

equation: 

log (contained copper, metric tons) = 5.60 + 0.70×

log (ore body area, km2

),

where both contained copper and area have values for which 

the lognormal distribution was not rejected at the 99th percent 

confidence limit. The regression equation is significant at the 

99th percent confidence limit and 66 percent of the variability in contained copper can be explained given knowledge of 

deposit area.

Equations for Reduced-Facies—Carbonate 

Écaille Deposits

Regression equations can be used to estimate tonnage 

and contained copper from the deposit areas for 12 reducedfacies—carbonate écaille deposits (fig. 2-35). The regression 

equation for tonnage is:

log (ore, metric tons) = 7.79 + 0.81×log (ore body area, km2

),

where both tonnage and area have values for which the lognormal distribution was not rejected at the 99th percent confidence 

limit. The regression equation is significant at the 99th percent 

confidence limit and 88 percent of the variability in deposit tonnage can be explained given knowledge of deposit area. Contained copper can be estimated using the following equation:

log (contained copper, metric tons) = 6.22 + 0.96×

log (ore body area, km2

),

where both contained copper and area have values for which 

the lognormal distribution was not rejected at the 99th percent 
56 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

confidence limit. The regression equation is significant at the 

99th percent confidence limit, and 88 percent of the variability in contained copper can be explained given knowledge of 

deposit area.

The recently discovered Kamoa deposit in the CACB is 

a laterally extensive reduced-facies deposit (Broughton and 

Rogers, 2010a, b) for which mineral inventory information 

is not published. Broughton and Rogers (2010a, b) describe 

the geology and discovery history of the deposit and indicate 

that mineralization grading more than 1 percent copper over 

3 meters extends over an area of 80 km2. An independent NI 

43-101 report completed in January 2011 defined indicated and 

inferred resources over an area of 35 km2 (Ivanhoe Nickel & 

Platinum, 2011). Broughton and Rogers (2010b) consider an 

average grade-thickness of 20 meter-percent copper to be typical of reduced-facies deposits in Zambia and Poland. Using this 

estimate, each square kilometer would contain approximately 20 

million metric tons of potential ore, containing approximately 

0.5 million metric tons of copper. Using the area estimate of 35 

km2

 and their approximations, the Kamoa deposit could contain 

700 million metric tons of potential ore containing 18 million 

metric tons of copper. Using the same value for the area and the 

regression equation based on all SSC, the estimated tonnage for 

the Kamoa deposit is about 520 million metric tons of potential 

ore containing approximately 7.9 million metric tons of copper. Either approximation suggests Kamoa is a world-class or 

giant deposit (containing in excess of 2 million metric tons of 

contained copper).

Discussion and Conclusions

T-tests show that the SSC deposits in the CACB have 

significantly higher copper grades than deposits found in 

other basins (fig. 2-5). Supergene enrichment of the ore 

6.5

7

7.5

8

8.5

9

9.5

−1.5 −1 −0.5 0 0.5 1 1.5 2 2.5 3

−1.0

− 0.6

− 0.2

0.2

0.6

−1.5 −1 − 0.5 0 0.5 1 1.5 2 2.5 3

5

5.5

6

6.5

7

7.5

8

−1.5 −1 − 0.5 0 0.5 1 1.5 2 2.5 3

−1.0

− 0.5

0.0

0.5

1.0

−1.5 −1 − 0.5 0 0.5 1 1.5 2 2.5 3

Log ore, in metric tons

Log contained copper, in metric tons

Log ore body area, in square kilometers Log ore body area, in square kilometers

Log ore body area, in square kilometers Log ore body area, in square kilometers

Residual

Residual

Reduced-facies—carbonate ecaille

Reduced-facies—n.b.

Sandstone copper

EXPLANATION

Figure 2-33. Bivariate graphs of ore body area plotted against ore tonnage and contained copper metal for sediment-hosted 

stratabound copper deposits. Regression line, confidence intervals, and a plot of residuals are also shown. n.b., nonbrecciated.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 57

bodies in the CACB, and correspondingly higher cutoff 

grades, may account for some of this difference. As previously described, supergene-enrichment characterizes the 

reduced-facies—carbonate écaille and the sandstone copper—Roan arenite deposits. Supergene chalcocite is also 

described from reduced-facies deposits associated with the 

Ore Shale Formation in Zambia: Chambishi (Davidson, 

1931), N’Changa-Chingola (Jackson, 1932; Notebaart and 

Vink, 1972), Roan Antelope (Davis, 1954; Notebaart and 

Vink, 1972), and Chililabombwe (Notebaart and Vink, 1972). 

Broughton and Rogers (2010a, b) describe a recently discovered reduced-facies deposit, Kamoa, in the DRC, that has an 

interval 50 to 200 m thick enriched in supergene chalcocite 

underlying a leached zone up to 50 m thick. The supergene 

zone contains 3 to 7 percent copper compared to grades of 2 

to 4 percent copper that characterize the underlying hypogene 

mineralized rocks. More research is required to determine if 

this is the sole reason for the difference between deposits in 

the CACB and the rest of the world.

When compared using ANOVA tests, the various types 

of SSC deposits show these statistically significant differences 

using a 0.05 confidence limit (fig. 2-36): (1) the tonnage of the 

reduced-facies—n.b. deposits is larger than reduced-facies—

carbonate écaille and sandstone copper deposits; (2) the copper 

grade of reduced-facies—carbonate écaille deposits is higher 

than reduced-facies—n.b. deposit, which are both higher than 

sandstone copper deposits; (3) the contained copper of sandstone copper deposits is lower than reduced-facies deposits. 

The characteristics of the deposit types and their suitability for grade and tonnage modeling in resource assessment 

are summarized in table 2-6, using the criteria of Singer and 

Menzie (2010, p. 93). All the distributions given in table 2-6 

are consistent with the normal model after values for tonnage 

and grade are log-transformed and the standard deviation of 

log-transformed values of tonnage are less than 1.0. Logtransformed values of tonnage and metal grade do not show 

significant correlation.

Although the distribution of data for all SSC deposits 

meets all the criteria listed by Singer and Menzie (2010), as 

a grade and tonnage model, it will overestimate copper and 

cobalt in most basins and will overestimate silver and underestimate copper in the Katanga Basin. 

In order to reduce bias in resource assessments of 

undiscovered copper, the CACB should be evaluated with 

6.5

7

7.5

8

8.5

9

9.5

−1 −0.5 0 0.5 1 1.5 2

−0.8

−0.5

−0.2

0.1

0.4

0.7

−1 −0.5 0 0.5 1 1.5 2

5

5.5

6

6.5

7

7.5

−1 −0.5 0 0.5 1 1.5 2

−0.8

−0.4

0.0

0.4

0.8

–1 −0.5 0 0.5 1 1.5 2

Log ore, in metric tons

Log contained copper, in metric tons

Log ore body area, in square kilometers Log ore body area, in square kilometers

Log ore body area, in square kilometers Log ore body area, in square kilometers

Residual

Residual

Figure 2-34. Bivariate graphs of ore body area plotted against ore tonnage and contained copper metal for sandstone copper 

deposits. Regression line, confidence intervals, and a plot of residuals are also shown.
58 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

its own grade and tonnage models. The distributions for 

reduced-facies, carbonate écaille and sandstone copper 

Roan arenite, are good models for undiscovered deposits in 

the halokinetically deformed Mines Subgroup rocks in the 

Democratic Republic of the Congo and the Roan Group in 

Zambia, respectively. There are not enough reduced-facies 

deposits associated with the Ore Shale Formation to make 

a separate model; the reduced-facies—n.b. distribution 

should be used. A separate model that includes only SSC 

deposits in the CACB would be more appropriate to apply to 

the Katanga Basin where separate tracts for reduced-facies 

and sandstone copper deposits cannot be distinguished. 

One should be aware that using this distribution as a model 

presumes that the proportion of undiscovered deposit types 

will be the same as in the model. In other words, 66 percent 

of the undiscovered deposits would be like those associated 

with the Mines Subgroup, 23 percent would be like those 

in the Roan Group in Zambia, and 11 percent would be like 

those in the Ore Shale Formation in Zambia. Cobalt should 

not be modeled because it appears to be enriched only in the 

deposits in the Mines Subgroup.

The sandstone copper distribution is considered a 

good model for undiscovered deposits of this type in basins 

throughout the world (excluding the Katanga Basin). The 

reduced-facies—n.b. distribution can be used for assessment 

of deposits of this type in any sedimentary basin.

Further research is required on the silver and cobalt concentrations in SSC deposits. With the current dataset, cobalt 

enriched ores appear to be restricted to reduced-facies—carbonate écaille deposits in the CACB. Silver appears to be 

enriched in both sandstone and reduced-facies—n.b. deposits, 

except in the CACB. Additional analyses of ores are needed to 

confirm these patterns.

Acknowledgments

Discussions with James Bliss and Donald Singer helped us 

understand many of the nuances of creating tonnage and grade 

models for resource assessment. Murray Hitzman and David 

Broughton gave us insights on how to classify deposit type in 

the CACB. Illustrations were prepared by Heather Parks, Kassandra Lindsey, and Joseph Miles. Jane Hammarstrom reviewed 

an early version of this report. James Bliss, Pamela Dunlap, and 

Daniel Mosier provided formal technical reviews. 

6.5

7

7.5

8

8.5

−1.5 −1 − 0.5 0 0.5

5

5.5

6

6.5

7

7.5

−1.5 −1 − 0.5 0 0.5

Log ore, in metric tons

Log contained copper, in metric tons

Log ore body area, in square kilometers Log ore body area, in square kilometers

Figure 2-35. Bivariate graphs of ore body area plotted against ore tonnage and contained copper metal for reduced-facies—

carbonate-écaille copper deposits. Regression line, confidence intervals, and a plot of residuals are also shown.
Chapter 2. Grade and Tonnage Relations for Sediment-Hosted Stratabound Copper Deposits 59

5

6

7

8

9

10

−0.5

−0.3

−0.1

0.1

0.3

0.5

0.7

0.9

3.5

4

4.5

5

5.5

6

6.5

7

7.5

8

EXPLANATION

Reduced-facies—n.b.

Reduced-facies—

 carbonate écaille

Sandstone copper

-2.33-1.64-1.28 -0.67 0.0 0.67 1.28 1.64 2.33

-2.33-1.64-1.28 -0.67 0.0 0.67 1.28 1.64 2.33

Subtype

Normal quantile

Log copper grade, in percent Log contained copper, 

in metric tons

Log ore, in metric tons

All pairs

Tukey-Kramer

0.05 Reduced-facies—n.b.

Reduced-facies— 

carbonate écaille

Sandstone copper

0.010.05

0.20.5

0.8

0.95

0.99

Subtype

Normal quantile

All pairs

Tukey-Kramer

0.05

0.010.05

0.20.5

0.8

0.95

0.99

Subtype

Normal quantile

All pairs

Tukey-Kramer

0.05

0.010.05

0.2

0.5

0.8

0.95

0.99

-2.33-1.64-1.28 -0.67 0.0 0.67 1.28 1.64 2.33

Reduced-facies—n.b.

Reduced-facies— 

carbonate écaille

Sandstone copper

Reduced-facies—n.b.

Reduced-facies— 

carbonate écaille

Sandstone copper

Figure 2-36. Box plots, normal quantile plots, and comparison circles for log-transformed values of ore, metric tons, copper grade, 

and contained copper illustrating differences among reduced-facies—carbonate-écaille, reduced-facies—n.b., and sandstone 

copper deposits. n.b., nonbrecciated. 
60 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Chapter 3. Sediment-Hosted Structurally Controlled 

Replacement and Vein Copper Deposits in the Central African 

Copperbelt, Democratic Republic of the Congo and Zambia

By Cliff D. Taylor

Introduction

Sediment-hosted copper districts are the result of longlived mineralizing systems that stayed active over several hundred-million years, from earliest continental rifting through 

basin inversion and orogeny (McGowan and others, 2003; 

Selley and others, 2005; Hitzman and others, 2005, 2010). 

Within sedimentary basins that host red beds, copper-dominant 

deposits have variable morphologies, and form diachronously, 

resulting in the array of stratabound sediment-hosted copper 

deposit subtypes described in this volume (see Zientek and 

others, this report, chapter 1) as well as a diverse subgroup 

of deposits that are referred to here as structurally controlled 

replacement and vein (SCRV) deposits. The various subtypes 

of sediment-hosted copper deposits have virtually similar 

mineralogy and metal endowments and owe their origins to 

the same red bed copper source rocks, transport of copper as 

a chloride complex in a brine, and redox precipitation mechanisms. Sediment-hosted copper deposits that are epigenetic 

SCRV may have formed tens to hundreds of million years later 

than sediment-hosted stratabound copper deposits within the 

same rift-related sedimentary sequence. 

Both stratabound and SCRV copper deposits occur 

throughout the Neoproterozoic Katangan Basin that hosts the 

Central African Copperbelt (CACB). Historically, exploration has targeted stratabound deposits in the Lufilian Arc, 

an arcuate, Neoproterozoic to early Paleozoic orogenic fold 

and thrust belt between the Congo and Kalahari Cratons 

(fig. 3-1). The majority of copper production in the CACB 

has come from these stratabound deposits. Within this main 

portion of the CACB, deposits with the greatest production 

are hosted in the Mines Group rocks of the lower Katangan Supergroup. Lesser production has come from an array 

of smaller deposits of variable morphologies that occur in 

higher stratigraphic intervals of the Katangan Supergroup 

(fig. 3-2) and (or) from peripheral parts of the CACB such 

as the Lufilian Foreland, an underexplored foreland basin to 

the west, north, and east of the Lufilian Arc and the Domes 

region of the CACB in the inner portion of the arc. In the 

past, SCRV copper deposits may have been overlooked due 

to genetic concepts that required sediment-hosted copper mineralization to occur syngenetically or during early 

diagenesis (Garlick, 1961; Annels, 1974; Rentzsch, 1974; 

van Eden, 1974; Sweeney and others, 1986; Mendelsohn, 

1989) rather than after lithification of the host sediments. 

However, the presence of the giant Kansanshi SCRV deposit 

in the Domes region and the development of the Dikulushi 

SCRV deposit, the first producing copper mine in the Lufilian 

Foreland, has spurred exploration interest for SCRV deposits 

higher in the Katangan stratigraphy and in peripheral portions of the CACB in recent years (El Desouky, 2008). 

Many of the SCRV deposits form massive, nearmonomineralic veins of ore minerals such as chalcocitebornite or chalcopyrite-bornite-covellite with highly 

variable amounts of quartz, carbonate, or feldspar gangue. 

Typically, the ore minerals are in direct contact with 

siliciclastic walls of faults or fractures, within brecciated 

rock between fault strands, or disseminated in more porous 

sandstones in the vicinity of structures that act as the plumbing system to bring the copper-rich brines into contact with 

reductant-bearing strata.

Chapter 1 of this report summarizes a deposit model for 

sediment-hosted stratabound copper deposits, which include 

the reduced-facies, sandstone Cu, and red bed subtypes. This 

chapter presents an overview of the characteristics of SCRV 

deposits, another type of sediment-hosted copper deposit, 

which also occurs throughout the CACB. 

Concise Description

Sediment-hosted structurally controlled replacements 

and veins of copper sulfide minerals are colocated in sedimentary basins that also host sediment-hosted stratabound copper 

deposits. The characteristics of the general class of sedimenthosted copper deposits are summarized in table 3-1.

Commodities (byproducts)

Copper (cobalt, gold, silver, uranium).

Importance

Most sediment-hosted structurally controlled replacement and vein deposits are small; notable exceptions are the 

Kansanshi deposit in Zambia and the Frontier deposit in the 

Democratic Republic of the Congo (figs. 3-1 and 3-3; table 
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 61

Katanga

High

Synclinorial

Belt

Domes

Region

External Fold and

Thrust Belt

A A'

EXPLANATION

Katangan Supergroup

Upper

Lower and middle

Undifferentiated

Basement

Overriding plate

Overthrust plate

Pan-African age granite

50 MILES

0 100 KILOMETERS

0

ZIMBABWE

ZAMBIA

Hook Granite

Mwembeshi

Shear Zone

Bangweulu

Block

CCB

Kirbaran

BeltLufilian Foreland

Lufilian Arc

DEMOCRATIC REPUBLIC

OF THE CONGO

ZCB

Kalahari Craton

Irumide Belt

Congo 

Craton

25°E 30°E

15°S

10°S

A

A'

EXPLANATION

Domes Region

Foreland

External Fold and Thrust Belt

Synclinorial Belt

Katanga High

Main Copperbelt deposits

0.56–0.53 Ga felsic province

0.76–0.73 Ga mafic province

Zambezi Belt

1.3–1.0 Ga orogen

2.05–1.8 Ga orogen

Basement

Archean shield

Regions of theKatanga Basin

100 MILES

0 200 KILOMETERS

0

100 

SCRV deposits described in text

Kansanshi

Kalengwa

Lonshi

Frontier

Tilwezembi

Dikulushi

Kipoi

Kileba

Kapulo

Kikonkula

Figure 3-1. Map showing the geology and major tectonic features of the Central African Copperbelt (modified from 

Selley and others, 2005). ZCB and CCB refer to Zambian and Congolese copper belts, respectively. Ga, giga-annum.
SUPERGROUP GROUP SUBGROUP FORMATION Former nomenclature (François, 1987) LITHOLOGY 

3 uK - onaiB 3 sK arkoses, conglomerates, argillaceous sandstones Sampwe - Ku 2.3 Ks 2.2 dolomitic pelites, argillaceous to sandy siltstones Kiubo - Ku 2.2 Ks 2.1 dolomitic sandstones, siltstones and pelites Mongwe - Ku 2.1 Ks 1.3 dolomitic pelites, siltstones and sandstones Lubudi - Ku 1.4 Ks 1.2.4 pink oolitic limestone and sandy carbonate beds Kanianga - Ku 1.3 Ks 1.2.2 and 1.2.3 carbonate siltstones and shales Lusele - Ku 1.2 Ks 1.2.1 pink to grey micritic dolomite Kyandamu - Ku 1.1 Ks 1.1 Petit Conglomérat (glacial diamictite) Monwezi - Ng 2.2 Ki 2 dolomitic sandstones, siltstones and pelites Katete - Ng 2.1 Ki 1.3 dolomitic sandstones, siltstones and shales in northern areas; alternating shale and dolomite beds ("Série Récurrente") in southern areas Kipushi - Ng 1.4 Ki 1.2.2 dolomite with dolomitic shale beds in southern areas Kakontwe - Ng 1.3 carbonates; Zn-Cu-Pb Kaponda - Ng 1.2 Ki 1.2.1 carbonate shales and siltstones; "Dolomie Tigrée" at the base Mwale - Ng 1.1 Ki 1.1 Grand Conglomérat (glacial diamictite) GROUP SUBGROUP FORMATION Former nomenclature (François, 1987) FORMA

Kanzadi - R 4.3 R 4.2 Kafubu - R 4.2 Kamoya - R 4.1 Kansuki - R 3.4 R 4.1 Mofya - R 3.3 R 3.2 R.G.S. - R 3.1 Kibalong

Kambove - R 2.3 Chingola 

Pelito-arko

Kamoto - R 2.1 R.A.T. - R 1 conglomerates, coarse arkoses and argillaceous siltstones Muto

setiztrauq 

ufaK aremolgnoc elbboc dna elbbep et 

fmihC dolomite, argillite beds at top arkoses, sandy to dolomitic argillites 

Banc

Kanwangu

1 and 

dolomites to arenitic dolomites interbedded with dolomitic shales; intrusive gabbros (formerly Carbonate Unit or Upper Roan) shales with grit (Antelope Clastics) R 2.2.2 and 3: dolomitic shales containing carbonaceous horizons; occasional dolomite or arkose R 2.2.1: arenitic dolomite at the top and dolomitic shale at the base; pseudomorphs after evaporite nodules and concretions; Cu-Co stromatolitic dolomite (R.S.C.), silicified/arenitic dolomites (R.S.F./D.Strat.), grey argillaceous dolomitic siltstone at the base (Grey R.A.T.); pseudomorphs after evaporites at the contact with RAT.; Cu-Co 

(± 620 Ma) DEMOCRATIC REPUBLIC OF THE CONGO arenites, argillaceous dolomites, argillites, dolomites, evaporites; Cu-Co Ore Sha

± 750 Ma (formerly Lower Mwashya): dolomites including volcaniclastic beds; Cu-Co ZAMBIA LITHOLOGY dolomitic shales, grey to black carbonaceous shales, quartzites LITHOLOGY sandstones or alternating siltstones and shales carbonaceous shales dolomitic shales, siltstones, sandstones, including conglomeratic beds and cherts in variable position dolomites, arenitic dolomites, dolomitic siltstones base of the R.A.T. sequence - unknown red argillaceous dolomitic siltstones, sandstones and pelites ("Roches Argilo- Talqueuses") stromatolitic, laminated, shaly or talcose dolomites; locally sandstone at the base; interbedded siltstones in the upper part; Cu-Co Dolomitic shales - R 2.2 < 900 Ma basal pebble and cobble conglomerate ± 2,050 Ma KIBARAN and PRE-KIBARAN, respectively Kundelungu - Ku Ngule - Ku 2 (formerly Upper Kundelungu- Ks) Gombela - Ku 1 Nguba - Ng (formerly Lower Kundelungu - Ki) Bunkeya - Ng 2 Muombe - Ng 1 argillaceous dolomitic siltstones with interbedded sandstone or white dolomite; intrusive gabbros argillaceous dolomitic siltstones ("Roches Greso- Schisteuses") Katangan Roan R ± 500 Ma Mwashya (formerly Upper Mwashya) - R4 Dipeta - R 3 Mines - R 2 Figure 3-2. Stratigraphic nomenclature and stratigraphy of the Katanga Supergroup throughout the Central African Copperbelt (modified from Cailt

2007); structurally controlled replacement and vein (SCRV) mineralized intervals are shown in red. Ma, mega-annum.
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 63

3-2), which contain 4.8 and 3.3 million metric tons contained 

copper, respectively. Kansanshi, the largest known SCRV 

deposit, ranks 11th largest out of the 27 known giant (>2 million metric tons, Singer, 1995; based upon contained copper 

metal, see table 2-1, Zientek and others, this report, chapter 

2) sediment-hosted stratabound and SCRV copper deposits 

worldwide; Frontier ranks 15th. 

Associated Deposit Types

Associated deposit types include sediment-hosted stratabound copper deposits, sediment-hosted uranium, sedimenthosted cobalt, unconformity uranium, basaltic copper, and 

Kipushi/Tsumeb-type lead-zinc-copper deposits (Unrug, 1989; 

Selley and others, 2005; Kampunzu and others, 2009). Halite, 

sylvite, gypsum, anhydrite and stratabound iron oxide deposits 

may be present within the same stratigraphic sequences; iron 

oxide-copper-gold-uranium deposits may occur within the 

same districts (Cox and others, 2003, rev. 2007).

Distribution

SCRV deposits and occurrences are present throughout the CACB and throughout the Katangan stratigraphic 

sequence (figs. 3-1, 3-2, and 3-3). 

Age Range

Like other sediment-hosted copper deposit subtypes, the 

SCRV deposits are limited to sedimentary or metasedimentary formations younger than 2,300 mega-annum (Ma), when 

free oxygen accommodated formation of the earliest red beds 

(Chandler, 1988; Bekker and others, 2004, 2005).

Available constraints on the age of mineralization of 

SCRV deposits in the CACB suggest that they may have 

formed during multiple periods associated with extension and 

basaltic volcanism just prior to the deposition of the Grand 

Conglomerate, from approximately 765–735 Ma (Key and 

others, 2001; Barron and others, 2003; Master and others, 

2005), and during Lufilian orogenesis and metamorphism 

starting at approximately 580 Ma, with peak orogenesis and 

metamorphism occurring at approximately 540–510 Ma 

(Selley and others, 2005). 

Crosscutting relationships and presence of mineralized 

clasts in the Grand Conglomerate at the Kipoi Central deposit 

suggest that both primary stratiform as well as structurally 

hosted breccia and vein mineralization hosted in the Mwashya 

Subgroup must be older than the Grand Conglomerate (~765 

Ma; Reidy and others, 2009). The age of mineralization at 

Kansanshi has been established by a variety of geochronological techniques (Re-Os, molybdenite; U-Pb, monazite 

and brannerite) and is well constrained to about 513–501 Ma 

(Torrealday and others, 2000; Broughton and others, 2002). 

Geochemical and petrographic work at the Dikulushi deposit 

and the Kikonkula, Lufukwe, and Mwitapile occurrences in 

the Lufilian Foreland suggest that mineralization occurred in 

two discrete stages. A polymetallic assemblage was deposited 

during the Lufilian orogeny from a saline fluid at moderate 

temperature. Remobilization of the polymetallic assemblage 

by low temperature fluids after the Lufilian orogeny resulted 

in deposition of a copper-silver assemblage along northeasttrending faults (El Desouky and others, 2008; Haest, Muchez, 

Dewaele, and others, 2009; Haest, Muchez, Petit, and Vanharcke, 2009). Lead isotopic constraints on the two assemblages suggest mineral-forming events at approximately 520 

Ma followed by remobilization during a Cretaceous fluid-flow 

event between 100–80 Ma (Haest and others, 2010).

Representative Deposits in the CACB

The locations of currently known SCRV deposits and 

prospects are shown on a map of the CACB in figures 3-1 

and 3-3. The relative positions of these deposits within the 

Katangan lithostratigraphy are shown in figure 3-2. Reported 

tonnages and grades are listed in table 3-2, along with key 

references for each deposit. 

Kansanshi, Zambia

The Kansanshi deposit (figs. 3-1 and 3-3) contains 412.5 

million metric tons of ore at an average grade of 1.16 percent 

copper, and recoverable gold. The deposit, mined since 

before Europeans arrived in Africa, was one of the early 

and most important rediscoveries in the Zambian Copperbelt (Broughton and others, 2002). A giant deposit, with an 

estimated copper metal content of almost 4.8 million metric 

tons, it is also the largest of the eleven identified SCRV 

deposits in the CACB.

Kansanshi is hosted in phyllites, schists, and marbles 

of the Nguba Group at a stratigraphic level that is tentatively 

correlated with the Grand Conglomerate (fig. 3-2). Rocks 

intersected by drilling suggest that the deposit is underlain by 

approximately 1,140 meters (m) of sedimentary rocks tentatively correlated with the Mwashya Subgroup through lower 

Roan Group strata (Broughton and others, 2002).

The Kansanshi deposit consists of a series of north-south 

striking, undeformed, high-angle veins and vein swarms, 

with associated alteration halos, that are distributed in an 

en echelon pattern along the axis of the northwest trending 

Kansanshi antiform (fig. 3-4A). Three stages of crosscutting 

veins are characterized by chalcopyrite-pyrrhotite-pyrite with 

minor to trace amounts of brannerite, monazite, uraninite, 

pitchblende, molybdenite and rare bornite (fig. 3-4B). Gangue 

minerals include quartz, ferroan carbonate minerals, rutile, and 

biotite. Gold occurs as native grains associated with chalcopyrite. The vein swarms have strike lengths of hundreds of 

meters to more than 1,200 m, widths as much as 200 m, and 

vertical dimensions as much as 300 m. Individual veins can 
64 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Topic Characteristics

Tectonic setting Continental rift basins

Failed rifts or aulacogens; less commonly rifted continental margins or passive margins

Pull-apart basins, grabens

Associated with periods of continental breakup

Long-lived continental to epicontinental, basins closed to fluid flow

Post-mineral enhancement during basin inversion and orogeny

Depositional settings Arid environments at low latitudes during ore formation 

Thick continental clastic sequences (red beds) overlain by fine grained, organic-rich, marginal marine 

or lacustrine sedimentary rocks

Fining upward siliciclastic to shale-evaporite or carbonate-evaporite cycles indicate rift-drift or rift-sag 

transgressive sedimentary sequences

Evaporative lagoonal settings, sabkhas

Depth considerations 1 to 4 kilometers 

Areas of preserved continental sedimentary basins (consider likelihood that deposits have been eroded 

away or are not yet exposed) 

Systems may be intact and laterally continous or folded and dismembered by post-mineralization 

 deformation

Structural setting Basement uplifts, pinchouts, and basin margin faults against stratigraphic seals

 (aquacludes such as shale or salt horizons) important sites of mineralization

Stratigraphic traps, anticlines, and oilfield structural geometries are favorable sites for mineralization

Halokinesis, including the formation of dissolution breccias, diapirs, salt-walls and salt intrusions

Extension related to gravitational collapse of the passive margin or halokinesis

Igneous petrology No direct link to igneous activity

Host sedimentary basins often contain rift-related bi-modal volcanic rocks and associated sills/dikes

Texture Conglomerates and arkoses grading upsection into well rounded, mature sandstones, arenites, and

aeolian sandstones. Fine grained, organic rich shales, siltstones, carbonate-rich siltstones, and 

shallow water carbonates

Stratiform/stratabound style of ore includes pyrite framboids and disseminated sulfides, massive 

 sulfides, breccias, and veins

Hydrothermal alteration Vast areas of hydrothermally altered rock (hundreds of km2

) may indicate basins that were unusually 

hydrodynamically active

Widespread hematite alteration with anhydrite and illite observed in some basins. Intense alteration 

can be destructive of sedimentary textures and extends well beyond ore limits. Complex paragenesis 

involving K, Na, and Mg mineral phases: feldspars, muscovite, chlorite, anhydrite, carbonate, quartz, 

tourmaline, scapolite, sodic amphiboles, and talc

Mineralogy Primary sulfide minerals: native copper, chalcocite, bornite, chalcopyrite, galena, sphalerite, pyrite, 

 carrollite, cobaltite, siegenite, tetrahedrite + others

Supergene minerals: chalcocite, cuprite, covellite, malachite, azurite, pseudomalachite, chrysocolla, 

heterogenite + others

 

 [Based on Hitzman and others (2005, 2010), Cox and others (2003), Kirkham (1989, 1996a), and Brown (1992, 1997)]

 Table 3-1. Selected characteristics of sediment-hosted copper deposits.
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 65

Geophysical signature Self potential, induced polarization, electromagnetics, magnetotellurics, magnetics, gravity, 

radiometrics, and other methods extensively employed

General lack of success in direct detection of ore due to subtle geophysical target, deep oxidation of sulfides, variable lateritization and weathering, and conductive overburden

Host strata displays low density and low magnetic susceptibility, with anomalously high resistivity

Potential for the delineation of favorable host rocks and basin architecture using gravity, resistivity, and 

seismic profiles

Radiometrics helpful for mapping potassic alteration; K and Th track each other for many rock types, but 

Th is relatively immobile during potassic alteration. Positive U-Th anomalies coupled with negative 

potassium anomalies may be useful in locating SCRV sub-type deposits due to presence of uraniumthorium veins and biotite-destructive alteration

Remote sensing ASTER may be useful to delineate broad-scale patterns of oxidation and reduction (bleaching) in hematite-stable red beds discernable over large areas. Not useful for buried deposits or in heavily vegetated 

areas

Landsat TM imagery can be used to delineate differences in vegetation patterns relating to underlying 

lithology and structures in heavily vegetated terrains

Geochemical signature Copper is the best pathfinder element in stream sediments and soils. Cu, Co, Ag, Pb, Zn, Fe, (Mo, V, Ni, 

Mn, U, Re, Ge, Au and PGE’s). Co, Ag, Au, U, and PGE’s locally important byproducts. U-enrichments 

result in weak radioactivity

Geochemistry is an essential exploration tool for shallow sediment-hosted copper deposits

Weathering Deposits exposed to weathering may develop leached cappings and supergene enrichment profiles depending on tectonoclimactic controls. Secondary chalcocite enrichment along hydogeologic gradients is 

common

Optimal settings for supergene enrichment: low erosion rate, steep faults, uninterrupted weathering (0.5 to 

>5 million years), tectonic uplift/water table depression, and hot, semiarid to pluvial climate

Associated deposit types Occurrence of deposits or prospects for the following deposit types may indicate likelihood of occurrence 

of sediment-hosted copper deposits: stratiform sediment-hosted and vein uranium deposits, Kipushitype Cu-Pb-Zn deposits, Tsumeb-type Pb-Zn deposits, massive iron-oxide deposits, basalt-hosted 

copper deposits, bedded halite, potash, gypsum, and anhydrite (evaporite) deposits

Continental rift or failed rift tectonic setting also likely to result in spatial-temporal association with iron 

oxide-copper-gold-uranium deposits and REE-U deposits in association with anorogenic intrusive rocks 

and alkaline granites. So-called five-element vein deposits may be present

Presence, or evidence of the former presence, of hydrocarbon accumulations and (or) sour gas is very 

important

Relation to Neoproterozoic global glacial events suggests association with Rapitan-type iron deposits

 

 [Based on Hitzman and others (2005, 2010), Cox and others (2003), Kirkham (1989, 1996a), and Brown (1992, 1997)]

 Table 3-1. Selected characteristics of sediment-hosted copper deposits.—Continued

Topic Characteristics
Table 3-2. Structurally controlled replacement and vein deposits in the Central African Copperbelt. [ t, metric ton; %, percent; n.d., no data; DRC, Democratic Republic of the Congo; Contained Cu in metric tons is computed as tonnage (t) × Cu grade (%)] Deposit Country Commodities Latitude Longitude Ore (t) Cu Grade (%) Co Grade (%) Contained Cu (t) References 

Kansanshi Zambia Cu, Au, U −12.097 26.433 412,472,600 1.16 n.d. 4,767,304 Arthurs (1992), Broughton and others (2002), Torrealday and others, 2000 NKalengwa Zambia Cu, Ag −13.459 24.999 4,000,000 5.2 n.d. 208,000 Thieme and Johnson (1981), Broughton and others (2004), Ellis and Mc- Gregor (1967) UDikulushi DRC Cu, Ag − 8.892 28.274 3,114,104 4.45 0.17 138,591 Haest, Muchez, Dewaele, and others (2007); Haest, Muchez, Dewaele, and others (2009); Haest, Muchez, Petit, and Vanharcke (2009); Haest and oth- ers (2010); Lepersonne (1974) K

Frontier DRC Cu −12.728 28.475 284,247,567 1.17 n.d. 3,313,797 Gregory and others (2006) GKileba DRC Cu −11.286 27.124 9,502,431 1.4 n.d. 133,034 Reidy and others (2009) M

Kipoi Central DRC Cu, Co, Ag −11.255 27.095 56,611,535 1.81 0.08 303,600 Reidy and others (2009) M

Lonshi DRC Cu −13.177 28.941 16,935,836 4.02 n.d. 680,838 Stephens and Newall (2003) KTilwezembe DRC Cu, Co −10.802 25.692 23,351,600 1.83 0.64 426,801 Dixon and others (2009) MSafari North and South DRC Cu, Ag − 8.329 29.238 2,357,000 2.62 n.d. 61,794 Mawson West Limited (2006), Le Burn and Hayward (2011) K

Sase [Central] DRC Cu, Co − 11.453 27.078 14,700,000 1.36 0.10 200,400 Tiger Resources Limited (2009) L

Shaba DRC Cu, Ag − 8.301 29.235 6,014,000 3.38 n.d. 203,192 Mawson West Limited (2006), Le Burn and Hayward (2011) K
Figure 3-3. Index map showing the distribution of structurally controlled replacement and vein (SCRV) deposits and prospects in the Central AfrCopperbelt, in relation to the extent of the Katanga Basin. L AKE TANGANYIKA ! ! ! ! ! ! ! !

!

!

((

Y

(

Y

Y

Y

? é

(

(

? ?

???? ?

( (

(

(

(

25°E 30°E

10°S15°S

Shaba

Lonshi

Kalengwa

Frontier

Kansanshi

Dikulushi

Tilwezembe

Safari North

Safari South

Sase

Central Kileba South

Congo

R

i

v

er

Kileba North

Kipoi Central

Kikonkula

Kipushi

Kabwe

Luao-Kasongo

Kileba area {

Kabwe

Ndola

Lusaka

Lumumbashi

DEMOCRATIC REPUBLIC 

OF THE CONGO

ZAMBIA

TANZANIA

ANGOLA

MOZAMBIQUE

ANGOLA

DRC

NAMIBIA

ZAM

SOUTAFRIC

20°E 

10°S30°S

Political boundaries from U.S. Department of State (2009).WGS 1984 UTM Zone 35S Projection.Central meridian, 27° E., latitude of origin, 0°.

EXP

0 50 100 150 200 KILOMETERS0 50 100 MILES

DepositProspect

Katanga BaStructurally and vein 

Barite veinGold vein

HydrothermIron vein

Kipushi Zn-

Y

é

(

Ë

?
0 50 

00 1MILE 1 2 KILOMETERS 0.5 26°24'E 26°26'E 26°28'E 12°4'S 12°6'S 12°8'S 25°E 26°E 

11°S 12°S Gabbro Upper M

Upper Pebb

Upper M

Upper DoloSolwezi BiVein swarm EXPLKansanshi Political bo

A B Cross secti

Zone outlin

and geoc

Kansanshi 

NW Zone Main Zone SE Zone DEMOCR

OF T

ZAM

B A

A

Figure 3-4 A, Kansanshi mine, Zambia. Plan view of the Kansanshi mine area, showing en-echelon distribution of major vein swarms along the axis (modified from Broughton and others, 2002). NW, northwest, SE, southwest. B, Schematic illustration of different types of veins and associated alter(modified from Torrealday and others, 2000). Vein widths less than 1 centimeter to greater than 5 meters. The location of the deposit is shown on the 
EXPLAN

Stage 1 - Quartz-do

(molybdenite) vei

Stage 2 - Ferroan d pyrite - (chalcopyStage 3 - Calcite-fe molybdenite - (brAlbitization with mMassive ferroan do

albitization Quartz-biotite schis

Marble Biotite-garnet schi

B Figure 3-4.—Continued. 
70 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

be traced for more than 400 m along strike and 50 m downdip, 

and have widths of <1 centimeter (cm) to >5 m. The veins and 

vein swarms are surrounded by alteration halos of albite, ferroan dolomite, ferroan calcite, quartz, green muscovite (V-rich 

roscoelite), and rutile. A fourth stage of mineralization occurs 

as brecciated veins and breccia zones of altered wall rock and 

vein fragments in a matrix of ferroan dolomite, calcite, albite, 

quartz, rutile and rare chalcopyrite. As mentioned above, the 

age of mineralization at Kansanshi is constrained to about 

513–501 Ma (Torrealday and others, 2000; Broughton and 

others, 2002).

The copper at Kansanshi may have been deposited by 

basinal brines (like those that formed nearby stratiform copper 

deposits; figs. 3-1 and 3-3) that were heated during metamorphism (Hitzman and others, 2005).

Kalengwa, Zambia

The Kalengwa deposit (figs. 3-1 and 3-3) is a relatively 

small, high grade, supergene-enriched deposit hosted in undifferentiated upper Katangan low grade meta-sedimentary rocks 

(Thieme and Johnson, 1981). Host rocks include calcareous 

siltstones, sandstones, conglomerates, and thin marble beds 

(Broughton and others, 2004; Ellis and McGregor, 1967). 

The deposit is in the immediate footwall of a breccia zone 

described by Broughton and others (2004) as being similar to 

breccias in the Congolese part of the CACB that are thought to 

be produced by halokinesis and dissolution of evaporites. Ellis 

and McGregor (1967) describe a supergene-enriched ore body 

with a strike length of about 150 m and width of 25 m in subcrop 1–8 m below the present-day land surface. The supergene 

ore body dips steeply to the northwest and narrows with depth 

to less than a meter of chalcopyrite-bornite mineralization at 

a depth of 131 m. Moderate to intense sodic (calcic) and local 

potassic alteration of the breccia and underlying meta-sedimentary sequence appears to predate hypogene mineralization. 

The main ore minerals are supergene malachite and chalcocite replacements of the carbonate matrix of conglomerate 

(Ellis and McGregor, 1967). Primary sulfide minerals include 

chalcopyrite, bornite, and lesser pyrite replacing hematite 

and carbonate minerals. Ellis and McGregor (1967) noted 

that the richer concentrations of ore occur in the conglomerate, which varies in texture from a sedimentary breccia with 

slight displacement of fragments to a poorly sorted calcareous 

conglomerate. The Kalengwa deposit is most likely hosted 

in Nguba Group strata and, based on its relationship to a 

stratiform breccia horizon and the replacement nature of the 

hypogene mineralization, belongs to the SCRV subtype of 

sediment-hosted copper deposits.

Dikulushi, DRC

The Dikulushi deposit is located about 300 km northeast 

of Lubumbashi in the Democratic Republic of the Congo 

(DRC) (figs. 3-1 and 3-3). The Dikulushi deposit is a small, 

high grade, SCRV deposit hosted in brecciated red sandstones, 

shales, and carbonate rocks that are tentatively correlated 

with the upper Gombela (Lubudi Formation) and lower Ngule 

(Mongwe Formation; fig. 3-2) subgroups of the Kundelungu 

Group. Northeast-directed shortening during the Lufilian orogeny resulted in the formation of several gently folded, northwest trending anticlines above subparallel detachment surfaces 

at depth (Dewaele and others, 2006; Haest and others, 2007). 

At Dikulushi, a north-northwest oriented thrust fault caused 

the upward displacement and ductile deformation of a shale 

unit against the base of a sandstone-dolomite sequence, causing brecciation and kink folding (fig. 3-5). A second period of 

structural disruption at Dikulushi is marked by the presence 

of cross-cutting, high angle, east-west and northeast oriented 

faults across the apex of the anticline, creating a structurally 

disrupted zone that was highly favorable for epigenetic styles 

of mineralization. Regionally, the contact between the Lubudi 

Formation carbonate rocks and the overlying Mongwe siltstones is characterized by broad-scale silicification, brecciation, and copper-mineralized veining, suggesting that there has 

been significant tectonic disruption and fluid flow within this 

stratigraphic interval of the Kundelungu Group (Anvil Mining 

Ltd., 2009).

The copper-lead-zinc-iron mineralization at Dikulushi 

is localized by a series of recurrently active, northeast trending fault zones that are present over a width of approximately 

50 m. Within the fault-bounded zone, the sandstone unit and 

sandstone clasts within the breccia at the western end of the 

deposit are altered to a gray color with green clay, which 

diminishes gradually eastwards. The Dikulushi ore body is 

located in the relatively narrow zone (up to 25 m in thickness) 

between the Main and Northern Fault zones (fig. 3-5), dips 70o 

to the southeast, and is open at depth. The ore body is characterized by a variable mineral assemblage of early chalcopyrite, 

bornite, and chalcocite, with minor pyrite, arsenopyrite, sphalerite, tennantite, and galena associated with a gangue of dolomite, calcite, and quartz, and a later assemblage of silver-rich 

chalcocite with barite, calcite, and quartz gangue (Haest and 

others, 2007; Haest, Muchez, Dewaele, and others, 2009). The 

richest Dikulushi ore occurs as massive chalcocite with silver 

in solid solution that grades as high as 20 percent copper and 

600 g/t silver (Dewaele and others, 2006). It occurs along the 

intersection of the Main and North Fault zones in the eastern 

portions of the mine and continues to depth where chalcocite 

surrounds remnant bornite mineralization. Supergene mineralization consists of malachite, chrysocolla, and azurite and 

occurs at the deepest levels of the mine (+905 m; Haest and 

others, 2007; Haest, Muchez, Dewaele, and others, 2009).

Fluid inclusion and isotopic studies indicate that mineralization at Dikulushi formed in two distinct episodes: (1) early 

deposition of subeconomic copper-lead-zinc-iron sulfides in a 

zone of crosscutting faults during the Lufilian orogeny, where 

chalcopyrite, bornite, chalcocite, and sphalerite precipitated 

from moderate temperature (~90 to 140 degrees Celsius, o

C), 

saline H2O-NaCl-CaCl2 fluids in a reducing environment, 

and (2) post-orogenic remobilization of copper from the 
0 50 100 METERS 0 300 FEET 150 N NF MF 

SF 

Section line 00 50 METERS 50 100 FEET 25 SOUTH SOUTHWEST NORTH NORTHEAST Pit outline April 2004 Pit outline June 2006 

Figure 3-5. Map and cross-section of the Dikulushi structurally controlled replacement and vein (SCRV) deposit, Democratic Republic of the Congocontrolled, steeply dipping envelopes of >0.5 percent copper around the major faults in the open pit (modified from Haest and others, 2007). The locshown on the index map, figure 3-3. %, percent.
72 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

upper parts of the polymetallic stage that formed chalcocitedominant copper-silver ores from lower temperature (~70 o

C) 

H2O-NaCl-KCl fluids in an oxidizing setting in reactivated 

and new faults along the eastern parts of the deposit (Haest, 

Muchez, Dewaele, and others, 2009; Haest, Muchez, Petit, and 

Vanharcke, 2009; Haest and others, 2010). 

Kikonkula, DRC

The Kikonkula prospect is on the northern nose of the 

Kiaka Anticline 22 km southwest of the Dikulushi mine (fig. 

3-3). It is hosted in upper Nguba and Kundelungu Group 

strata and exposed in gentle anticlinal structures along with 

stratiform copper prospects at Lufukwe and Mwitapile (Haest, 

Muchez, Dewaele, and others, 2009); therefore, all of the 

prospects are thought to be tectonically related to Lufilian or 

younger tectonic events. Mineralization at Kikonkula consists 

of disseminated chalcopyrite in the Lubudi Formation carbonate rocks along an east-west trending fault of Lufilian to 

post-Lufilian age (Haest, Muchez, Dewaele, and others, 2009). 

The chalcopyrite is associated with dolomite following early 

quartz. Subsequent remobilization has resulted in a digenitebornite-covellite assemblage associated with barite.

Kapulo Area, DRC

The Kapulo-area copper-silver deposits and prospects are 

located approximately 130 km northeast of Dikulushi (figs. 

3-1 and 3-3). The Kapulo deposits are (cumulatively) the 

largest sediment-hosted SCRV type resource in the Lufilian 

Foreland (table 3-1). At Kapulo, deposits and prospects occur 

along a 3-km strike length of the Kapulo Fault and include, 

from north to south, the Shaba (Katanga), Safari North, and 

Safari South deposits, and the Luao-Kasongo prospect (fig. 

3-6). Where exposed by artisanal workings, the Kapulo Fault 

generally dips steeply to the west. The Kapulo deposits are 

interpreted as hypogene, fault-controlled ore bodies with 

disseminated chalcopyrite and bornite in the sulfide zone 

and massive to nodular cuprite, malachite, and azurite in the 

oxide zone. The mineralization is hosted in shales and coarsegrained sandstones (the Luapula beds) of the Kundelungu 

Group and in basement granites of the Bangweulu Block 

(Kibaran basement on fig. 3-6) along the Kapulo Fault. Both 

the sedimentary rocks and granites exhibit varying degrees of 

brecciation and high grade zones are associated with bornitechalcopyrite-filled matrix. The individual deposits are generally small, high grade, and range in thickness from 0-40 m 

(Mawson West Ltd., 2006).

The Shaba (Katanga) deposit is controlled by a northnorthwest trending fault that dips 55° to the west and roughly 

separates sandstones and shales of the Kundelungu Group 

from granite in the footwall. The deposit occurs in the hanging wall of the fault and is located at the contact between a 

black shale and silicified sandstone interbedded with variably 

granite-dominant and sedimentary rock-dominant polymictic 

breccias. The hanging wall sandstone is not mineralized and is 

in contact with variably brecciated and epidote-altered granite. 

Copper mineralization consists of a band of cuprite at the footwall contact of the black shale and a broad zone of supergene 

malachite and azurite near surface. The mineralized interval is 

characterized by disseminated chalcopyrite and minor chalcocite at depth with increasing bornite and native silver as the 

interval plunges to the south. Drilling at the Shaba deposit 

intersected primary ore at 125 m depth where the ore body is 

roughly 15 m wide and averages 4 percent copper.

The Safari North and South deposits (referred to as the 

Safari North and South Group for grade and tonnage modeling 

purposes due to their proximity; see appendix A, this report) are 

also located along the Kapulo Fault in coarse-grained gray sandstones with unmineralized shale and sandstone in the hanging 

wall. Mineralization occurs as chalcopyrite and bornite, which 

continues into brecciated footwall granite. Pyrite increases and 

chalcopyrite decreases as the granite becomes less fractured and 

more brecciated (Le Burn and Hayward, 2011).

Malachite occurs in two forms in the Kapulo area 

deposits, with the most abundant form occurring as light 

green disseminated malachite in shales and sandstones on the 

footwall side of the fault and the less abundant form as darker 

green fracture filling most typically in the shales. Azurite is 

present as nodules and layers in the shales and sandstones at 

both Shaba and Safari North and cuprite occurs in massive 

and nodular form within the shale unit and along its contacts, 

particularly the footwall contact. The main sulfide mineral at 

both Shaba and Safari North is chalcopyrite with lesser bornite 

and chalcocite. The chalcopyrite occurs as fined-grained 

disseminated sulfides, as more massive blebs up to 10 mm 

in size, and as replacement layers in sandstone. Paragenetic 

relationships suggest that chalcopyrite is early and that bornite 

and chalcocite occur as both hypogene and supergene phases. 

With increasing depth, chalcopyrite decreases and pyrite 

becomes the dominant sulfide. However, at the Shaba deposit 

a high-grade zone in which bornite is the dominant sulfide 

and is accompanied by native silver plunges to the south at 50 

degrees. In this zone, bornite occurs as matrix to brecciated 

sandstone and granite at the footwall contact (Le Burn and 

Hayward, 2011).

Frontier, DRC

The Frontier deposit is located in the DRC, roughly 

35 km northwest of Ndola, Zambia (figs. 3-1 and 3-3). The 

deposit is epigenetic, structurally controlled, and located 

within the Grand Conglomerate and underlying shales of the 

Mwashya Subgroup. The shales unconformably overlie a 

dolomite unit of the upper Roan (possibly the Bancroft Formation). The deposit is confined to the thickened fold nose of a 

shallowly southeastward-plunging, northeastward-dipping, 

overturned anticline. Deep drilling in the southern portion of 

the ore body indicates that the mineralized shale folds back 
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 73

29°14'E 29°16'E

8°16'S

8°18'S

8°20'S

Political boundary source: U.S. Department of State (2009)

Projection: Africa Albers Equal Area Conic;

Central meridian: 25° E; Latitude of origin: 0°

Shaba

Safari North

Safari South

Luao-Kasongo

Katangan 

Supergroup

Kibaran

basement

Katangan Supergroup - quartzite and sandstone

Fine grained granite

Kibaran basement - coarse grained granite

Gabbro

Unnamed copper occurrence

Copper deposit

Copper prospect

12 °

20 °

Kapulo

Puta

0 1 2 KILOMETERS

0 0.5 1 MILE

EXPLANATION

Fault

28°E 30°E

8°S

10°S

DEMOCRATIC 

REPUBLIC 

OF THE CONGO

ZAMBIA

TANZANIA

20 ° Strike and dip 

KAPULO FAULT

Area of map

Figure 3-6. Map showng locations of deposits in the Kapulo area, Democratic Republic of the Congo, and their distribution along the 

Kapulo Fault (modified from Mawson West Ltd., 2006). The location of the Kapulo area is shown on the index map, figure 3-3.
74 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

on itself below the overturned anticline. Alteration associated 

with mineralization consists of sodic metasomatism, silicification, and dolomitization of the host rocks. Mineralization 

occurs as coarse-grained chalcopyrite with trace amounts of 

chalcocite, digenite, bornite, and covellite. Pyrite is the major 

gangue sulfide. The sulfide assemblage occurs in quartz-albitecarbonate stockworks, veins, veinlets, and breccias, and as 

foliation-parallel disseminations in altered shales and diamictites. Gangue minerals consist of plagioclase, carbonates, 

quartz, potassium feldspar, biotite and muscovite in decreasing order. Cobalt-rich areas within the ore body are present 

but are unevenly distributed. No discrete cobalt sulfides have 

been detected and scanning-electron-microscope studies have 

determined that pyrite is cobaltiferous (1.5 to 6.9 percent 

cobalt) and weakly arsenic bearing (0.2 to 1.7 percent arsenic; 

Gregory and others, 2006).

The Frontier deposit is bounded on the west by a fault 

zone that is oriented parallel to the ore body and vertically 

displaces the upper Roan dolomite. The ore body is primarily hosted by the (Mwashya) shale unit, which is sandwiched 

between the conformably overlying Grand Conglomerate and 

the unconformably underlying upper Roan dolomite. As of 

December, 2006, the ore body was closed to the north and 

west and open at depth to the south. The mineralized shale 

horizon has a strike length of 2 km and is at a depth of over 

400 m below surface at the southwestern end (Gregory and 

others, 2006). The Frontier mine commenced production in 

November, 2007, and as of December, 2009, was projected to 

have a 15-year mine life (First Quantum Minerals Ltd., 2010).

Kipoi Project Area, DRC

Both the Kileba and Kipoi Central deposits are located 

in the Kipoi project area about 85 km northwest of Lubumbashi in the DRC (figs. 3-1 and 3-3). Kileba is approximately 

6 km southeast of Kipoi Central (fig. 3-3). Host rocks in the 

project area consist of the Mwashya Subgroup (R4) unconformably overlain by tillites of the lower Nguba Group and 

discordantly underlain by talcose breccias (locally called 

the Breche Heterogene) of the R.A.T. and lowermost Mines 

Subgroups (R1 and R2.1). Throughout the project area the 

Mwashya Subgroup contains an interval of light green talcchlorite rocks interpreted as altered mafic volcanic rocks. In 

drill core they are massive, with internal monomictic breccias 

of irregularly shaped and angular clasts. The hanging wall 

contact is commonly marked by a 1- to 3-meter-wide band of 

hematite and jasperoid iron formation. At Kipoi Central, the 

iron formation is overlain by dolomitic siltstones with at least 

two interbedded dolomite layers that are each about 20–30 m 

thick and strike northeast-southwest (fig. 3-7). The uppermost 

stratigraphic layer consists of thin-bedded, fine- to mediumgrained dolomitic siltstone that is about 150 m thick. This 

Mwashya Subgroup siltstone hosts 70–80 percent of the mineralization (Reidy and others, 2009). Bedding measurements 

in the stratified portion of the Mwashya Subgroup indicate 

that these rocks strike easterly to northeasterly and are dipping 60–90° to the southeast. In outcrop, the contact with the 

overlying Nguba Group tillites is a high-angle unconformity 

and the contact of the Mwashya Subgroup with the underlying Breche Heterogene is irregular and generally steeply dipping to vertical. This contact is interpreted as the surface of a 

diapir related to salt extrusion.

Kipoi Central 

Observations of tectonic breccias at several locations at 

the Kipoi Central deposit indicate that the deposit is controlled 

by structural features. Artisanal workings expose structures 

that are mostly brittle faults subparallel, or at high angles, to 

bedding (fig. 3-7). Associated breccias are localized and separated by intervals of weakly deformed rocks cut by conjugate 

subvertical veins that are cross cut by late-stage subhorizontal 

veins. The most prominent brittle structure is located near 

the north end of the artisanal workings where it strikes nearly 

east-west, dips steeply to the west, and separates mineralized 

dolomitic siltstones from the mafic pyroclastic unit. The contact shows strong brittle deformation and a late-stage planar 

fault that is heavily overprinted by cobalt mineralization. The 

western portion of the Kipoi Central project area is thought 

to be separated from the Kipoi Central deposit by a north- to 

northeast-striking lineament that may consist of several minor 

subparallel faults. Where this lineament is exposed in the 

northwestern project area, it is characterized by strong brecciation and mineralization that separates Breche Heterogene 

from pyroclastic rocks. Southward, the presence of the lineament is inferred on the basis of a strong magnetic gradient and 

several minor subparallel splay-faults. This lineament may 

have exerted a control on the pattern of Mwashya Subgroup 

sedimentation to the east. An east-west trending brittle fault 

is mapped west of the lineament, terminates against it, and 

is marked by artisanal workings that exploit copper oxides. 

Structural interpretations suggest that the Kipoi Central 

project area represents a structurally dismembered (possibly 

diapiric) segment of Mwashya Subgroup sedimentary rocks 

that terminate eastward against Breche Heterogene and to 

the west is adjacent to an uplifted block of lower Mwashya 

Subgroup mafic volcanic rocks. The unconformable contact 

with overlying rocks and the presence of mineralized clasts in 

the tillite suggest that both brittle deformation and mineralization occurred before the deposition of the Nguba Group tillite 

(Grand Conglomerate).

Both primary sulfide and secondary oxide copper mineralization is observed at Kipoi Central, with the majority of 

the resource resulting from secondary enrichment and oxidation of primary sulfides in the weathering profile. In nonoxidized core, primary sulfides are present in cross-cutting and 

bedding-parallel veins and as matrix in crackle, mosaic, and 

rubble breccias of tectonic origin. The mineralogy of primary 

sulfide assemblages in late-stage veins consists of chalcopyrite and pyrite with quartz and calcite gangue. Paragenetically 
509800 510000 510200 510400 510600

8756600 8756400 8756200 8756000 1310 1320 1340 1360 1380 1390 1400 1330 1350 1370 1300 

0 100 200 METERS0 300 600 FEET

Figure 3-7. Simplified geological map of the Kipoi Central deposit, Democratic Republic of the Congo (modified from Reidy and others, 2009). Areas units are shown with patterns and darker shades of color. UTM grid, zone 35.
76 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

earlier bedding-parallel veins contain chalcopyrite exclusively. Primary sulfide minerals at Kipoi Central are therefore 

epigenetic and are almost exclusively structurally controlled. 

Primary sulfides have been strongly affected by deep weathering and oxidation, resulting in redistribution of copper. The 

main copper oxide mineral at Kipoi Central is malachite, with 

minor azurite, chalcocite, and native copper. The oxide mineralization occurs as in-situ replacement of stratabound primary 

sulfides, as coatings on bedding, cleavage, and joint surfaces, 

and to a lesser degree as fillings in cavities. As a result, copper 

oxides are dispersed over a much larger volume of rock than 

the primary copper sulfides. Both a volumetric as well as a 

textural zonation of copper minerals is observed in the vicinity 

of faults, with strong copper enrichments in fault matrix giving 

way laterally to mosaic and then simple vein styles of mineralization. Cobalt enrichment is important at Kipoi Central but 

is less well constrained. Cobalt is most strongly concentrated 

near the contact between Mwashya Subgroup sedimentary and 

mafic volcanic rocks and occurs in a black, talc-rich, soft mass 

that is up to several tens of meters thick. No cobalt minerals 

have been identified; it is assumed that cobalt occurs in the 

mineral heterogenite (Reidy and others, 2009).

Copper mineralization has not been observed in the 

underlying Breche Heterogene. Copper oxide-bearing clasts 

are present in the sandy matrix of the overlying Nguba Group 

tillite, suggesting that primary copper sulfides were present at 

the time of deposition of the tillite. Copper oxide mineralization is also present in brittle fractures that crosscut the tillite 

suggesting that prolonged or repeated deformation occurred.

Kileba

The Kileba deposit is located along a topographical ridgeline that extends from the Judiera prospect in the northwest, 

through the Kipoi Central deposit to Kileba at the southeast 

end of the trend. The Kileba deposit is separated by a low 

gap in the ridge into northwestern and southeastern segments 

marked by artisanal workings that occur intermittently over 

a strike length of about 1,100 m (Reidy and others, 2009). 

Mineralization is hosted in Mwashya Subgroup rocks consisting of a package of steeply southwest dipping (75–80°) mafic 

volcanic, talcose dolomite, banded iron formation, siltstones, 

and pebble conglomerate rocks. The mineralization is primarily hosted in the talcose dolomites at the base of the iron 

formation; however, the mineralized zone is interpreted as an 

east-west zone of thickening oblique to strike and is thought to 

be either fold or fault related, with isoclinal folding observed 

in the artisanal workings. The iron formation is a laterally 

continuous and slightly discordant hematite lens about 2 m 

thick and subparallel to bedding that is located about 20 m 

above the mafic pyroclastic rocks. The iron formation is generally composed of laminated specular hematite with internal 

breccias observed in places. The contact between the mafic 

pyroclastic rocks and sedimentary rocks is strongly sheared 

in the main pit at the southeastern end of the trend. A similar 

package of sheared and deformed mafic pyroclastic rocks 

to the northeast in contact with dolomitic siltstones to the 

southwest has been observed at the northwestern end of the 

prospect area.

Surface mapping augmented by regional magnetic data 

suggest that the Kileba deposit lies on the northeastern flank 

of a regional syncline. Whether this syncline is followed by 

an anticline or a thrust fault to the northeast has not been 

determined but is postulated based upon inferred contactparallel shearing and incipient anticlinal geometry. Subvertical, north to northeast-trending brittle structures crosscut and 

therefore postdate northwest trending structures, suggesting 

that regional stress was variable over time or that progressive deformation developed secondary splay structures. An 

abrupt dip reversal from southwest to northeast is observed in 

association with a narrow northeast-trending brittle fault at the 

northwestern end of the main pit, and a second dip reversal 

related to late faulting is inferred to occur in the gap between 

the northwestern and southeastern ridges due to the observed 

southwest dipping strata observed in outcrop on the northwestern ridge (Reidy and others, 2009).

Copper mineralization at Kileba consists entirely of 

copper oxides, with malachite and minor azurite localized 

within a halo of brecciated and silicified rock surrounding 

the contact between mafic pyroclastic rocks and dolomitic 

siltones. Copper oxides occur in veins and fractures extending up to 20 m from the contact. As at Kipoi Central, there is 

a strong empirical correlation between the volume of copper 

mineralization and proximity to epigenetic structural features 

(Reidy and others, 2009). The project area is divided by the 

gap in the ridgeline into two mineralized prospects, the Kileba 

North and South deposits, each with a different tenor of copper enrichment. The Kileba South deposit consists primarily of 

a supergene copper oxide body about 730 m long, 130 m wide 

and 120 m thick (depth to the base of the weathering profile) 

with copper sulfides extending below the oxidized zone. The 

majority of the inferred resources of 9.5 million metric tons at 

1.4 percent copper (modeled at 0.5 percent copper cutoff) is 

located within the oxide body (Reidy and others, 2009). The 

Kileba North deposit is thought to be a continuation of the 

structural zone hosting the Kileba South deposit and consists 

of copper oxides along 650 m of strike length and extending 

to a depth of 110 m; however, a supergene body apparently 

did not develop here. Mineralization is reported to be open at 

depth and along strike to the northwest. Both of the deposits 

are thought to be connected by a continuous deep zone of 

mineralization (Reidy and others, 2009).

Lonshi, DRC

The Lonshi deposit is hosted in Kirilabombwe Subgroup 

rocks just below the contact with the Mwashia Subgroup in 

the DRC approximately 10 km southeast of Ndola, Zambia 

(figs. 3-1 and 3-3). The stratigraphic succession in the mine 

area consists of eastward dipping lower Roan clastic rocks 

overlain by upper Roan pelitic, carbonate, and minor clastic 
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 77

rocks which are in turn overlain by Mwashya Subgroup shales. 

The Lonshi ore body is located along a thrusted and sheared 

contact between the Lonshi conglomerate and an overlying 

dolomitic marble (fig. 3-8). Sulfide mineralization occurs 

primarily as chalcopyrite replacing carbonate clasts in the 

Lonshi conglomerate and as disseminations and rare veinlets 

in both the conglomerate and the dolomitic marble. Supergene 

enrichment and subsequent deep oxidation and weathering 

have resulted in complete dissolution of the carbonate rock to 

produce a residual silty black material called Terre Noir. Terre 

Noir is host to a major secondary oxide ore body consisting 

of chalcocite that has largely been weathered to malachite 

and black copper oxide minerals. At depth, dissolution of the 

dolomitic marble is incomplete and Terre Noir has formed 

only along the upper and lower contacts of the carbonate unit 

(Stephens and Newall, 2003).

Extensions of the Lonshi ore body have been traced over 

a strike length of 2.5 km and have been drilled to a maximum 

depth of 150 m. Oxide mineralization varies from 2 to 50 m in 

true thickness with ore grades and mineable thicknesses being 

confined to a synclinal fold flexure. In 2003, similar synclines 

were mapped to the north and south of the Lonshi deposit but 

were not drilled (Stephens and Newall, 2003). The Lonshi 

oxide ore body was depleted and mining operations ceased 

in August, 2008. As of December, 2009, no oxide resources 

remain at Lonshi. First Quantum Minerals is currently investigating the continuation of sulfide mineralization along the 

trend of the Lonshi horizon to a depth of 350 m below the base 

of the present pit (First Quantum Minerals Ltd., 2010).

Tilwezembe, DRC

The Tilwezembe deposit is located in the western portion of the CACB about 27 km east of Kolwezi (figs. 3-1 and 

3-3). The deposit is near the western end of the Tilwezembe 

Anticline which extends eastward for more than 45 km before 

disappearing under recent alluvium. The crest of the anticline 

is marked by the trace of the north-verging Kamikongwa 

Thrust Fault that places older Mwashya Subgroup strata over 

younger lower Nguba Group strata. At least eight coppercobalt prospects are located along the crest of the Tilwezembe 

Anticline and include the Tilwezembe deposit as well as the 

Kisanfu, Kalumbwe-Myunga, and Deziwa prospects (Dixon 

and others, 2009).

The deposit is primarily hosted in vuggy to massive, 

strongly brecciated siliceous dolomites and dolomitic shales 

beneath a prominent hanging wall marker horizon of hematitic 

iron formation and ferruginous dolomites of the Mwashya 

(R4) Subgroup (fig. 3-2). However, lesser mineralization in 

brecciated lower Nguba Group strata along the footwall of the 

thrust suggests that mineral deposition is younger than lower 

Nguba Group strata (Dixon and others, 2009). The Nguba 

Group strata include various massive, bedded and brecciated 

argillites and tillites, which are in turn thrust over younger 

maroon Kundelungu argillites (Dixon and others, 2009). 

A Mwashya north-south cross-section perpendicular to the 

Kamikonwa Thrust Fault consists of basal Nguba Group tillite 

(the Grand Conglomerate) underlain by rocks of the Mwashya 

Subgroup, a secondary fault, and fragments of Nguba Group 

siltstones on the southern flank of the anticline above the 

trace of the thrust. The northern flank of the anticline below 

the thrust consists of shales and siltstones of the lower Nguba 

Group. The Mwashya Subgroup is 20–50 m thick, dips 40-50° 

to the south, and contains sporadic copper mineralization for a 

distance of 600 m and cobalt mineralization for 1,200 m along 

strike. Drilling has delineated mineralization to a depth of 250 

m (Dixon and others, 2009).

Ore in the oxide zone above a depth of 60–100 m 

consists primarily of malachite, pseudomalachite, and heterogenite with traces of libethenite. Manganese oxide gangue is 

ubiquitous and occurs as psilomelane and manganite (Dixon 

and others, 2009). Toward the base of the oxide zone, native 

copper is locally common along with spherocobaltite and 

chrysocolla. Carrollite, chalcocite and some bornite with 

traces of chalcopyrite characterize most of the sulfide assemblage. Thin carbonaceous shale at the base of the Mwashya 

Subgroup is always enriched in bedded and breccia-hosted 

carrollite and chalcocite. Mineralization is strongly correlated with silicification of the dolomite and occurs as infilling 

of vugs and in fissures and open fractures associated with 

brecciation in all lithologies.

Other SCRV Deposits and Occurrences

Examples of other districts that exhibit stratiform/

stratabound disseminated to epigenetic structurally controlled 

replacement and vein type deposits in the same sedimentary sequence include the Paradox Basin of Colorado-Utah, 

United States where both stratiform (Lisbon Valley mine) and 

structurally controlled (Cashin Mine, Cliffdweller) copper 

deposits were mined from the same sedimentary sequence, and 

the Kupferschiefer of Germany, where Mansfeld-type deposits 

and Rucken “vein” deposits are present within the Rotliegendes sandstone and Kupferschiefer shale Formations of the 

Southern Permian Basin. Although the Kupferschiefer deposit 

in Poland and Germany is the type example of the reducedfacies subtype of sediment-hosted stratabound copper deposit, 

crosscutting epigenetic mineralized veins have been described 

as a distinct, but related style of mineralization to explain the 

cobalt-nickel-bismuth veins along fault systems in contact 

with Zechstein sedimentary rocks at the Bieber deposit in Germany (Wagner and Lorenz, 2002). Within the Kupferschiefer 

itself, vertical sulfide-calcite veinlets and replacement textures 

are observed, where bedding plane sulfate and sulfide veinlets 

are cut by vertical sulfide veinlets. Jowett (1987) proposed that 

these vertical veinlets may have formed by hydrofracturing 

due to fluid overpressure from a temperature increase and generation of carbon dioxide (CO2

) and hydrocarbon gases from 

Kupferschiefer organic matter during rapid basin subsidence. 
0 5 KILOMETERS 0 1.5 3 MILES 2.5 

705000 E 710000 E 715000 E

8545000 N

Figure 3-8. Geologic map of the Lonshi deposit, Democratic Republic of the Congo (based on Stephens and Newall, 2003). The location of the depo

map, figure 3-3. UTM grid, zone 35.
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 79

The sandstone-hosted deposits of the Chu-Sarysu Basin 

of Kazakhstan may be another example of a district containing 

both stratabound and SCRV-type deposits and may be related 

to differences in stratal versus structurally controlled fluid flow 

(Gablina, 1981; Syusyura and others, 1986; Syusyura, 2008).

Cashin, Colorado, United States

The Cashin Mine is about 25 km northeast of the Lisbon Valley in Montrose County, southwestern Colorado. The 

Cashin deposit contains 11,750,000 metric tons of ore with an 

average copper grade of 0.52 percent. With 61,100 metric tons 

of contained copper, the Cashin deposit is smaller than any of 

the SCRV deposits in the CACB (table 3-2).

Cashin is one of a number of epigenetic and structurally 

controlled sediment-hosted SCRV prospects that are hosted 

within intracontinental, rift-related, terrestrial sandstones and 

restricted marine sedimentary rocks of the Paradox Basin 

(fig. 3-9). The basin initially received 600–900 m of evaporitic sediments of the Paradox Formation in Pennsylvanian 

time followed by as much as 3,500 m of mostly continental 

red beds and eolian sandstones during Permian through 

Jurassic time. The marine transgression of the Interior 

Seaway in the Early Cretaceous sealed the basin beneath 

600–900 m of Mancos shale (fig. 3-9). Salt tectonics during 

the Permian, Triassic, Jurassic, and Tertiary have resulted in 

the formation of diapirs or salt walls over northwest trending basement faults that have folded or pierced the overlying 

stratigraphy. The Paradox Basin also is host to significant 

petroleum reserves generated from organic-rich siltstones 

of the Paradox Formation. Additional mineral deposit types 

present in the basin include sediment-hosted stratabound 

copper deposits such as the Lisbon Valley deposit, which 

contains 48 million metric tons at 0.514 percent copper 

hosted in the Jurassic-Cretaceous sandstones, and sandstonehosted uranium-vanadium deposits in the late Jurassic Morrison Formation and uranium in the Triassic Chinle Formation 

(Thorson, 2005).

The Cashin deposit is localized in porous Jurassic Wingate eolean sandstone on either side of the Cashin Fault, about 

1.5 km from the inferred southwestern edge of the Paradox 

Valley salt anticline (fig. 3-10). The Wingate sandstone is 

about 75 m thick and consists of fine-grained, red-orange, 

carbonate-cemented sandstone with dark red to black iron 

and manganese staining on outcrops. The Wingate is underlain by red-brown shale and siltstone of the Triassic Chinle 

Formation and conformably overlain by the irregularly bedded, red, buff, light gray, and lavender shale, siltstone, and 

fine- to coarse-grained sandstone of the Kayenta Formation 

(fig. 3-9).

Structural relationships at the Cashin Mine are relatively simple (fig. 3-10). The host sedimentary rocks strike 

northwesterly and dip about 5° to the southwest at the mine 

and steepen to about 18–20° near the edge of the salt diapir. 

The Cashin Fault strikes about N45°E, dips 60–75° to the 

northwest, and has 12–18 m of normal, down to the northwest offset. Slickensides on the fault plane rake obliquely 

to the southwest. The similar Cliffdweller Fault is located 

about 450 m to the northwest of the Cashin Mine and creates 

a pie-shaped wedge of rock that slid down and away from 

the Paradox Anticline. In the mine area, the Cashin Fault is 

composed of two or more en echelon strands that are separated 

by horsetail zones of more intense fracturing. Several small 

subsidiary faults subparallel to the Cliffdweller Fault crosscut the Cashin Fault and appear to control the location of the 

horsetail zones. Locally more intense fracturing and presence 

of copper veinlets within the horsetail zones create high grade 

zones in the “disseminated” deposit.

The most obvious alteration feature is a roughly 13 km 

long, 6.5 km wide, semicircular area centered on the mine 

area in which the Wingate and Navajo sandstones have been 

visibly altered from red to white. Within this bleached zone, 

an earlier fluid is suggested to have reduced hematite to pyrite 

and altered sodic plagioclase prior to carbonate cementation 

and copper mineralization. The significance of this relatively 

widespread fluid alteration event is that it served to convert 

otherwise unfavorable oxidized strata into a reducing, favorable host rock for later copper-silver bearing fluids (Thorson, 

2004; MacIntyre and others, 2004, 2005). The presence of oilbearing fluid inclusions in the Wingate sandstone suggests that 

the source of both fluids was probably organic-rich units in 

the Paradox Formation (MacIntyre and others, 2004; Thorson 

and MacIntyre, 2005). Petrographic evidence indicates quartz 

dissolution and replacement by bornite and chalcopyrite in 

mineralized areas.

Copper mineralization is localized along the strike of the 

Cashin Fault for greater than 1,000 m and extends through 

the complete vertical section of the Wingate sandstone (fig. 

3-11). Copper grades are highest along the fault and in stratiform zones of higher permeability or higher concentrations 

of reductant. Disseminated zones of copper mineralization 

commonly extend 120 m and narrow zones of copper oxides 

have been traced as far as 550 m from the Cashin Fault. Disseminated sulfides consisting of chalcopyrite, bornite, covellite, and chalcocite replace pyrite, bituminous hydrocarbons, 

pore-filling dolomite, and occasionally quartz. Oxidation of 

this assemblage results in minor copper remobilization and 

creates thick supergene sequences of disseminated low-grade 

copper oxides consisting of malachite, azurite, copper-bearing 

neotocite, and supergene chalcocite. Oxidation becomes less 

pervasive at depth and commonly extends to depths of 30 m 

and 60 m along strike of the Cashin Fault.

Sulfide minerals along the Cashin Fault occur within a vein 

zone of crushed sandstone with veinlets and open-space fillings 

of pink saddle dolomite and white barite gangue. The vein also 

contains native copper and a complex assemblage of copper 

arsenides at depth. Filling temperatures of fluid inclusions in 

dolomite and barite from the Cashin vein are up to 105 °C 

(Gray and others, 1996; Thorson and MacIntyre, 2005).
Pennsylvanian Permian Triassic Jurassic Cretaceous

Glen Canyon

Group Cutler Group Hermosa Group San Rafael Group

Cutler Group

undivided

Mesaverde Group

Morrison Formation

Mancos Shale

Dakota Sandstone

Cedar Mountain and Burro

Canyon Formations

Curtis Formation

Entrada Sandstone

Carmel Formation

Chinle Formation

Moenkope Formation

Navajo Sandstone

Kayenta Formation

Wingate Sandstone

Summerville Formation

White Rim Sandstone

Organ Rock Formation

Cedar Mesa Sandstone

Honaker Trail Formation

Paradox Formation

Halgaito/Elephant Canyon

Formation

Major copper host at Lisbon Valley

Major copper host at Cashin

Age Group and formation

Dark grey LimestoneHalite and Bleached Red bed s

EXPL

Grey sand carboni diagene

Figure 3-9. Generalized stratigraphic section of southeastern Utah and southwestern Colorado, United States (modified from Thorson, 2005). 
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 81

108°58'W 108°56'W

38°20'N

38°19'N

Paradox Valley

D

D

D

D D

D D

D

D D D

D

D

D

U

U

U

U U

U U U

U U U

U

U

U

CASHIN FAULT

Cliffdweller Mine

Cashin Mine

Maude Mine

CLIFFDWELLER FAULT

UTAH COLORADO

ARIZONA

WYOMING

NEW MEXICO

IDAHO

Figure area

115°W 110°W 105°W

40°N

35°N

Fault

Disseminated copper

Old mine workings

EXPLANATION

North America Albers Equal Area Conic Projection.

Central meridian, 109° W., latitude of origin, 40° N.

0 500 1,000 METERS

0 1,500 3,000 FEET

CACB g 3-10

Figure 3-10. Map showing fault patterns in the Cashin Mine area, Colorado, United States (modified from Thorson and MacIntyre, 2005).

General Characteristics of SCRV 

Copper Deposits

General characteristics of SCRV deposits are briefly 

described here, based on the limited number of deposits that 

have been described as sediment-hosted replacement and vein, 

rather than as stratabound deposits.

Dimensions

Vein swarms can have strike lengths of hundreds of 

meters to more than 1,200 m, widths up to 200 m, and vertical 

dimensions of up to 500 m. Individual veins at Kansanshi, 

for example, can be traced for more than 400 m along strike 

and 50 m downdip, and have widths of <1 cm to >5 m. The 

copper-lead-zinc-iron mineralization at Dikulushi is constrained by a series of northeast-trending fault zones that are 

present over a width of approximately 50 m. The Dikulushi 

ore body is located in a relatively narrow zone (up to 25 m 

thick) between fault zones and is open at depth. The mineralized shale horizon at the Frontier deposit has a strike length 

of 2 km and extends from surface to a depth of more than 400 

m below surface at the southwestern end (Gregory and others, 2006). The Lonshi ore body has been traced over a strike 

length of 2.5 km along a thrust contact and has been drilled 

to a maximum depth of 150 m (Stephens and Newall, 2003). 

Oxide mineralization varies from 2 to 50 m in true thickness 

(Stephens and Newall, 2003). The presence of sulfide mineralization along the trend of the Lonshi ore body to a depth of 

350 m below the base of the present pit (First Quantum Minerals Ltd., 2010) may indicate a vertical extent of up to 500 m.

Host Rocks

Host rock lithologies include phyllites, schists, and marbles, calcareous siltstones, sandstones, conglomerates, and thin 

marble beds, shales, and carbonate rocks. In the CACB, SCRV 

deposits are present throughout the approximately 7-km-thick 

Katangan Supergroup (fig. 3-2). SCRV deposits occur in the 

lowermost Roan Group, at upper stratigraphic levels in the 

Mwashya Subgroup, throughout the Nguba Group and in the 

middle stratigraphic levels of the Kundelungu Group, and at 

contacts between contrasting lithologies (fig. 3-2). Mineralization crosses multiple lithologic units in many deposits.

Ore Controls

Fault intersections with permeable strata localize SCRV 

deposits by creating zones of increased permeability favorable for epigenetic styles of mineralization. Cross-cutting, 

high angle faults, and other structures developed during and 

subsequent to the Lufilian orogeny in the CACB provided conduits for copper-mineralizing fluids. Anticlines, detachment 
Oxide zone Mixed oxides and sulfides Sulfide zone CASHIN FAULT 

Borehole Contact 0 10 20 30 METERS 0 25 50 75 FEET EXPLANATION Copper assay values Copper mineralization >0.1% 0.1% 1.0%>1.0% Stratigraphic Figure 3.11 Northwest-southeast cross section perpendicular to the Cashin Fault, Colorado, United States, showing the distribution of copper. Histo

mineralization from 0.1 to 1.0 percent in shaded gray color; the length of the bars is proportional to the assay values. Assays with greater than 1 percblack bars (modified from Thorson and MacIntyre, 2005). %, percent.
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 83

surfaces, and thrust faults cause upward displacement and 

ductile deformation, brecciation, and kink folding, especially 

at contrasting lithologic contacts such as shale against sandstone or dolomite. 

Mineralogy

Chalcopyrite, bornite, chalcocite, digenite, and covellite 

are the major copper sulfide ore minerals in SCRV deposits. 

The major supergene ore minerals are malachite, chrysocolla, 

and azurite. Gold and silver may be present, as well as pyrite, 

pyrrhotite, arsenopyrite, sphalerite, tennantite, galena, brannerite, monazite, uraninite, pitchblende, molybdenite, heterogenite, carrolite, and spherocobaltite. Cobalt and arsenic may 

be present in pyrite. Cobalt, when present as discrete mineral 

phases, occurs in heterogenite, carrollite, and spherocobaltite. 

Silver occurs in solid solution in chalcocite and tennantite. 

Gangue minerals consist of quartz, plagioclase, carbonates 

(including dolomite, ferroan dolomite, and calcite), potassium 

feldspar, biotite, muscovite, barite, rutile, hematite, and Mnoxides including psilomelane and manganite.

Alteration and Weathering

Alteration halos around veins and breccias are ubiquitous 

in SCRV deposits and are a product of local sodic and potassic 

alteration, silicification, and dolomitization of the host rocks. 

More widespread bleaching, moderate to intense sodic- (calcic) metasomatism, silicification, and dolomitization of the 

host rocks may also occur. Supergene enrichment and subsequent deep oxidation and weathering can result in complete 

dissolution of the carbonate rock to produce a distinctive 

residual silty black material (called Terre Noir in the Congolese part of the CACB).

Geochemical Signature

Copper and cobalt may be present in anomalous amounts 

in surface samples, soils, and stream sediments. Gold, uranium, lead, and zinc may also be present.

Geophysical Signature

Induced polarization and resistivity surveys may identify copper sulfide minerals associated with SCRV deposits. 

Airborne and ground gravity, magnetic, and electromagnetic 

studies may facilitate mapping of structures and define ore 

controls and trap sites.

Genesis

Distinctions between stratabound and SCRV deposits 

are not always clear cut and may in some cases be a matter 

of scale. The processes required to form an SCRV deposit are 

the same as those required for other sediment-hosted copper 

deposits (see chapter 1). SCRV deposits form when oxidized 

copper-bearing fluids meet a reductant. Four ingredients are 

required: (1) an oxidized, hematite-stable copper source rock 

containing ferromagnesian minerals and (or) mafic rock fragments, (2) a source of sulfur, (3) a basinal brine to mobilize 

and transport the copper and sulfur, and (4) stratigraphic or 

structural conditions (a physical trap) that cause mixing of the 

brine with a reductant (chemical trap).

SCRV deposits commonly cut multiple lithologies, record 

multiple pulses of mineralization, and may be metamorphosed. 

Small-scale sulfide-bearing quartz-carbonate veins and veinlets 

in stratabound deposits have been ascribed to local remobilization of ore during metamorphic, or late diagenetic to synorogenic events that post-date the primary ore deposition. Based on 

observations of identical sulfide mineral assemblages in disseminations and associated gangue veinlets cutting the same rocks 

in stratiform copper deposits in the CACB, Sillitoe and others 

(2010) argued that host rocks must have been competent enough 

to undergo brittle fracture, where veinlets acted as feeders for 

disseminated mineralization. Therefore, they concluded that the 

disseminated ore could not result from passive fluid infiltration 

during early diagenesis associated with rifting and extension, 

and emphasized massive brine expulsion by hydraulic fracturing 

associated with contractural tectonism, basin inversion, uplift, 

and exhumation. At the Kansanshi SCRV deposit, early pre- or 

synorogenic disseminated and veinlet mineralization is present, 

but the main ores are associated with steep late orogenic veins 

and hydrothermal breccias formed in the waning stages of the 

Lufilian orogeny. Similar observations at the Frontier deposit 

led Sillitoe and others (2010) to conclude that CACB copper 

was mobilized over a time span that pre- and post-dated peak 

Lufilian orogeny. At Dikulushi, copper was remobilized from 

an early polymetallic vein paragenesis to form the higher-grade 

copper-silver deposit. 

Hydrocarbons and organic material in host rocks are the 

probable reductants in SCRV deposits. Direct evidence for 

reductants in SCRV deposits typically is lacking, although 

relict pyrobitumen is observed in pre-mineralization chert at 

Dikulushi and oil-bearing fluid inclusions are present in sandstone at the Cashin deposit. 

The model for copper deposits in the Paradox Basin 

developed by Thorson (2005) requires multiple fluids for 

formation of the deposits: stage 1 early diagenetic fluids form 

iron oxides in red beds, stage 2 reducing fluids convert hematite to pyrite, with hydrocarbons as an important source of 

reductant, and stage 3 epigenetic copper-bearing saline fluids 

introduced along structural feeder zones where copper precipitates on contact with reductants in bleached beds. 

Exploration and Resource Assessment 

Guidelines for SCRV Deposits

Structurally disrupted, continental to restricted marine, 

rift-related sedimentary basins that host stratabound copper 
84 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

deposits or other associated deposit types are considered 

permissive sites for SCRV deposits. The presence of evaporite 

beds in the sequence and (or) evidence of halokinesis are considered favorable factors, as is the presence of mafic igneous 

rocks related to extension and rifting. Because SCRV deposits 

are epigenetic, and are therefore assumed to form after lithification of the host rocks, evidence of tectonic disruption and 

faults at high angles to bedding are particularly favorable. 

SCRV-type mineralization is most likely to be developed 

where structural features intersect (1) carbonaceous and (or) 

pyritic marine or lacustrine sedimentary rocks interbedded 

with or occurring up-section or laterally from continental 

red-bed sedimentary rocks, and (or) (2) continental red-bed 

sedimentary rocks that exhibit evidence of the presence or 

former presence of sour gas or hydrocarbons in pore spaces. 

Indicators of hydrocarbon reductants include, bitumen, dead 

oil, petroleum and (or) natural gas in fluid inclusions, or nonred (bleached white or gray) areas within continental, hematite-stable (red) siliciclastic rocks. 

Several key features of epigenetic SCRV copper deposits 

that may have a bearing on exploration targeting and assessment include the following (partly based on Maiden, 2011):

•	 Exploration guides for SCRV copper deposits 

include identification of controlling structures 

and zones of structural complexity. Structures 

and rock fabrics resulting from post-lithification 

deformation provide the primary setting and trap 

for mineralizing fluids.

•	 Rock competency is critical because the rheological contrast between lithologic units in a host 

succession will control the generation and location of porosity in the form of veins and breccias. 

This may be reflected in the tendency for SCRV 

deposits to be developed in clastic units because 

they are more brittle compared to altered volcanic rocks and shales.

•	 Identification of reduced and permeable zones 

adjacent to faults and other possible structures 

that could channel fluid flow can guide exploration targets.

•	 Copper concentrates in structurally controlled 

dilatant zones: fault splays, fault intersections, 

shear zones, brecciated rock at fault bends, fold 

axes, kink folding, and in alteration zones.

•	 Multiple deformation events and (or) multiple 

hydrothermal events may be involved in formation of SCRV deposits. Copper may be pumped 

up along late structures.

•	 Alteration, especially sodic alteration, as well as 

veins and breccia zones are characteristic of the 

deposit type. Copper veins may represent part of 

a halo of a larger structurally controlled hydrothermal event related to deformation.

•	 Supergene minerals (chalcocite, malachite, 

azurite) may comprise the main ore minerals in 

oxidized deposits, or oxidized parts of deposits.

•	 Recognition of structure, rather than stratigraphy, 

as the primary ore control distinguishes SCRV 

from sediment-hosted stratabound deposits.

Grade and Tonnage Models for SCRV 

Deposits

Eleven structurally controlled replacement and vein 

copper deposits in the CACB were used to create preliminary grade and tonnage models (figs. 3-12 and 3-13). 

Summary statistics for the 11 deposits are given in table 

3-3. Median and mean values for ore tonnage are 15 and 76 

million metric tons, respectively, and for copper grade are 

1.82 and 2.58 percent, respectively. Too few values of silver 

and cobalt are reported to create frequency distributions for 

resource modeling.

Goodness of fit analysis using the Shapiro-Wilk test 

did not result in the rejection of the assumption that logtransformed values for tonnage and copper grades have a 

normal distribution. Log-transformed values of copper are 

significantly correlated with log tonnage (r=-0.72, n=11). The 

standard deviation of log-transformed value of ore tonnage is 

less than one (0.75).

Acknowledgments

Recognition of the need to create descriptive as well as 

grade and tonnage models for sediment-hosted SCRV copper deposits grew out of discussions with Murray Hitzman 

(Colorado School of Mines, Golden, Colorado) regarding the 

diversity of deposits within the CACB during the data gathering and construction of the database presented in appendix 

A of this report. The first SCRV grade and tonnage models 

were prepared during the CACB assessment workshop in 

Cape Town during February, 2010 with extensive input 

from the workshop participants: David Broughton, Michael 

Christie, Susan Frost-Killian, Murray Hitzman, Douglas 

Jack, Sharad Master, and Jonathan Woodhead. Their insights, 

contributions, and participation are gratefully acknowledged. 

The preliminary grade and tonnage models were provided 

by Michael Zientek. Hannah Campbell, Kasandra Lindsey, 

Drew Luders, and Heather Parks created the figures, and 

reviews by USGS colleagues James Bliss, Pamela Dunlap, 

and Daniel Mosier substantially improved the report.
Chapter 3. Sediment-Hosted Structurally Controlled Replacement and Vein Copper Deposits in the Central African Copperbelt 85

6.5

7

7.5

8

8.5

0.05 0.2 0.5 0.8 0.95

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.05 0.2 0.5 0.8 0.95

Log copper grade, in percent

Normal quantile plot Normal quantile plot

Log ore, in metric tons

-2.33-1.64-1.28-0.67 0.0 0.67 1.28 1.64 2.33 -2.33-1.64-1.28-0.67 0.0 0.67 1.28 1.64 2.33

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Ore, in metric tons

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.1 10.80.60.40.30.2 10765432

Copper grade, in percent

ProbabilityProbability

n=11 n=11

2 Mt 18 Mt 170 Mt 1.1 2.2 4.6

1e+4 1e+5 1e+6 1e+7 1e+8 1e+9 1e+10

Table 3-3. Summary statistics for tonnage and grade of structurally controlled replacement and vein (SCRV) copper deposits.

[g/t, grams per metric ton]

Mineral resource Number of samples 25th quantile Median 75th quantile Mean

Ore, metric tons 11 4,000,000 15,000,000 57,000,000 76,000,000

Copper grade, percent 11 1.36 1.82 4.02 2.58

Silver grade, g/t 3 4.7 10 115 43

Cobalt grade, percent 3 0.08 0.10 0.64 0.27

Contained copper metal, metric tons 11 140,000 210,000 1,000,000 1,000,000

Figure 3-12. Histogram, box plot, and normal quantile plot illustrating the distribution of log-transformed values for tonnage and 

copper grade for 11 structurally controlled replacement and vein copper deposits.

Figure 3-13. Cumulative frequency plots of grade and tonnage for 11 structurally controlled replacement and vein copper deposits. 

Each red circle is a data point for a deposit; the blue curve is the calculated lognormal distribution based on the population 

parameters of the data. Values for tonnage and grade for the 90th, 50th, and 10th probability values of the distribution are illustrated 

by extending a horizontal line from the vertical axis to the data curve, then drawing a vertical line to the horizontal axis. The value 

for the point where the vertical line intersects the horizontal axis is labeled. For some deposits, values for some metals are not 

reported, resulting in a censored or truncated dataset. For these metals, only the probability values for the data points with reported 

values are illustrated. Mt, million metric tons.
86 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

References Cited (Chapters 1, 2, and 3)

American Association of Petroleum Geologists, 1996, Sedimentary provinces of the world (BG)—Including GIS layer 

for giant oil and gas fields, a GIS mapping file in ARC/

INFO: American Association of Petroleum Geologists Datapages 52, CD-ROM.

Abdullah, S., Chmyriov, V.M., and Dronov, V.I., 1980, Geology 

and mineral resources of Afghanistan: Ministry of Mines and 

Industries, Afghan Geological and Mines Survey, Republic 

of Afghanistan Geological and Mineral Survey, 419 p.

Abramov, B.N., 2008, Petrochemistry of the Paleoproterozoic 

Udokan copper-bearing sedimentary complex: Lithology 

and Mineral Resources, v. 43, p. 37–43.

African Eagle Resources plc, 2009, Ndola project fact sheet: 

African Eagle Resources plc, 2 p., accessed Mar. 23, 2010, 

at http://www.africaneagle.co.uk/downloads/Ndola_

November_2009.pdf.

Aleinikoff, J.N., Hayes, T.S., Evans, K.V., Mazdab, F.K., Pillers, R.M., and Fanning, C.M., 2012, SHRIMP U-Pb ages of 

xenotime and monazite from the Spar Lake red bed-associated Cu-Ag deposit, western Montana—Implications for ore 

genesis: Economic Geology, v. 107, p. 1251–1254.

Alexander Mining plc, 2005, Alexander Mining plc placing by 

Evolution Securing Limited of 66,666,667 ordinary shares at 

10p each at 30 pence per ordinary share and admission of the 

whole to the ordinary share capital to trading on AIM: Alexander Mining plc AIM admission document, 24 March 2005, 

118 p., accessed September 5, 2011, at http://www.

alexandermining.com/files/AXM_Admission_Document.pdf .

Andritzky, G., 1998, Mineral map of Namibia: Geological 

Survey of Namibia, 1 map on 2 sheets, scale 1:1,000,000.

Annels, A.E., 1974, Some aspects of the stratiform ore deposits of the Zambian Copperbelt and their genetic significance, 

in Bartholome, P., ed., Gisements stratiformes et provinces 

cupriferes [Stratiform copper deposits and provinces]: 

Liège, Belgium, La Société Géologique de Belgique, 

p. 235–254.

Annels, A.E., 1984, The geotectonic environment of Zambian 

copper-cobalt mineralization: Journal of the Geological 

Society of London, v. 141, no. 2, p. 279–289.

Annels, A.E., 1989, Ore genesis in the Zambian Copperbelt, with particular reference to the northern sector of the 

Chambishi Basin, in Boyle, R.W., Brown, A.C., Jefferson, 

C.W., Jowett, E.C., and Kirkham, R.V., eds., Sedimenthosted stratiform copper deposits: Geological Association 

of Canada Special Paper 36, p. 427–452.

Anvil Mining Ltd., 2009, Annual information form for the 

financial year ended Dec. 31, 2008 [dated March 31, 

2009]: Anvil Mining Ltd. Annual Information Form, 67 p., 

accessed October 4, 2010, at http://www.anvilmining.com/

files/090331%20AIF%202008%20_clean_(1).pdf.

Arkhangel’skaya, V.V., Bykhovskiy, L.Z., Volodin, R.N., 

Narkelyun, L.F., Skursky, V.C., Trubachev, A.I., and 

Chechetkin, V.S., 2004, Udokanskoe mednoe i Katuginskoe 

redkometall’noe mestorozhdeniya Chitinskoioblasti, Rossiya [Udokan copper and Katuginskoe rare metal deposit 

Chita Oblast, Russia]: Chita, Russia, Administration of 

Chita, 519 p. [In Russian.]

Arthurs, J.W., 1992, Geological map of the Solwezi area, 

degree sheet 1226, NW quarter, with part of 1126 SW, to 

accompany report no. 36 by J.W. Arthrus: Zambia Geological Survey, 1 sheet, scale 1:100,000.

Bakun, N.N., Volodin, R.N., and Krendelev, F.P., 1966, Genesis of the Udokansk cupriferous sandstone deposit (Chitinsk 

Oblast): International Geology Review, v. 8, no. 4, 

p. 455–466.

Barron, J.W., Broughton, D.W., Armstrong, R.A., and 

Hitzman, M.W., 2003, Petrology, geochemistry and age of 

gabbroic bodies in the Solwezi area, northwestern Zambia, 

in Contributions presented at the 3rd IGCP-450 Conference, 

Proterozoic sediment-hosted base metal deposits of western 

Gondwana: Conference and Field workshop Lubumbashi 

2003, Lubumbashi, D.R. Congo, p. 75–77.

Bartholomé, P., 1962, Les minerais cupro-cobaltifères de 

Kamoto (Katanga-Ouest). I Pétrographie [Minerals of 

Kamoto copper-cobalt (Katanga West). I Petrography]: 

Studia Universitatis “Lovanium,” Faculté des Sciences, 

Léopoldville (Kinsasha), v. 14, 40 p.

Bartholomé, P., 1974, On the diagenetic formation of ores 

in sedimentary beds with special reference to the Kamoto 

copper deposit, Shaba, Zaire, in Bartholomé, P., ed., Gisements stratiformes et provinces cupriferes [Stratiform 

copper deposits and provinces]: Liège, Belgium, La Société 

Géologique de Belgique, p. 203–214. 

Bartholomé, P., Evrard, P., Katekesha, F., Lopez-Ruiz, J., and 

Ngongo, M., 1976, Diagenetic ore-forming processes at 

Kamoto, Katanga, Republic of Congo, in Amstutz, G.C., 

and Barnard, A.J., eds., Ores in sediments—VIII. International Sedimentological Congress, Heidelberg, August 

31–September 3, 1971: Berlin, Heidelberg, New York, 

Springer-Verlag, International Union of Geological Sciences, Series A, no. 3., p. 21–42.

Barton, P.B., Brew, D.A., Ayuso, R.A., Gamble, B.M., John, 

D.A., Ludington, S.D., Lindsey, D.A., Force, E.R., Goldfarb, R.J., and Johnson, K.M., 1995, Recommendations 
References Cited (Chapters 1, 2, and 3) 87

for assessments of undiscovered mineral resources: U.S. 

Geological Survey Open-File Report 95-82, 139 p.

Bateman, A.M., 1935, The Northern Rhodesia copper belt: 

Washington, D.C., XVI International Geological Congress, 

Copper Resources of the World, v. 2, p. 713–740.

Bavarian Geological State Office, 2004, Zechstein, verbreitung 

und tiefenlage der Trias basis [Zechstein, extent and depth of 

the Triassic base]: Bavarian Ministry of Economic Affairs, 

Infrastructure, Transport and Technology, Geothermal Atlas 

of Bavarian geological data and temperature maps, scale 

1:500,000, accessed September 9, 2010, at http://www.stmwivt.

bayern.de/fileadmin/user_upload/stmwivt/Themen/Energie_

und_Rohstoffe/Dokumente_und_Cover/Geothermie/Geothermieatlas_Zechstein.pdf.[In German.]

Bawiec, W.J., and Spanski, G.T., 2012, Quick-start guide for 

version 3.0 of EMINERS—Economic Mineral Resource 

Simulator: U.S. Geological Survey Open-File Report 

2009–1057, 26 p., accessed July 15, 2012, at http://pubs.

usgs.gov/of/2009/1057/. (This report supplements USGS 

OFR 2004–1344.)

Beales, F.W., and Hardy, J.L., 1977, The problem of recognition of occult evaporites with special reference to southeast 

Missouri: Economic Geology, v. 72, p. 487–490.

Bechtel, Achim, Sun Yuzhuang, Püttmann, Wilhelm, Hoernes, 

Stephan, and Hoefs, Jochen, 2001, Isotopic evidence for 

multi-stage base metal enrichment in the Kupferschiefer 

from the Sangerhausen Basin, Germany: Chemical Geology, 

v. 176, p. 31–49.

Beck, Richard, 1905, The nature of ore deposits: New York, 

Engineering and Mining Journal, v. 1 and 2, 685 p.

Beitler, Brenda, Chan, J.A., and Parry, W.T., 2003, Bleaching of Jurassic Navajo Sandstone on Colorado Plateau 

Laramide highs—Evidence of exhumed hydrocarbon supergiants?: Geology, v. 31, p. 1041–1044. 

Bekker, A., Holland, H.D., Wang, P.-L., Rumble III, D., Stein, 

H.J., Hannah, J.L., Coetzee, L.L., and Beukes, N.J., 2004, 

Dating the rise of atmospheric oxygen: Nature, v. 427, p. 

117–120.

Bekker, A., Kaufman, A.J., Kardu, J.A., and Eriksson, K.A., 

2005, Evidence for Paleoproterozoic cap carbonates in 

North America: Precambrian Research, v. 137, p. 167–206.

Bender, Friedrich, 1975, Geology of the Arabian Peninsula—

Jordan: U.S. Geological Survey Professional Paper 560-I, 

36 p., 3 plates.

Benson, D.G., 1974, Geology of the Antigonish Highlands and 

Cape George map areas, Nova Scotia: Geological Survey of 

Canada Memoir 376, 90 p.

Bliss, J.D., Orris, G.J., and Menzie, W.D., 1987, Changes in 

grade, volume, and contained gold during the mining lifecycle of gold placer deposits: Canadian Mining and Metallurgical Bulletin, v. 80, no. 903, p. 75–80.

Bogdanov, Yu.V., Bur’yanova, E.Z., Kutyrev, E.I., Feoktistov, 

V.P., and Trifonov, N.P., 1973, Stratifitsirovannye mestorozhdeniya medi SSSR [Stratabound copper deposits of the 

USSR]: Leningrad, Nedra Publishing House, 312 p

Bogdanov, Yu.V., Kochin, G.G., Kutyrev, E.I., Travin, L.V., 

and Feoktistov, V.P., 1966, Geology, formation conditions 

and distribution of cupriferous sandstones in northeastern 

Olekma-Vitim mountain province: International Geology 

Review, v. 8, no. 11, p. 1305–1315.

Boleneus, D.E., Appelgate, L.M., Stewart, J.H., and Zientek, 

M.L., 2005, Stratabound copper-silver deposits of the Mesoproterozoic Revett Formation, Montana and Idaho, with 

a section on databases and spatial-data files for the geology and mineral deposits of the Revett Formation by D.E. 

Boleneus, L.M. Appelgate, M.H. Carlson, D.W. Chase, and 

M.L. Zientek: U.S. Geological Survey Scientific Investigations Report 2005-5231, 66 p., 3 plates, Excel spreadsheet, 

spatial database. (Also available at http://pubs.usgs.gov/

sir/2005/5231/.)

Box, S.E., Syusyura, Boris, Hayes, T.S., Taylor, C.D., Zientek, M.L., Hitzman, M.W., Seltmann, Reimar, Chechetkin, 

Vladimir, Dolgopolova, Alla, Cossette, P.M., and Wallis, 

J.C., 2012, Sandstone copper assessment of the Chu-Sarysu 

Basin, Central Kazakhstan: U.S. Geological Survey Scientific Investigations Report 2010–5090–E, 63 p. and spatial 

data tables, accessed November 6, 2012, at 

http://pubs.usgs.gov/sir/2010/5090/e/. 

Brognon, G.P., and Verrier, G.R., 1966, Oil and geology in 

Cuanza basin of Angola: American Association of Petroleum Geologists Bulletin, v. 50, p. 108–158.

Brookins, D.G., 1976, Uranium deposits of the Grants, New 

Mexico, Mineral Belt: United States Energy Research and 

Development Agency GJBX-16(76), 143 p.

Broughton, D., and Rogers, T., 2010a, Discovery of the 

Kamoa Cu deposit, Central African Copperbelt, DRC: PowerPoint and PDF Slide Presentations, Society of Economic 

Geologists 2010 Conference Keystone, Colo., Oct 2–5, 

2010, 19Broughton.pdf, CD-ROM.
88 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Broughton, D., and Rogers, T., 2010b, Discovery of the Kamoa 

Cu deposit, Central African Copperbelt, D.R.C., in Goldfarb, 

R.J., Marsh, E.E., and Monecke, Thomas, eds., The challenge of 

finding new mineral resources—Global metallogeny, innovative 

exploration, and new discoveries, Volume I—Gold, silver, and 

copper-molybdenum: Society of Economic Geologists Special 

Publication Number 15, p. 287–297.

Broughton, D.W., Hitzman, M.W., and Stephens, A.J., 2002, 

Exploration history and geology of the Kansanshi Cu (-Au) 

deposit, Zambia, in Goldfarb, R.J., and Nielson, R.L., eds., 

Integrated methods for discovery—Global exploration in 

the twenty-first century: Littleton, Colorado, Society of 

Economic Geologists Special Publication 9, p. 141–153.

Broughton, D.W., Valorose, C.P., Coker, S.A., Spera, S.L., 

Venendaal, J.F., and Hitzman, M.W., 2004, Congolesestyle hypogene and supergene copper mineralization at the 

Kalengwa deposit, Zambia: Geological Society of America 

Abstracts with Programs, v. 36, no. 5, Abstract 222-11, p. 

517. (Also available at http://gsa.confex.com/gsa/2004AM/

finalprogram/abstract_78090.htm.)

Brown, A.C., 1971, Zoning in the White Pine copper deposit, 

Ontonagon County, Michigan: Economic Geology, v. 66,

 p. 543–573.

Brown, A.C., 1986, Marquette District—Lower Proterozoic 

copper and iron: Geological Association of Canada, Mineralogical Association of Canada, Canadian Geophysical 

Union, Joint Annual Meeting, Ottawa 1986, Field Trip 1 

Guidebook, p. 10–20.

Brown, A.C., 1992, Sediment-hosted stratiform copper deposits: Geoscience Canada, v. 19, no. 3, p. 99–115.

Brown, A.C., 1997, World-class sediment-hosted stratiform 

copper deposits—Characteristics, genetic concepts, and 

metallotects: Australian Journal of Earth Sciences, v. 44,

 p. 317–328.

Brown, A.C., 2005, Refinements for footwall red bed diagenesis in the sediment-hosted stratiform copper deposits model: 

Economic Geology, v. 100, no. 4, p. 765–771.

Brown, A.C., 2009, A process-based approach to estimating 

the copper derived from red beds in the sediment-hosted 

stratiform copper deposit model: Economic Geology, v. 104, 

p. 857–868.

Buffington, D.L., King, N.D., Stevens, M.G., and Tschabrun, 

D.B., 2005, Technical report of the Lisbon Valley Copper Project, San Juan County, Utah: Pincock, Allen, and 

Holt Technical Report, prepared for Constellation Copper 

Corporation, September 22, 2005, 9434.00, 108 p., accessed 

September 5, 2011, at http://www.pitecreative.com/staging/

CCU/art/lisbon/PAH_REVISED_Final_9_27.pdf.

Bureau of Geology and Mineral Resources of Sichuan Province, 

comp., 1991, Geologic map of Sichuan Province, People's 

Republic of China, Map 1 in Bureau of Geology and Mineral Resources of Sichuan Province, Regional geology of 

Sichuan Province: Beijing, Geological Publishing House, 

People's Republic of China Ministry of Geology and Mineral 

Resources Geological Memoirs Series 1, no. 23, 1 map on 4 

sheets, scale 1:1,000,000. [In Chinese with English abstract.]

Bureau of Geology and Mineral Resources of Yunnan Province, comp., 1990, Geologic map of Yunnan Province of 

the People's Republic of China, Map 1 in Bureau of Geology and Mineral Resources of Yunnan Province, Regional 

geology of Yunnan Province: Beijing, Geological Publishing House, People's Republic of China Ministry of Geology and Mineral Resources Geological Memoirs Series 1, 

no. 21, 1 map on 4 sheets, scale 1:1,000,000. [In Chinese 

with English abstract.]

Cailteux, J.L.H., Kampunzu, A.B., and Lerouge, C., 2007, The 

Neoproterozoic Mwashya-Kansuki sedimentary rock succession in the Central African Copperbelt, its Cu-Co mineralization, and regional correlations: Gondwana Research, v. 

11, no. 3, p. 414–431.

Cailteux, J.L.H., Kampunzu, A.B., Lerouge, C., Kaputo, A.K., 

and Milesi, J.P., 2005, Genesis of sediment-hosted stratiform copper-cobalt deposits, central African Copperbelt: 

Journal of African Earth Sciences, v. 42, p. 134–158.

Cairney, T., and Kerr, C.D., 1998, Geology of the Kabwe 

area—Explanation of degree sheet 1428, NW quarter: Geological Survey of Zambia Report No. 47, 40 p.

Canfield, D.E., 2005, The early history of atmospheric oxygen—Homage to Robert M. Garrels: Annual Reviews of 

Earth and Planetary Science, v. 33, p. 1–36.

Cathles, L.M., III, Oszczepalski, S awomir, and Jowett, 

E.C., 1993, Mass balance evaluation of the late diagenetic 

hypothesis for Kupferschiefer Cu mineralization in the 

Lubin Basin of southwestern Poland: Economic Geology, v. 

88, p. 948–956.

Chandler, F.W., 1988, Diagenesis of sabkha-related, sulphate 

nodules in the Early Proterozoic Gordon Lake Formation, 

Ontario, Canada: Carbonates and Evaporites v. 3, no. 1, 

p. 75–94.

Chartry, G., and Franceschi, G., comps., 2004, Mineral occurrences database and GIS map of the Democratic Republic 

of [the] Congo: Royal Museum for Central Africa, scale 

1:2,000,000, CD-ROM.

Committee for Mineral Reserves International Reporting 

Standards, 2006, International reporting template for the 

reporting of exploration results, mineral resources, and mineral reserves: Committee for Mineral Reserves International 

Reporting Standards, 53 p., accessed, at http://www.crirsco.

com/crirsco_template_first_ed_0806.pdf.
References Cited (Chapters 1, 2, and 3) 89

Cowley, W.M., Katona, L.F., and Gouthes, G., 2009, Assessment of mineral prospectivity of the northern Flinders 

Ranges using GIS analysis: Government of South Australia, Primary Industries and Resources, SA Report Book 

2009/19, 102 p.

Cox, D.P., 1986, Descriptive model of sediment-hosted Cu, in

Cox, D.P., and Singer, D.A., eds., Mineral deposit models: 

U.S. Geological Survey Bulletin 1693, p. 205.

Cox, D.P., 2003a, revised 2007, Descriptive model of reducedfacies Cu 30b.2, in Cox, D.P., Lindsey, D.A., Singer, D.A., 

Moring, Barry, and Diggles, M.F., Sediment-hosted copper 

deposits of the world—Deposit models and database: U.S. 

Geological Survey Open-File Report 03–107, version 1.3, 10 

p. (Also available at http://pubs.usgs.gov/of/2003/of03-107/.)

Cox, D.P., 2003b, revised 2007, Descriptive model of Revett 

Cu 30b.4, in Cox, D.P., Lindsey, D.A., Singer, D.A., Moring, 

Barry, and Diggles, M.F., Sediment-hosted copper deposits 

of the world—Deposit models and database: U.S. Geological Survey Open-File Report 03–107, version 1.3, 5 p. (Also 

available at http://pubs.usgs.gov/of/2003/of03-107/.)

Cox, D.P., 2003c, revised 2007, Descriptive model of sediment-hosted Cu 30b.1, in Cox, D.P., Lindsey, D.A., Singer, 

D.A., Moring, Barry, and Diggles, M.F., Sediment-hosted 

copper deposits of the world—Deposit models and database: U.S. Geological Survey Open-File Report 03–107, 

version 1.3, 11 p. (Also available at http://pubs.usgs.gov/

of/2003/of03-107/.)

Cox, D.P., and Bernstein, L.R., 1986, Descriptive model of 

Kipushi Cu-Pb-Zn, in Cox, D.P., and Singer, D.A., eds., 

Mineral deposit models: U.S. Geological Survey Bulletin 

1693, p. 227.

Cox, D.P., and Singer, D.A., 2003a, revised 2007, Grade and 

tonnage model of sediment-hosted Cu 30b, in Cox, D.P., 

Lindsey, D.A., Singer, D.A., Moring, B.C., and Diggles, 

M.F., Sediment-hosted copper deposits of the world—

Deposit models and database: U.S. Geological Survey 

Open-File Report 03–107, version 1.3, 5 p. (Also available 

at http://pubs.usgs.gov/of/2003/of03-107/.)

Cox, D.P., and Singer, D.A., 2003b, revised 2007, Grade and 

tonnage model of redbed Cu 30b.3, in Cox, D.P., Lindsey, 

D.A., Singer, D.A., Moring, B.C., and Diggles, M.F., Sediment-hosted copper deposits of the world—Deposit models 

and database: U.S. Geological Survey Open-File Report 

03–107, version 1.3, 5 p. (Also available at http://pubs.usgs.

gov/of/2003/of03-107/).

Cox, D.P., and Singer, D.A., 2003c, revised 2007, Grade and 

tonnage model of reduced-facies Cu 30b.2, in Cox, D.P., 

Lindsey, D.A., Singer, D.A., Moring, B.C., and Diggles, 

M.F., Sediment-hosted copper deposits of the world—

Deposit models and database: U.S. Geological Survey 

Open-File Report 03–107, version 1.3, 5 p. (Also available 

at http://pubs.usgs.gov/of/2003/of03-107/).

Cox, D.P., and Singer, D.A., 2003d, revised 2007, Grade and 

tonnage model of Revett Cu 30b.4, in Cox, D.P., Lindsey, 

D.A., Singer, D.A., Moring, B.C., and Diggles, M.F., Sediment-hosted copper deposits of the world—Deposit models 

and database: U.S. Geological Survey Open-File Report 

03–107, version 1.3, 4 p. (Also available at http://pubs.usgs.

gov/of/2003/of03-107/.)

Cox, D.P., Barton, P.R., and Singer, D.A., 1986, Introduction, 

in Cox, D.P., and Singer, D.A., eds. Mineral deposit models: 

U.S. Geological Survey Bulletin 1693, p. 1–10. 

Cox, D.P., Carrasco, R., André-Ramos, O., Hinojosa-Velasco, 

A., and Long, K.R., 1992, Copper deposits in sedimentary 

rocks, in U.S. Geological Survey and Servicio Geologico 

de Bolivia, Geology and mineral resources of the Altiplano 

and Cordillera Occidental, Bolivia: U.S. Geological Survey 

Bulletin 1975, p. 95–108.

Cox, D.P., Lindsey, D.A., Singer, D.A., and Diggles, M.F., 

2003, revised 2007, Sediment-hosted copper deposits of 

the world—Deposit models and database: U.S. Geological 

Survey Open-File Report 03–107 version 1.1, 50 p. (Also 

available at http://pubs.usgs.gov/of/2003/of03-107/.)

Cressman, E.R., 1985, The Prichard Formation of the lower 

part of the Belt Supergroup (middle Proterozoic) near 

Plains, Sanders County, Montana: U.S. Geological Survey 

Bulletin 1553, 64 p.

Dardir, A.A., editor-in-chief, 1998, Metallogenic map of Arab 

Republic of Egypt (Metallic and non metallic deposits), 

Sheet no. 11: Cairo, Egypt, The Egyptian Geological Survey 

and Mining Authority, scale 1:1,000,000.

Davidson, D.M., 1931, Geology and ore deposits of Chambishi, Northern Rhodesia: Economic Geology, v. 26,

 p. 131–152.

Davis, G.R., 1954, The origin of the Roan Antelope copper 

deposit of Northern Rhodesia: Economic Geology, v. 49, no. 

6, p. 575–615.

De Putter, Thierry, Mees, Florian, Decrée, Sophie, and 

Dewaele, Stijn, 2010, Malachite, an indicator of major Pliocene Cu mobilization in a karstic environment (Katanga, 

Democratic Republic of Congo): Ore Geology Reviews, v. 

38, p. 90–100.

Decrée, Sophie, Deloule, Étienne, Ruffet, Gilles, Dewaele, 

Stijn, Mees, Florias, Marignac, Christian, Yans, Johan, and 

De Putter, Thierry, 2010, Geodynamic and climate controls 

in the formation of Mio-Pliocene world-class oxidized 

cobalt and manganese ore in the Katanga province, DR 

Congo: Mineralium Deposita, v. 45, p. 621–629.
90 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Demesmaeker, G., François, A., and Oosterbosch, R., 1963, La 

tectonique des gisements cuprifère stratiformes du Katanga, 

in Lombard, J., and Nicolini, P., eds., Gisements stratiformes de cuivre en Afrique [Stratiform copper deposits in 

Africa]: Paris, Association des Services Géologique Africains [Association of African Geological Surveys], 

p. 47–115.

Department of Primary Industries and Resources South 

Australia, 2006, Neoproterozic geological provinces: South 

Australian Resources Information Geoserver, accessed 

October 5, 2011, at http://www.pir.sa.gov.au/minerals/sarig.

Dewaele, Stijn, Muchez, Philippe, Heijlen, Wouter, Boutwood, Amanda, Lemmon, Terry, and Tyler, Roger, 2006, 

Reconstruction of the hydrothermal history of the Cu-Ag 

vein-type mineralisation at Dikulushi, Kundelungu foreland, 

Katanga, D.R. Congo: Journal of Geochemical Exploration, 

v. 89, p. 376–379.

Diatchkov, S.A., 1994, Principles of classification of reserves 

and resources in the CIS countries: Mining Engineering, v. 

46, no. 3, p. 214217.

Discovery Minerals Ltd., 2010, Annual Report 2010: Brisbane, Australia, Discovery Minerals Ltd. Annual Report, 

79 p., accessed September 2, 2011, at http://www.discoverymetals.com/annual-reports-7/2010-annual-report5?y=2010&m=10.

Dixon, Roger, 2007, Independent technical report on the 

assets of Nikanor plc in the Katanga Province, Democratic 

Republic of Congo: SRK Consulting Project Technical 

Report No. 385848, prepared for Nikanor plc and Katanga 

Mining Ltd., November 28, 2007, 185 p. (Also available at 

http://www.sedar.com.)

Dixon, Roger, Simposya, Victor, Takolia, Ebrahim, Waldeck, 

Wally, Salter, Henrietta, von Wielligh, Anton, Naismith, 

Alan, Cilliers, Petrus, and McNeill, R., 2009, An independent technical report on the material assets of Katanga 

Mining Limited, Katanga Province, Democratic Republic 

of Congo (“DRC”): SRK Consulting Technical Report, 

prepared for Katanga Mining Ltd., March 17, 2009, 216 p. 

(Also available at http://www.sedar.com.)

Doornenbal, J.C., and Stevenson, A.G., eds., 2010, Petroleum 

geological atlas of the Southern Permian Basin area: TNO 

Geological Survey of the Netherlands, DVD.

Dreisinger, D., Shaw, M., Britton, S., Hodson, T., Gluck, T., 

and Ross, T., 2010, Baja Mining Corp. El Boleo (Boleo) 

Project, Technical Report update 2, March 2010, Baja California South, Mexico: Baja Mining Corp., March 2, 2010, 

206 p., accessed July 16, 2011, at http://www.bajamining.

com/static/technical_reports/2010%20MAR%20-%20 http://

www.bajamining.com/static/technical_reports/2010%20

MAR%20-%20Technical%20Report.pdf%20Report.pdf.

Drexel, J.F., McCallum, Wayne, Reid, Anthony, Preiss, 

Wolfgang, Cowley, Wayne, Katona, Laszlo, and Gouthas, 

George, 2009, Review of the Burra Mine Project, 1980-

2008—A progress report: Government of South Australia, Primary Industries and Resources SA Report Book 

2008/16, 40 p., accessed September 2, 2011, at http://www.

minerals.pir.sa.gov.au/__data/assets/pdf_file/0011/92999/

RB200800016.pdf.

Durieux, C.G., and Brown, A.C., 2007, Geological context, 

mineralization, and timing of the Juramento sedimenthosted stratiform copper-silver deposit, Salta district, northwestern Argentina: Mineralium Deposita, v. 42, p. 879–899.

Dyson, I.A., 2004, Geology of the eastern Willouran Ranges—

Evidence for earliest onset of salt tectonics in the Adelaide 

Geosyncline: MESA Journal, v. 35, p. 48–56.

El Desouky, H.A., 2008, Group metallogenesis of stratiform 

copper deposits in the Lufilian orogen, Democratic Republic of Congo: Geodynamics and geofluids Research Group 

at K.U. Leuven, accessed August 4, 2011, at http://geo.

kuleuven.be/g&g/hamdy/index.htm.

El Desouky, H.A., Muchez, P., and Cailteux, J., 2009, Two 

Cu-Co sulfide phases and contrasting fluid systems in the 

Katanga Copperbelt, Democratic Republic of Congo: Ore 

Geology Reviews, v. 36, p. 315–332.

El Desouky, H.A., Muchez, Philippe, and Tyler, Roger, 2008, 

The sandstone-hosted stratiform copper mineralization at 

Mwitapile and its relation to the mineralization at Lufukwe, 

Lufilian foreland, Democratic Republic Of Congo: Ore 

Geology Reviews, v. 34, p. 561–579.

Ellis, M.W., and McGregor, J.A., 1967, The Kalengwa copper 

deposit in northwestern Zambia: Economic Geology, v. 62, 

p. 781–797.

Elston, W.E., 1967, Summary of the mineral resources of 

Bernalillo, Sandoval, and Sante Fe Counties, New Mexico: 

New Mexico Bureau of Mines and Mineral Resources 

Bulletin 81, 81 p.

Entwistle, L.P., and Bouin, L.O., 1955, The chalcocite-ore 

deposits at Corocoro, Bolivia: Economic Geology, v. 50, 

p. 555–570.

Evans, D.G., and Nunn, J.A., 1989, Free thermohaline convection in sediments surrounding a salt column: Journal of 

Geophysical Research, v. 94, no. B9, p. 1413–1422.

Evans, H.T., Jr., 1959, The crystal chemistry and mineralogy of vanadium, in Garrels, R.M., and Larsen, E.S., 3rd, 

comps., Geochemistry and mineralogy of the Colorado 

Plateau uranium ores: United States Geological Survey 

Professional Paper 320, p. 91-102.
References Cited (Chapters 1, 2, and 3) 91

Federal Institute for Geosciences and Natural Resources, 1993, 

Geologische Karte der Bundesrepublik Deutschland [Geological map of Germany]: Federal Institute for Geosciences 

and Natural Resources, scale 1:1,000,000. [In German.]

First Quantum Minerals Ltd., 2010, Annual information form, 

as of December 31, 2009: First Quantum Minerals Ltd. 

Annual Information Form, 88 p., accessed March 16, 2011, 

at http://www.first-quantum.com/i/pdf/AIF.pdf.

Flint, S.S., 1989, Sediment-hosted stratabound copper deposits 

of the Central Andes, in Boyle, R.W., Brown, A.C., Jefferson, C.W., Jowett, E.C., and Kirkham, R.V., eds., Sedimenthosted stratiform copper deposits: Geological Association 

of Canada Special Paper 36, p. 371–398.

Folk, R.L., 1959, Practical petrographic classification of 

limestones: American Association of Petroleum Geologists 

Bulletin, v. 43, p. 1–38.

Foster, M.D., 1959, Chemical study of the mineralized clays, in 

Garrels, R.M., and Larsen, E.S., 3rd, comps., Geochemistry 

and mineralogy of the Colorado Plateau uranium ores: United 

States Geological Survey Professional Paper 320, p. 121–132.

François, Armand, and Cailteux, Jacques, 1981, La couverture Katangienne, entre les socles de Zilo et de la Kabompo, 

République du Zaïre - région de Kolwezi. [The Katangian 

cover between the basements of Zilo and Kabompo, Republic 

of Zaire, Kolwezi area]: Annales Musee Royal de l’Afrique 

Centrale, Série in-octavo, Sciences Geologiques, no. 87, 50 p.

François, Armand, 1973, L’extrémité occidentale de l’arc 

cuprifere Shabien—Etude geologique [The western end of 

the Shabien copper arc—Geological study]: [Likasi, Zaire], 

Département Géologique de la Gécamines, 65 p.

François, Armand, 2006, La partie centrale de l’Arc cuprifere du Katanga; étude géologique [The central part of the 

Katanga Copperbelt; geologic study]: Musée Royal de 

l’Afrique Centrale, Tervuren African Geoscience Collection, 

v. 109, 61 p.

Freeman, P.V., comp., 1988, Description of mineral deposits 

on the Copperbelt (and Kabwe, Nampundwe): Lukasa, 

Zambia, [Consolidated Copper Mines Ltd. (ZCCM) unpublished company report], 88 p.

Fugro Robertson, Ltd., 2008, Fugro Tellus sedimentary basins 

of the world map: AAPG Datapages, accessed November 

6, 2009, at http://www.datapages.com/AssociatedWebsites/

GISOpenFiles/FugroTellusSedimentaryBasinsofthe

WorldMap.aspx.

Gablina, I.F., 1981, New data on formation conditions of 

the Dzhezkazkan copper deposit: International Geology 

Reviews, v. 23, no. 11, p. 1303–1311.

Garlick, W.G, and Fleisher, V.D., 1972, Sedimentary environment of Zambian copper deposition: Geologie en Mijnbouw, v. 51, no. 3, p. 277–298.

Garlick, W.G., 1961, Chambishi, in Mendelsohn, F., ed., The 

geology of the Northern Rhodesian Copperbelt: London, 

Macdonald & Co. (Publishers) Ltd., p. 281–297.

Garrity, C.P., and Soller, D.R., 2009, Database of the geologic 

map of North America; adapted from the map by J.C. Reed, 

Jr. and others (2005): U.S. Geological Survey Data Series 

424, accessed April 16, 2012, at http://pubs.usgs.gov/ds/424/.

Garven, G., 1985, The role of regional fluid flow in the genesis 

of the Pine Point deposit, western Canada sedimentary 

basin: Economic Geology, v. 80, p. 307–324.

GECO Project, 2009, Mineralogical database of the Katangan 

Copperbelt: GECO Project Web Page, accessed August 5, 

2011, at http://www.gecoproject.org/?page=minerals&.

Geological Survey of Norway, 2008, Fact sheet for deposit 2017–

006, deposit area—Repparfjord: Norges geologiske undersokelse [Geological Survey of Norway], The Ore Database, 

accessed September 2, 2011, at http://aps.ngu.no/pls/oradb/

minres_deposit_fakta.Main?p_objid=766&p_spraak=E.

GeoPubs, 1998, Geological dataset of the Central African 

Copperbelt: Essex, England, GeoPubs [dataset purchased 

from http://www.geopubs.co.uk/home.htm and downloaded 

on December 16, 2009].

Giusiano, Adolfo, Franchini, M.B., Impiccini, Agnes, and 

Pons, M.J., 2008, Mineralización de Cu en sedimentitas 

Mesozóicas del Grupo Neuquén y hábitat de los hidrocarburos en la Dorsal de Huincul Neuquén [Cu mineralization 

in Mesozoic sediments of the Neuquén Group and habitat 

of hydrocarbons in the Neuquén Huincul Ridge]: Salta, 17° 

Congreso Geológico Argentino, Actas 2 [17th Argentina 

Geological Congress, Proceedings 2, Summary in full for 

the Neuquén Basin Symposium], p. 769–770.

Good, P.I., and Hardin, J.W., 2009, Common errors in statistics (and how to avoid them), third edition: Hoboken, New 

Jersey, Wiley, 273 p.

Goossens, Pierre, 2007, Phoenix rising in an uncertain 

world—New mining activities in Katanga: Académie 

Royale des Sciences d’Outre-Mer, Bulletin des séances, v. 

53, no. 3, p. 361–385.

Gourlay, A.W., 2005, Technical report on the Coates Lake 

copper deposit, Nahanni Mining District, western Northwest Territories: Lumina Resources Corp. Technical Report, 

August 15, 2005, 38 p., accessed September 5, 2011, at 

http://www.westerncoppercorp.com/content/pdfs/technical_reports/Aug1505_Redstone_TechnicalReport.pdf.

Gray, Anton, 1932, The Mufulira copper deposit, Northern 

Rhodesia: Economic Geology, v. 27, no. 4, p. 315–343.

Gray, G.G, Pottorf, R.J., Summa, L.L., May, S.R., and Holl, 

J.E., 1996, Fluid flow and the Cashin fault: Geological Society of America Abstracts with Programs, v. 23, p. A254.
92 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Gregory, J., Hanssen, G., Cameron, A., Thomas, I., Cooper, D., 

and Broom, M., 2006, Frontier Copper Project, Haut Katanga 

Province, Democratic Republic of Congo: First Quantum 

Minerals Ltd. Technical Report, pursuant to National Instrument 43-101 of the Canadian Securities Administrators, 

December 21, 2006, 118 p. (Also available at http://www.

sedar.com.) 

Guiraud, René, 1999, Paleozoic geodynamic evolution of the 

northeastern African epicratonic basins—An outline, in 

Feist, R., Talent, J.A., and Daurer, A., eds., North Gondwana—Mid-Paleozoic terranes, stratigraphy and biota: Gabhandungen der Geologicshen Bundesanstalt, v. 54, p. 15–26.

Gunson Resources Ltd., 2009, Mount Gunson Copper Project 

preliminary feasibility studies—MG 14 deposit: Gunson Resources Ltd. ASX Release October 12, 2009, 8 p., 

accessed July 16, 2011, at http://www.gunson.com.au/files/

reports/Preliminary%20Feasibility%20Study%2012%20

oct%2009.pdf.

Haddon, I.G., comp., 2001, Sub-Kalahari geological map: 

Council for Geosciences, South Africa, 1 sheet, scale 

1:2,500,000.

Haest, M., Muchez, P., Dewaele, S., Boyce, A.J., von Quadt, 

A., and Schneider, J., 2009, Petrographic, fluid inclusion 

and isotopic study of the Dikulushi Cu-Ag deposit, Katanga 

(D.R.C.)—Implications for exploration: Mineralium 

Deposita, v. 44, p. 505–522.

Haest, M., Muchez, P., Dewaele, S., Franey, N., and Tyler, R., 

2007, Structural control on the Dikulushi Cu-Ag deposit, 

Katanga, Democratic Republic of Congo: Economic Geology, v. 102, p. 1321–1333.

Haest, M., Muchez, P., Petit, J.C.J., and Vanharcke, F., 2009, 

Cu isotope ratio variations in the Dikulushi Cu-Ag deposit, 

D.R.C.—Of primary origin or induced by supergene 

reworking?: Economic Geology, v. 104, no. 7, 

p. 1055–1064.

Haest, Maarten, Schneider, Jens, Cloquet, Christophe, 

Latruwe, Kris, Vanhaecke, Frank, and Muchez, Philippe, 

2010, Pb isotopic constraints on the formation of the Dikulushi Cu–Pb–Zn–Ag mineralisation, Kundelungu Plateau 

(Democratic Republic of Congo): Mineralium Deposita, v. 

45, no. 4, p. 393–410.

Hagni, R.D., and Gann, D.E., 1976, Microscopy of copper 

ore at the Creta mine, southwestern Oklahoma, in Johnson, 

K.S. and Croy, R.L., eds., Stratiform copper deposits of the 

Midcontinent Region, a symposium: Oklahoma Geological 

Survey Circular 77, p. 40–50.

Hahn, G.A., and Thorson, J.P., 2006, Geology of the Lisbon 

Valley sandstone-hosted copper deposits, San Juan County, 

Utah, in Bon, R.L., Gloyn, R.W., and Park, G.M., eds., Mining districts of Utah: Utah Geological Association Publication 32, p. 511–533.

Hammarstrom, J.M., Zientek, M.L., Orris, G.J., and Taylor, 

C.D., 2010, Global Mineral Resource Assessment—Challenges and opportunities for developing and refining assessment methods [abs.]: Geological Society of America Denver 

2010 Annual Meeting Final Program Web Page, accessed 

November 22, 2010, at http://gsa.confex.com/gsa/2010AM/

finalprogram/abstract_178026.htm.

Harris, D.P., 1984, Mineral resource appraisal—Mineral 

endowment, resources, and potential supply—Concepts, 

methods, and cases: Oxford, Claredon Press, 445 p.

Hayes, T.S., 1984, Zonation and paragenesis of the Spar Lake 

stratabound copper-silver deposit in the Belt Supergroup, 

Montana (abs.): Geological Society of America Abstracts 

with Programs, v. 16, p. 534.

Hayes, T.S., 1990, A preliminary study of thermometry and 

metal sources of the Spar Lake stratabound copper-silver 

deposit, Belt Supergroup, Montana: U.S. Geological Survey 

Open-File Report 90-0484, 30 p.

Hayes, T.S., and Einaudi, M.T., 1986, Genesis of the Spar 

Lake stratabound copper-silver deposit, Montana—Part I. 

Controls inherited from sedimentation and pre-ore diagenesis: Economic Geology, v. 81, p. 1899–1931.

Hayes, T.S., Landis, G.P., Whelan, J.F., Rye, R.O., and Moscati, 

R.J., 2012, The Spar Lake strata-bound Cu-Ag deposit formed 

across a mixing zone between trapped natural gas and metalbearing brine: Economic Geology, v. 107, p. 1223–1250.

Hayes, T.S., Rye, R.O., Whelan, J.F., and Landis, G.P., 1989, 

Geology and sulphur-isotope geothermometry of the Spar 

Lake stratabound Cu-Ag deposit in the Belt Supergroup, 

Montana, in Boyle, R.W., Brown, A.C., Jefferson, C.W., 

Jowett, E.C., and Kirkham, R.V., eds., Sediment-hosted 

stratiform copper deposits: Geological Association of 

Canada Special Paper 36, p. 319–338. 

Hitzman, M.W., Selley, David, and Bull, Stuart, 2010, Formation of sedimentary rock-hosted stratiform copper deposits 

through Earth history: Economic Geology, v. 105, 

p. 627–639.

Hitzman, Murray, Kirkham, Rodney, Broughton, David, 

Thorson, Jon, and Selley, David, 2005, The sedimenthosted stratiform copper ore system, in Hedenquist, J.W., 

Thompson, J.F.H., Goldfarb, R.J., and Richards, J.P., eds., 

Economic Geology—One hundredth anniversary volume 

1905-2005: Boulder, Colorado, Society of Economic Geologists, p. 609–642.

Hoy, L.D., and Ohmoto, H., 1989, Constraints for the genesis 

of redbed-associated stratiform Cu deposits from sulphur 

and carbon mass-balance relations, in Boyle, R.W., Brown, 

A.C., Jefferson, C.W., Jowett, E.C., and Kirkham, R.V., 

eds., Sediment-hosted stratiform copper deposits: Geological Association of Canada Special Paper 36, p. 135–149.
References Cited (Chapters 1, 2, and 3) 93

Huderek, Richard, 2008a, Katangan Copperbelt: Google Earth 

KML file, accessed July–September 2009 and October 

2010, at http://maps.google.com/maps/ms?ie=UTF8&hl=nl

&oe=UTF8&msa=0&msid=118078989952556264569.0004

4e1e24afa04af0cca&output=kml.

Huderek, Richard, 2008b, Zambian_copperbelt.kml: Google 

Earth KML file, accessed July 8, 2009 and Oct. 2010, at 

http://maps.google.com/maps/ms?hl=en&gl=us&ie=UTF8

&oe=UTF8&msa=0&msid=118078989952556264569.0004

51715e9f065a35bbe&output=kml.

Isachsen, Y.W., and Evenson, C.G., 1956, Geology of uranium 

deposits in the Shinarump and Chinle Formatons on the 

Colorado Plateau, in Page, R., Stocking, H.E., and Smith, 

H.G., comps., Contributions to the geology of uranium and 

thorium: United States Geological Survey Professional 

Paper 300, p. 263-280.

Ivanhoe Nickel & Platinum, 2011, Developing Kamoa’s 

world-class copper discovery and Platreef’s nickel, platinum, palladium, copper & gold: Ivanhoe Nickel & Platinum 

Brochure, 2 p., accessed February 29, 2012, at http://www.

ivanplats.com/i/pdf/2011-March-Brochure.pdf.

Jackson, G.C.A., 1932, The ores of the N’Changa Mine and 

extensions, Northern Rhodesia: Economic Geology, v. 27, 

no. 3, p. 247–280.

Jackson, M.P.A., and Talbot, C.J., 1991, A glossary of salt 

tectonics: Texas Bureau of Economic Geology Geological 

Circular 91-4, 44 p. 

Jackson, M.P.A., Warin, O.N., Woad, G.M., and Hudec, M.R., 

2003, Neoproterozoic allochthonous salt tectonics during 

the Lufilian Orogeny in the Katangan Copperbelt, central 

Africa: Geological Society of America Bulletin, v. 115, no. 

3, p. 314–330.

Jakubiak, Z., and Smakowski, T., 1994, Classification of mineral reserves in the former Comecon countries, in Whateley, 

M.K., and Harvey, P.K., eds., Mineral resource evaluation 

II—Methods and case histories: Geological Society, London, Special Publications 79, p. 17–28.

Japan International Cooperation Agency, and Metal Mining 

Agency of Japan [JICA and MMAJ], 1996a, Report on the 

cooperative mineral exploration in the Chambishi southeast 

area the Republic of Zambia: Japan International Cooperation Agency and Metal Mining Agency of Japan, 53 p., 

accessed May 27, 2010, at http://lvzopac.jica.go.jp/external/library?func=function.opacsch.mmindex&view=view.

opacsch.toshoshozodsp〈=eng&shoshisbt=1&shoshino=0000

088693&volno=0.

Japan International Cooperation Agency and Metal Mining 

Agency of Japan, 1996b, Report on the cooperative mineral 

exploration in the Chambishi Southeast area, consolidated 

report: Japan International Cooperation Agency and Metal 

Mining Agency of Japan, 69 p. and appendixes.

Johnson, K.S., 1976, Permian copper shales of southwestern Oklahoma, in Johnson, K.S. and Croy, R.L., eds., 

Stratiform copper deposits of the Midcontinent Region, a 

symposium: Oklahoma Geological Survey Circular 77, 

p. 3–14.

Jowett, E.C., 1986, Genesis of Kupferschiefer Cu-Ag deposits 

by convective flow of Rotliegendes brines during Triassic 

rifting: Economic Geology, v. 81, p. 1823–1837.

Jowett, E.C., 1987, Formation of sulfide-calcite veinlets in the 

Kupferschiefer Cu-Ag deposits in Poland by natural hydrofracturing during basin subsidence: Journal of Geology, v. 

95, p. 513–526.

Jowett, E.C., Pearce, G.W., and Rydzewski, Andrzej, 1987, 

A Mid Triassic paleomagnetic age of the Kupferschiefer 

mineralization in Poland, based on a revised apparent polar 

wander path for Europe and Russia: Journal of Geophysical 

Research, v. 92, no. B1, p. 581–598.

Kalahari Minerals plc, 2006, Placing of 40,000,000 new 

Ordinary Shares at 15p per share—Admission to trading 

on AIM: Kalahari Minerals plc, 15 March 2006, 97 p., 

accessed September 5, 2011, at http://www.kalahari-minerals.com/Investor_Relations/Document_Downloads/Admission_Document/Admission_Document/File.aspx?id=213.

Kalahari Minerals plc, 2008, Investor roadshow, March 

2008: Kalahari Minerals plc, Company Update 

11.03.2008, accessed September 5, 2011, at http://www.

kalahari-minerals.com/News/Presentations/Company_

Update_11_03_2008/File.aspx?id=55.

Kamitani, Masaharu, Okumura, Kimio, Teraoka, Yoji, 

Miyano, Sumiko, and Watanabe, Yasusi, 2007, Mineral deposit data of mineral resources map of east Asia: 

Geological Survey of Japan, DataSheet.xls, accessed 

September 6, 2011, at http://www.gsj.jp/Map/EN/docs/

overseas_doc/DataSheet.xls.

Kamona, A.F., and Günzel, A., 2007, Stratigraphy and base 

metal mineralization in the Otavi Mountainland, Northern 

Namibia—A review and regional interpretation: Gondwana 

Research, v. 11, no. 3, p. 396–413.

Kampunzu, A.B., Akanyang, P., Mapeo, R.B.M., Modie, B.N., 

and Wendorff, M., 1998, Geochemistry and tectonic significance of the Mesoproterozoic Kgwebe metavolcanic rocks 

in northwest Botswana—Implications for the evolution of 

the Kibaran Namaqua-Natal Belt: Geological Magazine, v. 

135, p. 669–683.
94 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Kampunzu, A.B., Cailteux, J.L.H., Kamona, A.F., Intiomale, 

M.M., and Melcher, F., 2009, Sediment-hosted Zn-Pb-Cu 

deposits in the Central African Copperbelt: Ore Geology 

Reviews, v. 35, p. 263–297.

Key, R.M., Liyungu, A.K., Njamu, F.M., Somwe, V., Banda, 

J., Mosley, P.N., and Armstrong, R.A., 2001, The western 

arm of the Lufilian arc in NW Zambia and its potential for 

copper mineralization: Journal of African Earth Sciences, v. 

33, p. 503–528.

Key, Roger, 1998, National geologic map of Botswana—Digital format: Botswana Geological Survey, scale 1:1,000,000.

Khalifa, M.A., Soliman, H.E., and Wanas, H.A., 2006, The 

Cambrian Araba Formation in northeastern Egypt—Facies 

and depositional environments: Journal of Asian Earth Sciences, v. 27, p. 873–884.

Kidwell, A.L., and Bower, R.R., 1976, Mineralogy and microtextures of sulfides in the Flowerpot Shale of Oklahoma 

and Texas, in Johnson, K.S. and Croy, R.L., eds., Stratiform 

copper deposits of the Midcontinent Region, a symposium: 

Oklahoma Geological Survey Circular 77, p. 51–60.

Kirkham, R.V., 1989, Distribution, settings, and genesis of 

sediment-hosted stratiform copper deposits, in Boyle, R.W., 

Brown, A.C., Jefferson, C.W., Jowett, E.C., and Kirkham, 

R.V. eds., Sediment-hosted stratiform copper deposits: Geological Association of Canada Special Paper 36, p. 3–38.

Kirkham, R.V., 1996a, Sediment-hosted stratiform copper, 

in Eckstrand, O.R., Sinclair, W.D., and Thorpe, R.I., eds., 

Geology of Canadian Mineral Deposit Types: Geological 

Survey of Canada, Geology of Canada, no. 8, p. 223–240.

Kirkham, R.V., 1996b, Volcanic redbed copper, in Eckstrand, 

O.R., Sinclair, W.D., and Thorpe, R.I., eds, Geology of Canadian mineral deposit types: Geological Survey of Canada, Geology of Canada, no. 8, p. 241–252. (Also available as Geological 

Society of America, The Geology of North America, v. P-1.)

Kirkham, R.V., Carrière, J.J., and Rafer, A.B. comp., 2003, 

World distribution of sediment-hosted, stratiform copper 

deposits and occurrences: Geological Survey of Canada, 

unpublished, accessed Sept 26, 2009, at http://apps1.gdr.

nrcan.gc.ca/gsc_minerals/index.phtml?language=en-CA.

Kirkham, R.V., Carrière, J.J., Laramee, R.M., and Garson, 

D.F., 1994, Global distribution of sediment-hosted stratiform copper deposits and occurrences: Geological Survey 

of Canada Open File 2915b, 256 p.

Kirkham, Rodney, and Broughton, David, 2005, Supplement 

to the sediment-hosted stratiform copper ore system, in 

Hedenquist, J.W., Thompson, J.F.H., Goldfarb, R.J., and 

Richards, J.P., eds., Economic Geology—One hundredth 

anniversary volume 1905-2005: Littleton, Colorado, Society 

of Economic Geologists, Inc., p. 609–642.

Klitzsch, Eberhard, List, F.K., and Pöhlmann, Gerhard, 1987, 

Geological map of Egypt, Sheet NH 36 SE South Sinai: 

Cairo, Egypt, Cononco Coral and the Egyptian General 

Petroleum Company, scale 1:500,000.

Knitzchke, Gerhard, 1995, Metall- und produktionsbilanz für 

die Kupferschieferlagerstätte im Südöstlichen Harzvorland 

[Metal production and balance sheet for the Kupferschiefer 

deposit in the southeastern Harz foreland], in Jankowski, 

Günter, editor, Zur geschichte des Mansfelder Kupferschieferbergbaus [The mining history of the Mansfeld Kupferschiefer]: Clausthal-Zellerfeld, Germany, GDMB-Infomationgesellschaft, p. 270–303.

Konnikov, A.Z., Kornutova, E.I., Kuteinikov, E.S., Magnushevski, E.L., Mironyuk, E.P., Shtein, L.F., and Krapivko, 

S.Y.,1984 [1990], [Geological map of the USSR, new 

series, sheet O-49(50) Bodaybo, Map of pre-Quaternary 

rocks]: Leningrad, Ministry of Geology of the USSR, 

VSEGEI, scale 1:1,000,000. [In Russian.]

Kopp, Jürgen, Simon, Andreas, and Göthel, Michael, 2006, 

Die kupfer-lagerstatte Spremberg-Graustein in Südbrandenburg [The copper deposit Spremberg-Graustein in South 

Brandenburg]: Brandenburgische Geowissen-schaftliche 

Beiträge, Kleinmachnow, v. 13, no. 1/2, p. 117–132., 

accessed September 5, 2011, at http://www.zit-bb.de/sixcms/media.php/4055/Ver%25C3%25B6ffKoppSimonG%25

C3%25B6thelSprembergnk.pdf.

Kulick, Jens, Leifeld, D., and Theuerjahr, A.-K., 1986, Section B: German Kupferschiefer excursion, in Jowett, E.C., 

ed., Kupferschiefer and other sediment-hosted deposits in 

central Europe: Geological Association of Canada, Mineralogical Association of Canada, Canadian Geophysical Union 

Joint Annual Meeting, Ottawa, Ontario, 1986 Field Trip 

Guidebook 12, p. 11–34.

Jackson, M.P.A., and Talbot, C.J., 1991, A glossary of salt 

tectonics: Texas Bureau of Economic Geology Geological 

Circular 91-4, 44 p. 

Jackson, M.P.A., Warin, O.N., Woad, G.M., and Hudec, M.R., 

2003, Neoproterozoic allochthonous salt tectonics during 

the Lufilian Orogeny in the Katangan Copperbelt, central 

Africa: Geological Society of America Bulletin, v. 115, no. 

3, p. 314–330.

Laghmouch, M., comp., 2008a, Carte géologique de la République Démocratique Du Congo, L’arc cuprifére du Katanga 

[Geologic map of the Democratic Republic of the Congo, 

Katanga Copperbelt]: Royal Museum of Central Africa, 

scale 1:500,000.

Laghmouch, M., comp., 2008b, L’Arc cuprifère du Katanga: 

géologie et minéralisations (2007)—GIS and raster [Katanga 

copper arc—geology and mineralization]: Tervuren, Belgium, 

Royal Museum of Central Africa, scale 1:500,000, CD-ROM.
References Cited (Chapters 1, 2, and 3) 95

Lagzdina, G.Yu., Mironyuk, E.P., Mikhaylov, K.V., Nikolaeva, M.G., and Tarasova, V.G., 1978, [Geological map of 

the USSR, new series, sheet O-(50),51 Aldan, Map of the 

pre-Quaternary rocks]: Ministry of Geology of the USSR, 

VSEGEI, scale 1:1,000,000. [In Russian.]

Lattanzi, Christopher, 1997, Mining engineer’s report: Micon 

International Ltd., prepared for KGHM Polska Miedź S.A., 

July 7, 1997, accessed June 22, 2009, at http://www.kghm.

pl/_files/File/Gielda/Prospekt-en/Mining%20Engineers%20

Report.pdf.

Le Burn, Steve, and Hayward, Peter, 2011, Kapulo Project, 

DRC: Coffey Mining Pty Ltd. National Instrument 43-101 

Technical Report, prepared for Mawson West Ltd, revised 7 

March, 2011, refiled March 18, 2011, 101 p. (Also available 

at http://www.sedar.com.)

Lefebure, D.V., and Alldrick, D.J., 1996, Sediment-hosted Cu 

± Ag ± Co, in Lefebure, D.V., and Höy, T, eds., Selected 

British Columbia mineral deposit profiles, Volume 2—

Metallic deposits: British Columbia Ministry of Employment and Investment, Open File 1996-13, p. 13–16.

Lefebvre, J.J., 1974, Mineralisations cupro-cobaltiferes associees aux horizons pyroclastiques situes dans le faisceau 

superieur de la Serie de Roan, a Shituru, Chaba Zaire [The 

cupro-cobaltiferous mineralization associated with pyroclastic horizons in the upper part of Roan series, Shituru, Shaba, 

Zaire], in Bartholome, P., ed., Gisements stratiformes et 

provinces cupriferes [Stratiform copper deposits and provinces]: Liège, Belgium, La Société Géologique de Belgique, 

p. 103–122.

Liedtke, Maren, and Vasters, Jürgen, 2008, Renaissance des 

deutschen Kupferschieferbergbaus? [Renaissance of German 

copper shale mining?]: Bundesanstalt für Geowissenschaften 

und Rohstoffede Commodity Top News Number 29, 15 p., 

accessed September 5, 2011, at http://www.bgr.bund.de/DE/

Gemeinsames/Produkte/Downloads/Commodity_Top_News/

Rohstoffwirtschaft/29_kupferschieferbergbau.pdf.

Lindgren, W., Graton, L.C., and Gordon, C.H., 1910, The ore 

deposits of New Mexico: U.S. Geological Survey Professional Paper 68, 361 p.

Lindsey, D.A., and Cox, D.P., 2003, revised 2007, Descriptive 

model of Redbed Cu 30b.3, in Cox, D.P., Lindsey, D.A., 

Singer, D.A., Moring, B.C., and Diggles, M.F., Sedimenthosted copper deposits of the world—Deposit models 

and database: U.S. Geological Survey Open-File Report 

03–107, version 1.3, 5 p. (Also available at http://pubs.usgs.

gov/of/2003/of03-107/.)

Lindsey, D.A., Woodruff, L.G., Cannon, W.F., Cox, D.P., and 

Heran, W.D., 1995, Sediment-hosted Cu deposits (model 

30b; Cox, 1986), in du Bray, E.A., ed., Preliminary compilation of descriptive geoenvironmental mineral deposit 

models: U.S. Geological Survey Open-File Report 95-0831, 

p. 214–224. (Also available at http://pubs.usgs.gov/of/1995/

ofr-95-0831/CHAP28.pdf.)

Ljunggren, P., and Meyer, H.C., 1964, The copper mineralization in the Corocoro Basin, Bolivia: Economic Geology, v. 

59, p. 110–125.

Lockwood, R.P., 1972, Geochemistry and petrology of some 

Oklahoma red bed copper occurrences: Norman, University 

of Oklahoma, Ph.D. dissertation, 125 p.

Lopatin, N.V., 1971, [Temperature and geologic time as 

factors in coalification]: Izvestiya Akademii Nauk URSS, 

Seriya Geologicheskaya, v. 3, p. 95–196. [In Russian.]

Lur’ye, A.M., and Gablina, I.F., 1972, The copper source in 

production of Mansfeld-type deposits in the west Ural Foreland: Geochemistry International, v. 9, p. 56–67.

Mach, Leah, Clarke, Peter, Michael, Nick, and Puspa, Patricia, 

2006, Technical report, Cashin copper deposit: SRK Consulting Project Reference No. 162302, prepared for Constellation Copper Corporation, May 2006, 76 p. (Also available 

at http://www.sedar.com.)

MacIntyre, T.J., Thorson, J.P., and Hitzman, M.W., 2004, 

Setting the stage for sediment-hosted copper—Fault related 

hydrocarbon(?) bleaching and copper ore at the Cashin 

Mine, Montrose County, Colorado: Geological Society 

of America Abstracts with Programs, v. 36, no. 5, p. 516. 

(Also available at https://gsa.confex.com/gsa/2004AM/

finalprogram/abstract_74076.htm.)

MacIntyre, T.J., Thorson, J.P., and Hitzman, M.W., 2005, 

Fault-related bleaching and sediment-hosted copper mineralization around the Paradox Valley, Montrose, Colorado: 

Window to the World, Geological Society of Nevada Symposium, Program with Abstract, Reno/Sparks, Nevada, May 

2005, p. 64. 

MacKevett, Jr., E.M., Cox, D.P., Potter, II, R.W., and Silberman, M.L., 1997, Kennecott-type deposits in the Wrangell 

Mountains, Alaska—High-grade copper ores near a basaltlimestone contact, in Goldfarb, R.J., and Miller, L.D., eds., 

Mineral deposits of Alaska: Economic Geology Monograph 

9, p. 66–89.

Maiden, Ken, 2011, Exploration models—You can flirt with 

a model but you shouldn’t marry one: Australian Institute 

of Geoscientists (AIG) Base Metals Symposium, June 

2011, Perth, Australia, accessed July 15, 2011, at http://

aig.org.au/attachments/Ken%20Maiden%20Exploration%20

Models.pdf.

Marjonen, R., 2000, Geological map of the Kitwe-Mufulira 

area, quarter degree sheets 1228 SW and part of 1228 NW, 

to accompany report no. 60 by R. Marjonen: Zambia Geological Survey, scale 1:100,000.

Marquillas, R.A., del Papa, Cecilia, and Sabino, I.F., 2005, 

Sedimentary aspects and paleoenvironmental evolution of a 
96 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

rift basin—Salta Group (Cretaceous-Paleogene), northwestern Argentina: International Journal of Earth Sciences, v. 

94, p. 94–113.

Marston and Marston, Inc., 2011, Resource estimate and NI 

43-101 technical report for Copperwood Project, Ironwood 

Michigan: Marston and Marston, Inc. Technical Report, 

prepared for Orvana Resources US Corp., March 7, 2011, 

135 p., accessed July 27, 2011, at http://www.orvana.com/

projects/pdf/110307-copperwood-technical-report.pdf.

Martins-Neto, M.A., and Catuneanu, O., 2010, Rift sequence 

stratigraphy: Marine and Petroleum Geology, v. 27,

 p. 247–253.

Master, S., Rainaud, C., Armstrong, R.A., Phillips, D., and 

Robb, L.J., 2005, Provenance ages of the Neoproterozoic 

Katanga Supergroup (Central African Copperbelt), with 

implications for basin evolution, in Robb, L.J., Cailteux, 

J.L.H., and Sutton, S.J., eds., Recent advances in the geology and mineralization of the Central African Copperbelt 

dedicated to the memory and work of Henri Ali Basira 

Kampunzu: Journal of African Earth Sciences, v. 42, no. 

1-5, p. 41–60.

Mawson West Ltd., 2006, Technical update-Kapulo Copper 

Project–DRC/Zambia, ASC Release: Perth, Western Australia, Mawson West Ltd., 7 p.

McCarthy, J.H., and Reimer, G.M., 1986, Advances in soil gas 

exploration for natural resources: Journal of Geophysical 

Research, v. 91, p. 12327–12338.

McGowan, R.R., Roberts, S., Foster, R.P., Boyce, A.J., and 

Coller, D., 2003, Origin of the copper-cobalt deposits of the 

Zambian Copperbelt—An epigenetic view from Nchanga: 

Geology, v. 31, p. 497–500.

McKinney, Mark, Brown, Ian, Goldschmidt, Allan, and 

Lomberg, Ken, 2009, Tschudi copper deposit—Geological 

modelling and mineral resource estimate: Coffey Mining 

(SA) (Pty) Ltd., prepared for Weatherly Mining Namibia 

Ltd., 13 November 2009, 127 p., accessed September 5, 

2011, at http://www.weatherlyplc.com/downloads/pdf/

Coffey_Tschudi_Resource_Estimate_13112009_Final.pdf.

Mendelsohn, F., 1989, Central/southern African ore shale 

deposits, in Boyle, R.W., Brown, A.C., Jefferson, C.W., 

Jowett, E.C., and Kirkham, R.V. eds., Sediment-hosted 

stratiform copper deposits: Geological Association of 

Canada Special Paper 36, p. 453–469.

Metcalfe, R., Rochelle, C.A., Savage, D., and Higgo, J.W., 

1994, Fluid-rock interactions during continental red 

bed diagenesis—Implications for theoretical models of 

mineralization in sedimentary basins, in Parnell, J., ed., 

Geofluids—Origins, migration and evolution of fluids in 

sedimentary basins: Geological Society, London, Special 

Publications 78, p. 301–324.

Michalik, M., 1997, Chlorine containing illites, copper 

chlorides and other chlorine bearing minerals in the ForeSudetic copper deposit (Poland) (extended abstract), in 

Papunen, H., ed., Mineral deposits—Research and exploration—Where do they meet?: Rotterdam, Balkema, 

p. 543–546.

Michalik, M., 2001, Diagenesis of the Weissliegend sandstones in the southwest margin of the Polish Rotliegend 

Basin: Krakow, Poland, Polska Akademia Nauk, Prace 

Mineralogiczne 91, 176 p.

Moore, T.A., 1968b, Geological map of the Ndola area (degree 

sheet 1228 SE quarter) to accompany Report No. 20: Zambia Geological Survey Department, scale 1:100,000.

Morrison, S.J., and Parry, W.T., 1986, Formation of carbonatesulfate veins associated with copper ore deposits from saline 

basin brines, Lisbon Valley, Utah—Fluid inclusion and 

isotopic evidence: Economic Geology, v. 81, no. 12, 

p. 1853–1866.

Mosier, D.L., Berger, V.I., and Singer, D.A., 2009, Volcanogenic massive sulfide deposits of the world—Database and 

grade and tonnage models: U.S. Geological Survey OpenFile Report 2009-1034, accessed February 17, 2012, at 

http://pubs.usgs.gov/of/2009/1034/.

Mosier, D.L., Singer, D.A., and Cox, D.P., 1986, Grade and 

tonnage model of sediment-hosted Cu, in Cox, D.P., and 

Singer, D.A., eds., Mineral deposit models: U.S. Geological 

Survey Bulletin 1693, p. 206–208. 

Musée Royal de l’Afrique Centrale, 2006a, Carte géologique 

de la République Démocratique du Congo, Region de Kolwezi-Kalukundi, Partie ouest de l’arc cuprifère du Katanga 

[Geological map of the Democratic Republic of Congo, 

Kolwezi-Kalukundi region-Western Katanga Copper Arc] 

[GIS and raster]: Tervuren [Belgium], Musée Royal de 

l’Afrique centrale, scale 1:100,000.

Musée Royal de l’Afrique Centrale, 2006b, Carte géologique 

de la République Démocratique du Congo, Region de 

Likasi, Partie centrale de l’arc cuprifère du Katanga [Geologic map of the Democratic Republic of Congo, Likasi 

Region, central part of the Katangan Copperbelt] [GIS and 

raster]: Tervuren [Belgium], Musée Royal de l’Afrique 

Centrale, scale 1:100,000.

Musée Royal de l’Afrique Centrale, 2008, Carte géologique de 

la République Démocratique du Congo, Region de KolweziKalukundi-Likasi, Parties occidentale et centrale de l’arc 

cuprifère du Katanga [Geological map of the Democratic 

Republic of Congo, Kolwezi Region-Kalukundi-Likasi Parties of Western and Central Katanga Copper Arc]: Tervuren [Belgium], Musée Royal de l’Afrique Centrale, scale 

1:200,000, CD-ROM.

Nawrocki, Jerzy, 2000, Clay mineralogy, crystallinity, and 

K-Ar ages of illites within the Polish Zechstein basin—
References Cited (Chapters 1, 2, and 3) 97

Implications for the age of Kupferschiefer mineralization—

A discussion: Economic Geology, v. 95, p. 241–242. 

Nawrocki, Jerzy, 1997, Permian to Early Triassic magnetostratigraphy from the Central European Basin in Poland—

Implications on regional and worldwide correlations: Earth 

and Planetary Science Letters, v. 152, p. 37–58.

Newton, Joseph, and Wilson, C.L., 1942, Metallurgy of copper: New York, John Wiley & Sons, Inc., 539 p.

Nicholson, S.W., Shirey, S.B., Schulz, K.J., and Green, J.C., 

1997, Rift-wide correlation of 1.1 Ga midcontinent rift 

system basalts—Implications for multiple mantle sources 

during rift development: Canadian Journal of Earth Sciences, v. 34, p. 504–520.

Nimry, Y.F., ed., 1973, The copper and manganese prospects 

of the Wadi Araba: Hashemite Kingdom of Jordan, Natural 

Resources Authority, Mining Division, 107 p. 

Notebaart, C.W., and Vink, B.W., 1972, Ore minerals of the 

Zambian Copperbelt: Geologie en Mijnbouw, v. 51, 

p. 337–345.

Novachuk, Oleg, 2008, Kazakhmys plc—Strong base for 

stability and growth: Kazakhmys plc Presentation at Credit 

Suisse Global Steel and Mining Conference, September 

2008, accessed September 5, 2011, at http://www.kazakhmys.

com/en/resources/383/2008%20Global%20Steel%20and%20

Mining%20Conference%20Credit%20Suisse.pdf.

Nowack, G.J., Speczik, Stanislaw, and Oszczepalski, Slawomir, 2001, Petrographic composition of organic matter 

in the Kupferschiefer horizon of Poland, in Piestrz ski, A., 

and others, eds., Mineral deposits at the beginning of the 

21st century, Proceedings of the joint sixth biennial SGASEG meeting, Kraków, Poland, 26-29 August 2001: Lisse, 

Belgium, A.A. Balkema Publishers, p. 67–70.

O’Sullivan, John, 2006, Scott Grant claims, license 06436, 

Canfield Creek Prospect, Cumberland County, Nova Scotia, 

NTS 11E/13a, Report on prospecting and compilation of 

data: [Nova Scotia Department of Natural Resources Mineral Resources Branch] Assessment Report AR2006-083, 

16 p., accessed September 5, 2011, at http://www.gov.ns.ca/

natr/meb/data/ar/2006/AR_ME_2006-083.pdf.

Oszczepalski, S awomir, 1989, Kuperschiefer in southwestern 

Poland—Sedimentary environments, metal zoning, and 

ore controls, in Boyle, R.W., Brown, A.C., Jefferson, C.W., 

Jowett, E.C., and Kirkham, R.V., eds., Sediment-hosted 

stratiform copper deposits: Geological Association of 

Canada Special Paper 36, p. 571–600.

Oszczepalski, S awomir, 1999, Origin of the Kupferschiefer 

polymetallic mineralization in Poland: Mineralium Deposita, v. 34, p. 599–613.

Oszczepalski, S awomir, and Speczik, Stanis aw, 2011, Rudy 

miedzi i srebra [copper and silver ore], in Wo kowicza, 

Stanis awa, Smakowskiego, Tadeusza, and Speczika, Stanis

awa, eds., Bilans perspektywicznych zasobów kopalin Polski wg stanu na 31 XII 2009 r. [Balance of Polish prospective minerals resources as of 31 December 2009]:Warsaw, 

Ministry of Environment, Polish Geological Institute, p. 

76-93, accessed September 5, 2011 at http://www.pgi.gov.

pl/pl/component/docman/doc_download/218-bilanszasobow-perspektywicznych-2010.pdf.

Oszczepalski, S awomir, Nowak, G.J., Bechtel, A., and Zák, 

Karel, 2002, Evidence of oxidation of the Kupferschiefer 

in the Lubin-Sieroszowice deposit, Poland—Implications 

for Cu-Ag and Au-Pt-Pd mineralization: Polish Geological 

Institute Geological Quarterly, v. 46, p. 1–23.

Peters, S.G., and Bawiec, W.J., 2007, Sediment-hosted copper, 

in Peters, S.G., Ludington, S.D., Orris, G.J., Sutphin, D.M., 

Bliss, J.D., and Rytuba, J.J., eds., and the U.S. Geological Survey-Afghanistan Ministry of Mines Joint Mineral 

Resource Assessment Team, Preliminary non-fuel mineral resource assessment of Afghanistan: U.S. Geological 

Survey Open-File Report 2007-1214, p. 274–298, accessed 

November 9, 2012, at http://pubs.usgs.gov/of/2007/1214/.

Piestrzy ski, Adam, Pieczonka, Jadwiga, and Głuszek, Adam, 

2002, Red bed-type gold mineralization, Kupferschiefer, 

south-west Poland: Mineralium Deposita, v. 37, p. 512–528.

Pinaar, P.J., 1961, Bwana Mkubwa area, in Mendelsohn, F., 

ed., The geology of the Northern Rhodesian Copperbelt: 

London, Macdonald & Co. (Publishers) Ltd., p. 467–484.

Polish Geological Institute, 2009, Wykaz złóś rud miedzi 

[list of copper ore deposits]: Polish Geological Institute, 

accessed September 16, 2010, at http://www.pgi.gov.pl/

surowce_mineralne/PDF-tabele2/Rudy%20miedzi.pdf.

Pollastro, R.M., Karshbaum, A.S., and Viger, R.J., 1997, Maps 

showing geology, oil and gas fields and geologic provinces 

of the Arabian Peninsula: U.S. Geological Survey Open-File 

Report 97-470B, version 2.0, accessed April 16, 2012, at 

http://pubs.usgs.gov/of/1997/ofr-97-470/OF97-470B/.

Pretorius, Awie, and Park, Vivian, 2011, Resource estimate 

update, Hana Mining Ltd., Ghanzi Copper-silver Project, 

Ghanzi District, Botswana: Sphynx Consulting CC Technical Report for NI 43-101, prepared for Hana Mining Ltd. 

February 3, 2011, 235 p., accessed July 15, 2011, at http://

www.hanamining.com/i/pdf/HanaMining-43-101-Report_

Feb%202011_ALL.pdf.

Prosser, Sarah, 1993, Rift-related linked depositional systems 

and their seismic expression, in Williams, G.D., and Dobb, 

A., eds., Tectonics and seismic sequence stratigraphy: Geological Society of London Special Publication 71, p. 35–66.

Rabb’a, Ibrahim, and Nawasreh, Mohammed, 2006, Mineral 

status and future opportunity—Copper: Hashemite Kingdom of Jordan, Natural Resources Authority, Geological 

Survey Administration, 21 p., accessed July 16, 2011, at 

http://www.nra.gov.jo/images/stories/pdf_files/Copper.pdf.
98 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Rackley, R.I., 1976, Origin of western-states type uranium 

mineralization, in Wolf, K.H., ed., Handbook of Stratabound and Stratiform Ore Deposits, v. 7: Elsevier, New 

York, p. 89–156.

Rainbird, R.H., Jefferson, C.W., and Young, G.M., 1996, 

The early Neoproterozoic sedimentary Succession B of 

northwestern Laurentia—Correlations and paleogeographic 

significance: Geological Society of America Bulletin, v. 

108, p. 454–70.

Reidy, Paddy, Dorling, Simon, Adams, Patrick (Rick), Brans, 

Rhett, and deKlerk, Quinton, 2009, Kipoi Copper Project in 

the Democratic Republic of the Congo, May 29, 2009: CSA 

Global pty Ltd. NI 43-101 Technical Report, prepared for 

Tiger Resources Ltd., May 29, 2009, 214 p. (Also available 

at http://www.sedar.com.) 

Rentzsch, A.E., 1974, The Kupferschiefer in comparison with 

the deposits of the Zambian Copperbelt, in Bartholomé, P., 

ed., Gisements stratiformes et provinces cupriferes [Stratiform copper deposits and provinces]: Liège, Belgium, La 

Société Géologique de Belgique, p. 395–418.

Riese, W.C., 1980, The Mount Taylor uranium deposit, San 

Mateo, New Mexico: Albuquerque, New Mexico, University of New Mexico, Unpublished Ph.D. dissertation, 643 p.

Root, D.H., Menzie, W.D., and Scott, W.A., 1992, Computer 

Monte Carlo simulation in quantitative resource estimation: 

Natural Resources Research, v. 1, no. 2, p. 125–138.

Ruan, Huichu, Hua, Renmin, and Cox, D.P., 1991, Copper 

deposition by fluid mixing in deformed strata adjacent to a 

salt diapir, Dongchuan area, Yunnan Province, China: Economic Geology, v. 86, p. 1539–1545.

Ruxton, P.A., 1986, Sedimentology, isotopic signature, and ore 

genesis of the Klein Aub copper mine, South West Africa/

Namibia, in Anhaeusser, C.R., and Maske, S., eds., Mineral 

deposits of southern Africa: Johannesburg, Geological Society of South Africa, p. 1725–1738. 

Rybakov, Michael, and Segev, Amit, 2004, Top of the crystalline basement in the Levant: G3-Geochemistry, Geophysics, 

Geosystems, v. 5, no. 9, 8 p. doi: 10.1029/2004GC000690.

Salisbury Resources, 2011, Cattle Grid—Copper—South Australia, ML 5599: Salisbury Resources Web Page, accessed 

July 16, 2011, at http://www.salisburyresources.com.

au/?page_id=117.

Sall, John, Creighton, Lee, and Lehman, Ann, 2007, JMP®

start statistics, a guide to statistics and data analysis using 

JMP®, Fourth Edition: Cary, North Carolina SAS Institute 

Inc., 607 p.

Schoenike, H.G., and Zeballos, R.A., 1976, The geology, 

exploration, and development of the stratiform copper 

deposit located northwest of Crowell, Texas, in Johnson, 

K.S., and Croy, R.L., eds., Stratiform copper deposits of the 

Midcontinent region, a symposium: Oklahoma Geological 

Survey Circular 77, p. 99. 

Scholtzhauer, S.D., 2007, Elementary statistics using JMP®: 

Cary, North Carolina, SAS Institute Inc., 458 p.

Schreiber, U.M., comp., 1980, Geological map of Namibia: 

Geological Survey of Namibia, scale 1:1,000,000.

Schuenemeyer, J.H., and Drew, L.J., 2011, Statistics for earth 

and environmental scientists: Hoboken, New Jersey, John 

Wiley & Sons, Inc., 407 p.

Schulz, K.J., and Briskey, J.A., 2003, The Global Mineral 

Resource Assessment Project: U.S. Geological Survey Fact 

Sheet 053-03, accessed February 2, 2011, at http://pubs.

usgs.gov/fs/fs053-03/.

Selley, David, 2000, Proterozoic sediment-hosted copper 

deposits—Geological framework and copper mineralization 

in South Australia: University of Tasmania, Centre for Ore 

Deposit Research, AMIRA/ARC Project P544, Meeting 

2, December 2000, 42 p., accessed July 16, 2011, at http://

www.codes.utas.edu.au/reports/AMIRA_Reports/P544/

P544_02_Dec_2000.pdf.

Selley, David, Broughton, David, Scott, Robert, Hitzman, 

Murray, Bull, S.W., Large, R.R., McGoldrick, P.J., Croaker, 

Mawson, Pollington, Nicky, and Barra, Fernando, 2005, 

A new look at the geology of the Zambian Copperbelt, in 

Hedenquist, J.W., Thompson, J.F.H., Goldfarb, R.J., and 

Richards, J.P., eds., Economic Geology—One hundredth 

anniversary volume 1905-2005: Society of Economic 

Geologists, Littleton, Colo., United States, p. 965–1000.

Servico Geológico Mexicano, 1997, Carta geologic-minera 

Santa Rosalía, Baja California Sur: Servico Geológico 

Mexicano Map G12-1, Secretaria de Economia, scale 

1:250,000. (Also available at http://mapserver.sgm.gob.mx/

cartas_impresas/productos/cartas/cartas250/geologia/

metadatos/santa_rosalia.html)

Sillitoe, R.H., Perelló, José, and García, Alfredo, 2010, 

Sulfide-bearing veinlets throughout the stratiform mineralization of the Central African Copperbelt—Temporal and 

genetic implications: Economic Geology, v. 105, no. 8, 

p. 1361–1368.

Simposya, V.M., and Hart, P.C.L, 2008, Technical report on 

the mineral resources for the Konkola North Copper project, 

Chililabombwe, Zambia: SRK Consulting Project Number 

384408, prepared for TEAL Exploration and Mining Co., 

March 2008, 78 p. (Also available at http://www.sedar.com.)

Simposya, V.M., Waldeck, H.G., Tagami, M., and McDonald, 

A.J., comps., 2008, The Shituru Copper Project feasibility 

study, Katanga Province, Democratic Republic of Congo: 
References Cited (Chapters 1, 2, and 3) 99

SRK Consulting Report no. 359212 (October 29, 2008), 

prepared for International Barytex Resources, Ltd., 125 p. 

(Also available at http://www.sedar.com.)

Sinclair, A.J., and Blackwell, G.H., 2006, Applied mineral 

inventory estimation: New York, Cambridge University 

Press, 381 p.

Singer, D.A., 1992, Grade and tonnage model of Sierran kuroko deposits, in Bliss, J.D., ed., Developments in 

mineral deposit modeling: U.S. Geological Survey Bulletin 

2004, p. 29–32.

Singer, D.A., 1993, Basic concepts in three-part quantitative 

assessments of undiscovered mineral resources: Natural 

Resources Research, v. 2, no. 2, p. 69–81.

Singer, D.A., 1995, World-class base and precious metal 

deposits—A quantitative analysis: Economic Geology, v. 

90, no. 1, p. 88–104.

Singer, D.A., 2011, A lognormal distribution of metal 

resources: Earth Science – Journal of China University of 

Geosciences, v. 36, no. 2, p. 1–8.

Singer, D.A., and Menzie, W.D., 2010, Quantitative mineral 

resource assessments—An integrated approach: New York, 

Oxford University Press, 219 p.

Singer, D.A., and Mosier, D.L., 1986, Grade and tonnage 

model of kuroko massive sulfide, in Cox, D.P., and Singer, 

D.A., eds., Mineral deposit models: U.S. Geological Survey 

Bulletin 1693, p. 190–197.

Singer, D.A., and Page, N.J, 1986, Grade and tonnage model 

of minor podiform chromite, in Cox, D.P., and Singer, D.A., 

eds., Mineral deposit models: U.S. Geological Survey Bulletin 1693, p. 34–38.

Singer, D.A., Berger, V.I., and Moring, B.C., 2008, Porphyry 

copper deposits of the world—Database, map, and grade 

and tonnage models, 2008: U.S. Geological Survey OpenFile Report 2008-1155, 45 p., accessed January 15, 2009, at 

http://pubs.usgs.gov/of/2008/1155/.

Singer, D.A., Berger, V.I., and Moring, B.C., 2009, Sedimenthosted zinc-lead deposits of the world—Database and grade 

and tonnage models: U.S. Geological Survey Open-File 

Report 2009-1252, accessed February 17, 2012, at http://

pubs.usgs.gov/of/2009/1252/.

Singer, D.A., Briskey, J.A., and Cunningham, C.G, 2008, 

Grade and tonnage model of giant porphyry copper deposits, in Cunningham, C.G., Zappettini, E.O., Vivallo S., 

Waldo, Celada, C.M., Quispe, Jorge, Singer, D.A., Briskey, 

J.A, Sutphin, D.M., Gajardo M., Mariano, Diaz, Alejandro, 

Portigliati, Carlos, Berger, V.I., Carrasco, Rodrigo, and 

Schulz, K.J., 2008, Quantitative mineral resource assessment of copper, molybdenum, gold, and silver in undiscovered porphyry copper deposits in the Andes Mountains of 

South America: U.S. Geological Survey Open File Report 

2008–1253, p. 64–67, accessed October 10, 2011, at http://

pubs.usgs.gov/of/2008/1253/. 

Singer, D.A., Page, N.J, and Lipin, B.R., 1986, Grade and tonnage model of major podiform chromite, in Cox, D.P., and 

Singer, D.A., eds., Mineral deposit models: U.S. Geological 

Survey Bulletin 1693, p. 38–44. 

Singewald, J.T., Jr., and Berry, E.W., 1922, The geology of the 

Corocoro copper district of Bolivia: Johns Hopkins University Studies in Geology, no. 1, 117 p.

Sneh, A., Bartov, Y., Weissbrod, T. and Rosensaft, M., 1998, 

Geological Map of Israel: Geological Survey of Israel, 4 

sheets, 1:200,000.

Soulé, J.H., 1956, Reconnaissance of the “red bed” copper 

deposits in southeastern Colorado and New Mexico: U.S. 

Bureau of Mines Information Circular 7740, 74 p.

SRK Consulting, 2006, Resource estimate Centennial Deposit, 

Lisbon Valley, Utah: SRK Consulting Project no. 162301 

(February 2006), prepared for Constellation Copper Corporation, 71 p., accessed September 5, 2011, at http://www.

pitecreative.com/staging/CCU/art/lisbon/LisbonValley.

ResourceEstimation.162301.LM.Final.pdf.

Stephens, A.J., and Newall, G.C., 2003, The Lonshi copper mine, Katanga Province, Democratic Republic of the 

Congo: First Quantum Minerals Ltd. Form 43-101F1 Technical Report, March 26, 2003, amending the January 30, 

2003 report, 35 p. (Also available at http://www.sedar.com.)

Sutton, S.J., and Maynard, J.B., 2005, A fluid mixing model 

for copper mineralization at Konkola North, Zambian Copperbelt: Journal of African Earth Sciences, v. 42, p. 95–118.

Sweeney, M., Turner, P., and Vaughan, D.J., 1986, Stable isotope and geochemical studies of the role of early diagenesis 

in ore formation, Konkola Basin, Zambia Copper Belt: 

Economic Geology, v. 81, p. 1838–1852.

Sweeney, M.A., and Binda, P.L., 1989, The role of diagenesis 

in the formation of the Konkola Cu-Co ore body of the 

Zambian Copperbelt, in Boyle, R.W., Brown, A.C., Jefferson, C.W., Jowett, E.C., and Kirkham, R.V., eds., Sedimenthosted stratiform copper deposits: Geological Association 

of Canada Special Paper 36, p. 499–518.

Sweeney, M.A., and Binda, P.L., 1994, Some constraints on 

the formation of the Zambian Copperbelt deposits: Journal 

of African Earth Sciences, v. 19, no. 4, p. 303–313.

Swenson, J.B., Person, M., Raffensperger, J.P., Cannon, W.F., 

Woodruff, L.G., and Berndt, M.E., 2004, A hydrogeologic 

model of stratiform copper mineralization in the Midcontinent Rift System, northern Michigan, USA: Geofluids, v. 4, 

p. 1–22.

Syusyura, B.B., 2008, Copper-bearing sandstones of Kazakhstan, in Ore Provinces of Central Asia, International Geo-
100 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

logical Congress – IGC-33 Reports of geologists of Central 

Asia countries: Ministry of Energy and Mineral Resources 

of Republic of Kazakhstan, Almaty, p. 1–13.

Syusyura, B.B., Glybovsky, V.O., and Kislitsin, A.V., 1986, 

Red-colored terrigenous sediments—Specific copperforming systems, in Friedrich, G.H., Genkin, A.D., Naldrett, A.J., Ridge, J.D., Sillitoe, R.H., and Vokes, F.M., 

eds., Geology and metallogeny of copper deposits: Berlin, 

Springer-Verlag, Proceedings 27th International Geological 

Congress, Moscow, 1984, p. 504–512.

Syusyura, Boris, and Tyugay, Oleg, 2008, Cupriferous 

sandstones of Kazakhstan: 33rd International Geological Congress, Olso, August 6-14th 2008, Abstract no. 

1342858, accessed April 27, 2012, at http://www.cprm.gov.

br/33IGC/1342858.html.

Taylor, H.K., 1972, General background theory of cutoff 

grades: Transactions of the Institute of Mining and Metallurgy, v. 81, section A, p. A160–A179.

Taylor, Roger, 2011, Gossans and leached cappings—Field 

assessment: Berlin Heidleberg, Springer-Verlag, 146 p.

Theys, L.F., and Lee, L.V., 1958, Sulfate roasting coppercobalt sulfide concentrates: Journal of Metals, February 

1958, p. 134–136.

Thieme, J.G., and Johnson, R.L., 1981, Geological map of the 

Republic of Zambia, second edition: Zambia Geological 

Survey, 1 map on 4 sheets, scale 1:1,000,000.

Thorson, J.P., 2004, Paradox basin sandstone-hosted copper 

deposits generated by two episodes of basinal fluid expulsion: Geological Society of America Abstracts with Programs, v. 36, no. 5, p. 517.

Thorson, J.P., 2005, Introduction and itinerary, in Thorson, J.P., 

and Presnell, Ricardo, eds., Lisbon Valley sediment-hosted 

copper deposits and Paradox basin fluids field trip: Society of 

Economic Geologists Guidebook Series, v. 37, p. 1–6.

Thorson, J.P., and MacIntyre, Timothy, 2005, Geology of the 

Cashin Mine sandstone-hosted disseminated copper deposit, 

Montrose County, Colorado, in Thorson, J.P., and Presnell, 

Ricardo, eds., Lisbon Valley sediment-hosted copper deposits and Paradox basin fluids field trip: Society of Economic 

Geologists Guidebook Series, v. 37, p. 43–49.

Timberline Resources, 2012, Other projects—Snowstorm, ID: 

Timberline Resources Corporation, accessed March 5, 2012, 

at http://mapserver.sgm.gob.mx/cartas_impresas/productos/

cartas/cartas250/geologia/metadatos/santa_rosalia.html.

Torrealday, H.I., Hitzman, M.W., Stein, H.J., Markeley, R.J., 

Armstrong, R., and Broughton, D., 2000, Re-Os and U-Pb 

dating of vein-hosted mineralization at the Kansanshi copper deposit, northern Zambia: Economic Geology, v. 95, p. 

1165–1170.

Trites, A.F., Jr., Chew, R.T., 3rd, and Lovering, T.G., 1959, 

Mineralogy of the uranium deposit at the Happy Jack mine, 

San Juan County, Utah, in Garrels, R.M., and Larsen, E.S., 

3rd, comps., Geochemistry and mineralogy of the Colorado 

Plateau uranium ores: United States Geological Survey 

Professional Paper 320, p. 185–195.

U.S. Department of State, 2009, Small-scale digital international land boundaries (SSIB)—Lines, edition 10: Boundaries and Sovereignty Encyclopedia (B.A.S.E.), U.S. Department of State, Office of the Geographer and Global Issues.

Unrug, R., 1989, Landsat-based structural map of the Lufilian fold belt and the Kundelungu aulacogen, Shaba (Zaire), 

Zambia, and Angola, and the regional position of Cu, Co, 

U, Au, Zn, and Pb mineralization, in Boyle, R.W., Brown, 

A.C., Jefferson, C.W., Jowett, E.C., and Kirkham, R.V., 

eds., Sediment-hosted stratiform copper deposits: Geological Association of Canada Special Paper 36, p. 519–524. 

Van Belle, Gerald, 2008, Statistical rules of thumb, second 

edition: Hoboken, New Jersey, John Wiley & Sons, Inc., 

272 p.

van Eden, J.G., 1974, Depositional and diagenetic environment related to sulfide mineralization, Mufulira, Zambia: 

Economic Geology, v. 69, p. 59–79.

Van Waggoner, J.C., Mitchum, R.M., Campion, K.M., and 

Rahmanian, V.D., 1990, Siliciclastic sequence stratigraphy 

in well logs, cores, and outcrops—Concepts for high-resolution correlation of time and facies: American Association 

of Petroleum Geologists Methods in Exploration Series, no. 

7, 55 p.

Vejbæk, O.V., and Britze, Peter, compilers, 1994, Top of the 

pre-Zechstein rocks—Structural depth map: Geological 

Survey of Denmark, Map Series no. 45, scale 1:750,000.

Veselinovic-Williams, M., and Frost-Killian, S., 2003 [2007], 

Digital international metallogenic map of Africa: Council 

for Geoscience, South Africa and Commission for the Geologic Map of the World, scale 1:5,000,000, CD-ROM.

Volodin, R.N., Chechetkin, V.S., Bogdanov, Yu, V., Narkelyun, 

L.F., and Trubachev, A.I., 1994, The Udokan cupriferous sandstones deposit (Eastern Siberia): Geology of Ore 

Deposits, v. 36, no. 1, p. 1–25.

Wagner, T., and Lorenz, J., 2002, Mineralogy of the complex 

Co-Ni-Bi vein mineralization, Bieber deposit, Spessart, 

Germany: Mineralogical Magazine, v. 66, no. 3, p. 385–407.

Warren, J.K., 2000, Evaporites, brines, and base metals—

Low temperature ore emplacement controlled by evaporite 

diagenesis: Australian Journal of Earth Sciences, v. 47, p. 

179–208.
References Cited (Chapters 1, 2, and 3) 101

Wedepohl, K.H., 1964, Untersuchungen am Kupferschiefer in 

Nordwestdeutschland—Ein beitrag zur deutung der genese 

bituminöser sedimente [Studies on copper shale in northwestern Germany—A contribution to the significance of the 

genesis of bituminous sediments]: Geochimica et Cosmochimica Acta, v. 28, p. 305–364.

Weed, W.H., 1907, The copper mines of the world: New York 

and London, Hill Publishing Company, 375 p.

Weisgerber, Gerd, 2006, The mineral wealth of ancient Arabia 

and its use, I—Copper mining and smelting at Feinan and 

Timna—Comparison and evaluation of techniques, production, and strategies: Arabian Archaeology and Epigraphy, v. 

17, p. 1–30.

Wengen, Chen, and Bin, Xia, 2005, Diagenetic origin of the 

Luzhou copper deposit, Yunnan Province, China, in Mao, 

Jingwen, and Bierlein, F.P., eds., Mineral Deposit Research—

Meeting the global challenge: Berlin, Springer, p. 91–92.

White, W.S., 1968, The native copper deposits of northern 

Michigan, in Ridge, J.D., ed., Ore deposits of the United 

States, 1933-1967, the Graton-Sales Volume: New York, 

American Institute of Mining, Metallurgical, and Petroleum 

Engineers, p. 303–325.

White, W.S., 1971, A paleohydrologic model for mineralization of the White Pine copper deposit, northern Michigan: 

Economic Geology, v. 66, p. 1–13.

Wilbrand, J.T., 1978, The copper resources of northern Michigan: Final report for U.S. Bureau of Mines, Contract No. 

J0366067, 21 p., accessed April 23, 2012, at http://www.

michigan.gov/documents/deq/GIMDLUSBMOFR1978_302972_7.pdf.

Wilson, J.T., 1966, Did the Atlantic close and then re-open?: 

Nature, v. 211, p. 676–681. 

Wodzicki, A., and Piestrzyński, A., 1994, An ore genetic 

model for the Lubin-Sieroszowice mining district, Poland: 

Mineralium Deposita, v. 29, p. 30–43.

Woodward, L.A., Kaufman, W.H., Schumacher, O.L., and 

Talbott, L.W., 1974, Strata-bound copper deposits in Triassic sandstone of Sierra Nacimiento, New Mexico: Economic 

Geology, v. 69, p. 108–120.

Yamana Resources Inc., 1997, Annual report 1997: Yamana 

Resources Inc. Annual Report, 52 p. (Also available at 

http://www.sedar.com.)

Yan, Guangsheng, Qiu, Ruizhao, Lian, Changyun, Li, Jinyi, 

Xiao, Keyan, and Mao, Jingwen, 2010, [Quantitative assessment on the resource potential of porphyry and sedimenthosted copper deposits in China]: Beijing, Geological 

Publishing House, 218 p. [In Chinese.]

Yikang, Liu, 2002, Geological overview and mining districts 

of China: PDAC meeting presentation, March 12, 2002, 59 

p., accessed January 3, 2011, at http://www.gl.ntu.edu.tw/

joomla/images/Yikang%201995%20Ore%20deposits%20

in%20China.pdf.

Yi-Ming, Zhao, and Wu, Liangshi, 2006, [China’s copper 

mineral resource map]: China Geological Publishing House, 

scale 1:5,000,000. [In Chinese.]

Zhuang, Hanping, Ran, Chongying, He Mingqin, and Lu, 

Jialan, 1996, Interactions of copper, evaporite, and organic 

matter and genesis of sandstone-hosted copper deposits 

in the Chuxiong Basin, Yunnan province: Acta Geologica 

Sinica, v. 9, p. 407–419.

Zimbabwe Geological Survey, 1985, Provisional geological 

map of Zimbabwe, seventh edition: Zimbabwe Geological 

Survey, 1 sheet, scale 1:1,000,000.
102 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Appendixes A–B
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 103

Appendix A. Relational Database of Sediment-Hosted Copper 

Deposits, Resources, and Production in the Central African 

Copperbelt, Democratic Republic of the Congo and Zambia

By Anna B. Wilson, J. Douglas Causey, Paul D. Denning, Timothy S. Hayes, John D. Horton, Michael J. 

Kirschbaum, Heather L. Parks, Cliff D. Taylor, and Michael L. Zientek

Introduction

This appendix describes a Microsoft Access® database 

containing geologic, mineral resource, production, and other 

economic information for more than 100 sediment-hosted 

copper deposits in the Central African Copperbelt (CACB), 

in the Democratic Republic of the Congo (DRC) and Zambia. 

Deposit types represented include stratabound as well as structurally controlled replacement and vein deposits. The database was designed to be used to estimate the in-situ mineral 

endowment and to create tonnage and grade models for use in 

mineral resource assessment studies. In addition, the database 

needed to be interactive as it would be queried to calculate the 

total tonnage and weighted average copper and cobalt grades 

for each deposit and deposit group. Mineral resource estimates 

and mineral production information are recorded for each site, 

along with information such as the site name, location, and 

a geologic categorization of the mineralization according to 

mineral deposit type, and references. This appendix summarizes the database design, describes the information content, 

and provides some guidance on how to use the database. 

Instructions for use of the database, especially understanding the use of queries, revising, or adapting the data, assume 

the user has a solid working knowledge how to use Microsoft 

Access® and a reasonable understanding of SQL (Structured 

Query Language) tools.

The database extends and revises the earlier work 

of other economic geologists who have summarized the 

geology and mineral resource endowment of the CACB 

(Kirkham and others, 1994; Cox and others, 2003, revised 

2007; Kirkham and Broughton, 2005). This study benefited 

from new exploration activity in the region, enhanced reporting requirements for publicly traded mineral exploration 

companies, the ability to search for and find information 

using the Internet, the use of GIS technology to understand 

the spatial context of the data, and access to publicly available high-resolution satellite imagery. 

Data are available from both public and private sources, 

but we are constrained to using only publicly available data. 

And although this compilation is based on data in the public domain, we did review information that we could not 

include in the database. Compilations created by colleagues 

in the mining industry for their clients were extraordinarily 

helpful. We also reviewed licensed or copyrighted information 

available from other scientific organizations and commercial 

vendors. Their work directed us to primary data sources and 

gave us a basis on which to evaluate the outcome of our work. 

Grade and tonnage estimates computed from this database 

(table A1) are reasonably close to some of the confidential 

summaries shared by colleagues in the mining industry and to 

those available through commercial databases.

The Database Design section describes the database 

tables, queries, forms, and their relationships. The Users’ 

Guide section describes how to open and use the database. 

The FAQ section poses what we anticipate might be frequently 

asked questions and answers them. The database, sir2010-

5090j_DB.zip, is available on the Internet at http://pubs.usgs.

gov/sir/2010/5090/j/.

Data Discussion and Methodology

The relational database, CACB_sedCu_deposits.mdb, 

accompanying this report was created in Microsoft Access®

(version 2003).1 Figures in this report were produced in version 2010. The database describes copper deposits (including 

mines, properties, or projects) in the CACB and provides 

production information, resource estimates, total endowment, 

and references cited. Mineral exploration and production 

rights in the CACB are associated with tracts of land that were 

originally subdivided based on social criteria, not geology; the 

names of these tracts (properties) and the exploration activities 

on them (projects) are recorded if they differ from the deposit 

name. To the extent possible, the information was recorded 

so that each site represents a single style of mineralization 

(deposit type). The record describes the relation of the deposit 

to mines and properties/projects. In some cases, a deposit is 

large enough so that it is, or was, developed by more than one 

mine, in which case data from multiple mines are aggregated 

and reported as representing a single deposit. Conversely, a 

mine may develop more than one deposit, in which case the 

values are reported for the individual deposits, not the mine.

Multiple values for production and estimated resources 

may have been reported, therefore a database record may have 

 1The database has not been fully tested with older or newer versions of 

Microsoft Access®.
104 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table A1. Summary of grade, tonnage, and total endowment (pre−mining) of the sediment−hosted copper deposits of the Central African 

Copperbelt (CACB).

[DepID, deposit identifier from relational database CACB_SedCu_deposits.mdb; DRC, Democratic Republic of the Congo; −, no data or not applicable.]

Deposit 

ID

Name Latitude Longitude Country Ore, 

metric tons

Copper 

grade, 

percent

Cobalt 

grade, 

percent

Contained 

copper, 

metric tons

Contained 

cobalt, 

metric tons

Sediment-hosted stratabound copper, reduced-facies—carbonate écaille

45 Bangwe −10.7289 26.3839 DRC 240,000 4.30 – 10,320 –

110 Dilala East −10.695 25.47 DRC 19,100,000 2.92 0.87 557,600 165,780

59 DIMA −10.7423 25.3785 DRC 280,473,964 2.79 0.19 7,811,973 531,328

44 Disele/Dankeru −10.7525 26.2544 DRC 4,052,000 2.69 0.07 109,125 2,738

31 Etoile −11.6354 27.5841 DRC 29,697,862 4.32 0.31 1,283,532 92,597

111 Etoile Extension −11.6301 27.5597 DRC 3,126,357 0.30 0.61 9,379 19,071

19 Fungurume −10.6153 26.2966 DRC 64,330,000 4.33 0.36 2,784,075 233,076

54 Fwalu −10.5807 26.155 DRC 40,265,000 2.46 0.17 990,359 69,480

43 Kababankola −10.7333 26.4227 DRC 1,887,000 1.62 1.12 30,569 21,134

22 Kabolela North and 

South

−10.8463 26.4788 DRC 11,699,762 2.31 0.50 270,656 58,568

41 Kakanda East −10.7365 26.4059 DRC 166,000 4.03 0.46 6,690 764

40 Kakanda North −10.7316 26.4021 DRC 23,287,000 2.62 0.17 610,119 39,588

42 Kakanda South −10.7388 26.3993 DRC 8,936,000 3.60 0.20 321,696 17,872

26 Kalongwe −11.0181 25.2219 DRC 3,000,000 5.00 – 150,000 –

37 Kalukundi −10.6352 25.9334 DRC 8,277,661 2.39 0.39 198,163 32,448

36 Kalukundi Anticline −10.6517 25.9271 DRC 4,685,813 2.42 0.57 113,375 26,851

35 Kalukundi Principal −10.6527 25.923 DRC 9,846,812 2.72 0.78 267,777 77,160

25 Kamatanda −10.951 26.7727 DRC 400,000 4.90 – 19,600 –

24 Kambove Principal −10.8863 26.6102 DRC 14,040,000 9.09 – 1,276,236 –

14 Kambove West −10.8862 26.5986 DRC 32,900,000 5.52 0.30 1,816,000 100,000

21 Kamfundwa −10.8137 26.5862 DRC 26,800,000 2.72 0.20 728,250 53,650

58 Kamoto Mine −10.7143 25.4009 DRC 139,376,734 4.48 0.35 6,238,825 493,127

127 Kamoya −10.878 26.5794 DRC 10,000,000 2.70 0.45 270,000 45,000

128 Kamwale −11.1431 27.1871 DRC 1,560,000 4.92 1.96 76,752 30,576

62 Kananga −10.6892 25.4588 DRC 8,100,000 1.80 0.88 146,010 71,590

56 Kansalawile −10.6202 26.2228 DRC 42,272,000 2.55 0.17 1,077,350 70,571

74 Karavia −11.6637 27.281 DRC 550,000 3.92 – 21,560 –

1 Karu East −11.6277 27.2764 DRC 5,500,000 1.80 – 99,000 –

72 Kasonta −11.5996 27.2749 DRC 1,500,000 5.18 – 77,700 –

6 Kasonta South −11.6101 27.2718 DRC 4,400,000 1.64 – 72,160 –

12 Kazibizi −10.8392 26.6004 DRC 1,000,000 3.20 0.60 32,000 6,000

38 Kii −10.6298 25.9349 DRC 4,492,295 2.49 0.58 112,021 26,008

27 Kimbwe −11.1454 27.4943 DRC 50,000,000 4.00 – 2,000,000 –

68 Kinsevere −11.3604 27.5733 DRC 50,215,648 4.09 0.00 2,053,315 426

32 Kipapila −12.0173 27.9023 DRC 2,600,000 4.40 0.54 114,400 14,040

70 Kipoi North −11.2448 27.092 DRC 5,274,000 1.36 0.05 71,726 2,637

47 Kiwana II −10.737 26.3055 DRC 82,000 2.70 0.35 2,214 287
 Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 105

7 Kolwezi −10.7259 25.4581 DRC 20,000,000 6.00 – 1,200,000 –

61 KOV −10.7134 25.4185 DRC 235,900,000 4.87 0.39 11,481,980 928,890

52 Kwatebala −10.5804 26.1899 DRC 114,741,000 1.95 0.36 2,234,970 415,895

48 Lufomboshi −10.7521 26.2381 DRC 225,000 1.98 0.06 4,455 135

28 Luishia −11.1668 27.0087 DRC 49,376,615 3.16 0.40 1,559,171 197,833

15 Luiswishi −11.5151 27.4391 DRC 8,000,000 2.50 1.10 200,000 88,000

49 Luita −10.7394 26.286 DRC 438,000 2.90 0.60 12,702 2,628

29 Lukuni −11.506 27.4207 DRC 2,700,000 4.30 – 116,100 –

30 Lupoto −11.5993 27.2631 DRC 37,152,000 2.63 – 976,320 –

113 Makala R2 −10.769 25.6685 DRC 1,211,695 2.81 0.27 33,993 3,240

57 Mambilima −10.62 26.2434 DRC 70,693,000 2.45 0.16 1,729,301 114,553

23 M’Sesa −10.8503 26.6099 DRC 8,000,000 5.90 0.21 472,000 17,000

39 Mukondo −10.7244 26.3487 DRC 36,255,529 2.00 1.40 725,111 507,577

9 Mupine −10.6979 25.404 DRC 10,000,000 2.50 – 250,000 –

60 Musonie T17 West −10.7135 25.4433 DRC 30,977,200 2.38 0.61 737,910 187,597

123 Mutanda Ya Mukonkota −10.7859 25.8134 DRC 299,600,000 1.23 0.59 3,673,910 1,761,040

20 Mutoshi −10.6817 25.5386 DRC 10,765,000 4.20 0.30 451,770 32,731

124 Mutoshi (breche) −10.6816 25.5384 DRC 45,460,000 1.75 – 793,609 –

8 Mutoshi Northwest −10.6726 25.5174 DRC 10,000,000 4.00 – 400,000 –

55 Mwandinkomba −10.5963 26.2049 DRC 35,430,000 3.16 0.14 1,120,315 48,789

73 Niamumenda −11.6024 27.2922 DRC 2,600,000 2.25 2.31 58,500 60,000

46 Nundo −10.7053 26.359 DRC 66,000 0.78 1.00 515 660

64 Ruashi −11.619 27.5444 DRC 45,843,595 2.81 0.25 1,286,500 112,690

50 Saafi −10.7401 26.4204 DRC 181,000 2.70 0.30 4,887 543

131 Shamitumba −10.958 26.6083 DRC 175,000 3.30 0.70 5,775 1,225

13 Shangolowe −10.7949 26.5684 DRC 25,000 8.00 – 2,000 –

115 Shinkolobwe Signal −11.0494 26.5706 DRC 125,200 3.17 1.70 3,974 2,125

125 Shituru −11.0172 26.7709 DRC 7,860,000 4.39 0.07 344,983 5,328

51 Taratara −10.7245 26.3667 DRC 165,000 1.83 0.92 3,020 1,518

53 Tenke −10.6015 26.1372 DRC 122,251,000 2.06 0.28 2,517,634 337,463

Sediment-hosted stratabound copper, reduced-facies ore shale

99 Baluba −13.0597 28.3399 Zambia 91,800,000 2.41 0.14 2,213,230 128,120

87 Chambishi Main and 

West

−12.658 28.0426 Zambia 116,223,700 2.53 – 2,940,038 –

10 Chambishi Southeast −12.7 28.1061 Zambia 177,629,000 2.13 0.07 3,781,032 123,009

83 Chingola −12.5445 27.8255 Zambia 141,390,000 1.47 – 2,075,438 –

108 Fitwaola −12.4085 27.8806 Zambia 3,450,000 2.94 – 101,430 –

126 Ichimpe −12.7351 28.1493 Zambia 3,100,000 1.78 – 55,180 –

Deposit 

ID

Name Latitude Longitude Country Ore, 

metric tons

Copper 

grade, 

percent

Cobalt 

grade, 

percent

Contained 

copper, 

metric tons

Contained 

cobalt, 

metric tons

Sediment-hosted stratabound copper, reduced-facies—carbonate écaille

Table A1. Summary of grade, tonnage, and total endowment (pre-mining) of the sediment-hosted copper deposits of the Central African 

Copperbelt (CACB).—Continued

[DepID, deposit identifier from relational database CACB_SedCu_deposits.mdb; DRC, Democratic Republic of the Congo ; −, no data or not applicable.]
106 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Deposit 

ID

Name Latitude Longitude Country Ore, 

metric 

tons

Copper 

grade, 

percent

Cobalt 

grade, 

percent

Contained 

copper, 

metric tons

Contained 

cobalt, 

metric tons

Sediment-hosted stratabound copper, reduced-facies ore shale

79 Konkola −12.3449 27.7978 Zambia 662,874,267 3.03 – 20,078,663 –

101 Luanshya −13.1132 28.3735 Zambia 264,000,000 2.80 – 7,403,360 –

92 Mindola−Nkana N−S −12.8233 28.1908 Zambia 701,787,416 2.17 0.06 15,209,735 428,602

100 Muliashi −13.0802 28.3196 Zambia 48,970,000 1.42 0.06 695,374 27,913

33 Musoshi −12.2719 27.7362 DRC 111,900,000 2.11 – 2,361,090 –

84 Nchanga −12.5102 27.8539 Zambia 425,730,000 3.24 0.03 13,791,044 130,838

86 Pitanda −12.6539 27.9886 Zambia 15,000,000 1.70 255,000

Sediment-hosted stratabound copper, sandstone copper—Roan arenite

98 Bwana Mkubwa −13.0315 28.6923 Zambia 8,600,000 3.34 – 287,240 –

95 Chibuluma South −12.9125 28.0809 Zambia 7,365,766 3.70 – 272,321 –

94 Chibuluma−Chibuluma 

West

−12.8232 28.0933 Zambia 19,922,000 3.69 0.19 734,766 37,114

96 Chifupu −12.9307 28.0703 Zambia 1,936,000 3.05 – 59,048 –

88 Fitula −12.6599 27.8717 Zambia 4,500,000 5.00 – 225,000 –

90 Kasaria−Luansobe −12.4497 28.1386 Zambia 21,500,000 2.31 – 496,650 –

34 Kinsenda −12.2614 27.9655 DRC 35,000,000 5.50 – 1,925,000 –

65 Lubembe −12.3571 28.0949 DRC 47,500,000 2.20 – 1,045,000 –

85 Mimbula −12.6266 27.8611 Zambia 46,850,000 1.20 – 560,700 –

2 Mokambo North −12.4262 28.3221 Zambia 3,854,000 1.70 – 65,518 –

81 Mokambo Project −12.4674 28.373 Zambia 14,900,000 1.22 – 181,780 –

11 Mokambo South −12.4967 28.3898 Zambia 6,000,000 2.70 – 162,000 –

82 Mufulira −12.5198 28.2285 Zambia 332,586,652 2.66 – 8,860,079 –

106 Mutundu North −12.5845 28.3409 Zambia 4,300,000 1.44 – 61,920 –

91 Mwambashi B −12.7232 27.9687 Zambia 14,210,000 1.78 – 253,626 –

93 Mwerkera −12.7998 28.5007 Zambia 7,100,000 1.53 – 108,630 –

129 Ndola East −12.9012 28.6094 Zambia 40,000,000 0.76 – 304,000 –

80 Nsato −12.4849 28.188 Zambia 8,400,000 1.61 – 135,240 –

89 Pitanda South −12.6738 27.9612 Zambia 7,060,000 1.58 – 111,548 –

130 Sebembere −14.3479 28.3347 Zambia 5,700,000 1.90 – 108,300 –

Structurally controlled replacement and vein

18 Dikulushi −8.892 28.2743 DRC 3,114,104 4.45 – 138,591 –

67 Frontier −12.7278 28.4745 DRC 284,247,567 1.17 – 3,313,797 –

102 Kalengwa −13.4592 24.9989 Zambia 4,000,000 5.20 – 208,000 –

76 Kansanshi −12.0968 26.433 Zambia 412,472,600 1.16 – 4,767,305 –

71 Kileba −11.2859 27.1244 DRC 9,502,431 1.40 – 133,034 –

69 Kipoi Central −11.2551 27.0948 DRC 56,611,535 1.81 0.08 1,023,100 46,430

66 Lonshi −13.1771 28.9408 DRC 16,935,836 4.02 – 680,838

17 Nama A −12.2662 27.6015 Zambia 43,656,000 0.10 0.06 43,219 24,011

Table A1. Summary of grade, tonnage, and total endowment (pre-mining) of the sediment-hosted copper deposits of the Central African 

Copperbelt (CACB). —Continued

[DepID, deposit identifier from relational database CACB_SedCu_deposits.mdb; DRC, Democratic Republic of the Congo ; −, no data or not applicable.]
 Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 107

16 Nama C −12.1978 27.5155 Zambia 78,218,000 0.01 0.04 9,386 33,634

105 Nama D −12.1429 27.4913 Zambia 63,909,000 0.04 0.08 22,368 51,127

4 Safari North −8.3268 29.2374 DRC 1,965,000 2.79 – 54,738 –

5 Safari South −8.3309 29.238 DRC 392,000 1.80 – 7,056 –

109 Sase Central −11.4528 27.078 DRC 14,700,000 1.36 0.02 200,400 3,100

3 Shaba −8.3005 29.2354 DRC 6,014,000 3.38 203,192

63 Tilwezembe −10.7998 25.6921 DRC 23,351,600 1.83 0.64 426,757 148,724

Unclassified copper deposits

78 Chimiwungo −12.2776 25.8854 Zambia 760,900,000 0.64 0.01 4,858,530 68,833

97 Itawa −12.9617 28.668 Zambia 40,000,000 0.76 – 304,000 –

107 Kalumbila −12.2601 25.3186 Zambia 340,000,000 0.78 0.03 2,652,000 102,000

114 Kimwehulu −10.6637 25.589 DRC 3,463,848 0.86 – 29,789 –

75 Lubwe −12.179 25.9511 Zambia 70,000,000 0.80 – 560,000 –

112 Makala R4 −10.7746 25.672 DRC 17,251,408 0.30 0.33 51,117 56,386

77 Malundwe −12.2279 25.8119 Zambia 161,700,000 0.89 0.01 1,437,980 23,314

103 Mufumbwe −13.6799 24.7949 Zambia 5,200,000 2.30 – 119,600 –

104 Samba −12.735 27.8844 Zambia 14,000,000 1.10 – 154,000 –

Deposit 

ID

Name Latitude Longitude Country Ore, 

metric

 tons

Copper 

grade, 

percent

Cobalt 

grade, 

percent

Contained 

copper, 

metric tons

Contained 

cobalt, 

metric tons

Structurally controlled replacement and vein

Table A1. Summary of grade, tonnage, and total endowment (pre-mining) of the sediment-hosted copper deposits of the Central African 

Copperbelt (CACB). —Continued

[DepID, deposit identifier from relational database CACB_SedCu_deposits.mdb; DRC, Democratic Republic of the Congo ; −, no data or not applicable.]

more than one value for production and estimated resource. 

During the process of creating this database, we recorded all 

the production and resource estimates that were available for a 

property. Resource estimates are usually reported in different 

categories (for example, measured, indicated, demonstrated, 

inferred) based on the quality of information; this information 

was retained in the database. We reviewed all the information 

to determine which set of records would give us the best and 

most comprehensive estimate of pre-mining in-situ resources 

(resources and (or) reserves, plus production) for the deposit. 

The data recorded in the database is also available in the Excel 

spreadsheet, CACB_raw_data.xls; references for this information are included in the Excel file, CACB_database_references.

xls. Care was taken to (1) not count any values more than once 

(in the case of overlapping mine properties), (2) keep track of 

inclusive versus exclusive resources and reserves, and (3) not 

count production that was already accounted for in a previous 

in-ground resource estimate. For complex areas comprising 

multiple deposits, we were careful to keep track of individual 

ore bodies. Most data sources reported the tonnage and grade 

of mineralized rock; however, some reported contained metal 

and grade (from which total tonnage can be computed by dividing contained metal by grade). Only the records that allowed us 

to estimate total endowment are included in the database. 

Tonnage and grade information for deposits that are 

contiguous or whose outer limit of the resource estimate tract 

were within 500 meters (m) of each other were aggregated for 

the purposes of resource modeling. In a few cases, a company 

reported combined resources and production for multiple deposits; these aggregated records are categorized as deposit groups.

Total tonnage and weighted average copper and cobalt 

grades are calculated for each deposit and deposit group using 

custom queries. Simply put, grade multiplied by tonnage2

equals the amount of contained metal.3 If data for grade or tonnage are not provided, the amount of contained metal is used 

to calculate the missing data, provided either tonnage or grade 

is available. If neither of these values are present for copper, 

the value for acid soluble copper (ASCu) is multiplied by the 

ore tonnage. Use of ASCu values will result in underreporting 

the in-situ endowment because it does not consider the copper 

losses during processing. 

2

Divided by 100 to convert from weight percent.

3

Microsoft Access® calculates to a higher precision than is warranted by the 

data. We formatted the displays to show rounded numbers that may still be too 

precise, but are closer to the correct significant figures. 
108 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Where the calculation of cobalt grade for a deposit uses 

data records that both include and exclude values for cobalt, the 

metal tonnage calculation assumes the grade is zero for each 

record lacking a value for cobalt. In some cases, tonnage, grade, 

and contained cobalt are reported. In those cases, the contained 

metal is calculated using the tonnage and grade values. Out of 

64 records where this is true, 23 calculated values are either 

greater than or less than the reported tonnage by more than 1 

metric ton. The difference between calculated and reported 

amounts of cobalt metal range from 233 to 400 metric tons, 

except for one record in which the calculated amount of cobalt 

is 79,762 metric tons greater than the reported metal tonnage. 

This one large discrepancy may be due to several factors, 

including reporting true recovered metal or estimating possible 

loss from mining and milling. For most properties, we believe 

the reported cobalt grade is either lower than the true grade or 

not even mentioned. Total tonnage of metal is divided by the 

total tonnage of ore for each deposit and deposit grouping to 

calculate weighted average grades.4

Silver and gold, present in some of these deposits in 

small quantities, are not economically important commodities 

in most of the CACB deposits. The number of deposits for 

which silver and gold grades were reported is small (9 and 5, 

respectively), and the amounts of contained silver and gold 

in these deposits is minor. Thus, weighted average grades of 

silver and gold for those few deposits are not calculated.

Many mineralized surface exposures have historically 

been worked by individuals and small-scale mining operations 

(artisanal mining), by high-grading rich pockets of ore. Most 

of this production has gone unreported; however, the amount 

mined by this method is assumed to have been minimal.

Comparison of Total Endowment with 

Previously Published Values

The total pre-mining endowment of copper in the CACB 

was 166,000,000 metric tons5 which is a little more than 

three times the total production of 50,200,000 metric tons or 

47,800,000 metric tons reported by Freeman (1988) and Fortin 

(2006) (table A2). Considering only the known deposits, there 

is still more than twice as much copper in the ground as has 

ever been produced in the CACB. The total endowment of 

cobalt is 6,500,000 metric tons. 

For Zambia, Freeman (1988) reported total production 

of 29,200,000 metric tons copper. We report total production 

of 36,500,000 metric tons copper, which means 7.3 million 

metric tons was produced in the 23 years since Freeman’s estimate. Other reasons for discrepancies between our values and 

those previously published include: (1) our sources may have 

included or excluded production from parts of each property, 

and (2) production reported may actually contain information 

from several unrelated properties because some processing 

plants received ore from many mines, even some from the 

DRC. We strove to include only production information from 

the individual deposits, not from the total amount of ore put 

through processing plant. 

In the DRC, Gécamines (successor to Union Minière du 

Haut Katanga) controlled all mining until about 1995; thus 

we believe that data reported before that date are reasonably 

accurate. In 1995, the government monopoly was broken up 

and Gécamines retained only partial control, which is, in part, 

why there was a drastic decrease in reported production. Our 

database, on the other hand, reflects higher production in recent 

years, but is undoubtedly deficient with respect to production 

prior to 1994. 

Fortin (2006) reported cobalt production of about 

500,000 metric tons for the DRC, but we were unable to find 

reliable figures for cobalt production in Zambia. Our estimate 

for the total cobalt endowment (6.5 million metric tons) in the 

CACB includes 671,000 metric tons of cobalt already produced (of which 87 percent, or 5.66 million metric tons, came 

from the DRC).

Sources of Information

Data from both public and proprietary sources were 

reviewed; however, we compiled only publicly available 

data from about 130 information sources. We also examined 

several databases including, but not limited to, those compiled by Cox and others (2003, revised 2007), Kirkham and 

others (1994), and Kirkham and Broughton (2005), to help 

us identify the important sediment-hosted copper deposits in 

central Africa. Compilations created by our colleagues in the 

mining industry for their clients were extraordinarily helpful, 

but we do not report those values unless they are in the public 

domain. We also reviewed licensed or copyrighted information 

available from other scientific organizations and commercial 

vendors. All of these products directed us to primary data 

sources that could be cited.

Complete bibliographic citations for all the publicly 

available information used to compile the deposits and 

resources data are stored in a table that is related to both the 

deposit and resource tables (see Data Tables section). Relations are many-to-many, so junction tables were constructed to 

provide the necessary links between the deposit and resource 

tables and the references table.

Database Design

The relational database (CACB_sedCu_deposits.

mdb) contains three types (Data, Look-up, and Junction) of 

tables (12 of them in all, including one, internally generated, 

4

Multiplied by 100 to account for weight percent.

 5There are several kinds of “tons”, but this report only uses metric tons. 

Metric tons may also be denoted as tonnes and abbreviated as t. No other form 

of tons can be symbolized tonne or t.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 109

Table A2. Comparison of copper production and total copper endowment with 

previously reported values.

Location Data Source Time Period Copper (t)1

Production

Zambia Freeman (1988)2 To 1988 29,200,000

Zambia This report To 2009 36,500,000

DRC Gecamines (Fortin, 2006)3 1914–2006 18,600,000

DRC This report To 2009 13,700,000

Total endowment

Zambia This report To 2009 96,100,000

DRC This report To 2009 69,900,000

Total CACB This report To 2009 166,000,000

1

In metric tons.

2

 Production taken from Freeman, 1988, page 18.

3

 Production interpolated from bar graph and only includes production from

 Gecamines and its predecessor properties. 

“Switchboard Items,” that just holds information for the 

Switchboard6), seven forms, ten queries, and one macro (script 

or program) (table A3). Forms provide the user with a display 

for entering, editing, and viewing the information for each 

deposit. Queries are custom requests. The macro simply opens 

the switchboard form immediately after the splashscreen 

closes.

The table relationships are shown in figure A1. We recommend that users read about the tables to understand what 

data are included, even though most of the users’ interactions 

will be with the forms.

Some of the queries, described in the Queries section, are 

used to calculate tonnages and grades of the deposits. Other 

queries provide selections of related fields from multiple tables 

so they can be used on the forms. The forms, described in the 

Forms section, provide the user with reformatted views of the 

data, in many instances showing multiple tables in a single 

view. They are mainly used for data input, but also can be used 

to produce hard-copy printouts. The Switchboard form has 

three buttons that are used to perform automated actions.

Field names in the tables may be represented by aliases in 

the forms used to view that same data. Field names in tables and 

their corresponding alias used on a form are given in table A4. 

Tables

There are three types of tables: data tables, look-up 

tables, and junction tables (fig. A2). Data tables (1_Deposittbl, 

 6An Access form that facilitates navigation through the database.

2_Resourcestbl, and 3_Referencetbl) contain information 

acquired from a variety of publicly available sources and 

categorized for the purposes of determining copper and cobalt 

endowment of the sediment-hosted copper deposits in the 

CACB; the table name begins with a number followed by 

an underscore and ends with the suffix “tbl.” Look-up tables 

(table name ending with the suffix “_LU”) contain lists and 

descriptions of terms that are used to populate fields in the 

data tables. Junction tables (table name ending with the suffix “_MM”) are used to manage many-to-many relationships 

in order to create joins between data tables. The Switchboard 

Items table (Switchboard Items) is included among the data 

tables; it simply holds data for the Switchboard Manager. The 

tables and relationships between them are shown in figure A1.

Data Tables

1_Deposittbl Table

The mineral deposit data table, 1_Deposittbl table, contains basic information about each deposit. A brief description 

of each of the 15 fields is provided in table A5. 

GroupName identifies a collective name for one or more 

deposits that are not known to be contiguous, but are within 

500 m of another deposit of the same deposit type. Thus, a 

group may contain several deposits in close proximity. If there 

is only one such deposit, the group name is the same as the 

deposit name. Groups are used for grade and tonnage modeling of the different deposit types.

Property is a name for the property or project associated 

with the deposit(s). A property may contain multiple deposits, 

but each deposit will have its own DepID. For example, the 

Konkola/Mushoshi Property contains the Fitwaola, Konkola, 
110 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

File Name Description

Data tables

1_Deposittbl Deposit table, primary table

2_Resourcestbl Resource data

3_Referencetbl References

Look-up tables

DepositSubtype_LU List of deposit style names for use in Geology portion of 1_Mastertbl_frm

DepositType_LU Deposit type names

Province_LU State and Province names

ResourceCat_LU List of terms used in the Resource_cat field of the 2_Resourcestbl table

ResourceStd_LU List of mineral evaluation reporting code standards for use in the Resources_std field of the 2_

Resourcestbl table

SiteActivity_LU List of terms for SiteStatus field in 1_Mastertbl table

Junction tables

DepRef_MM Table provides one-to-many links between 1_Deposittbl and 3_Referencetbl

ResRef_MM Table provides one-to-many links between 2_Resourcestbl and 3_Referencetbl

Internally generated table

Switchboard Items

Forms

1_Deposittbl_frm CACB sediment-hosted copper master form. Use for editing and viewing all related data

2_Resourcestbl_frm Subform used on 1_Deposittbl_frm to display resources and related references

Deposit_WgtAvg_qry_subform Form that shows calculated tonnage and grade values. Form used as subform on 1_Deposittble_frm form

DepRef_MM_subform Subform uses DepRef_qry to show references related to deposit information on 1_Deposittbl_frm

ResRef_MM_subform Subform uses ResRef_qry to show references related to resource information on 2_Resourcestbl_

frm and 1_Deposittbl_frm

Splashscreen A form that opens with the database and shows the reference for this report and a disclaimer for 5 seconds

Switchboard Form that opens after the Splashscreen form closes with buttons for several actions

Queries

Deposit_SumGradexTons_qry Query uses the Group_tonsXgrade_qry to sum all the grades times tonnages for each deposit

Deposit_SumTons_qry Query uses the 1_Mastertbl and 2_Resourcestbl to sum the tonnages for all deposits

Deposit_TonsxGrade_qry Query uses 1_Mastertbl and 2_Resourcestbl to calculate the tonnage times grade for all deposits

Deposit_WgtAvg_qry Query calculates tonnage and weighted average copper and cobalt grades for all deposits

DepRef_qry Query used to join 1_Deposittbl to 3_Referencetbl

Group_SumGradexTons_qry Query uses the Group_tonsXgrade_qry to sum all the grades times tonnages for each group

Group_SumTons_qry Query uses the 1_Mastertbl and 2_Resourcestblto sum the tonnage for all deposit groups

Group_TonsxGrade_qry Query uses 1_Mastertbl and 2_Resourcestbl to calculate the tonnage times grade for all deposit groups

Group_WgtAvg_qry Query calculates tonnage and wighted average copper and cobalt grades for all deposit groups

ResRef_qry Query used to join 2_Resourcestbl to 3_Referencestbl

Table A3. List and description of files in the database.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 111

Table A4. Source tables, queries, and fields for data displayed on the forms, as well as any controls or type of data that should be entered. 

[Source Field is the name of the corresponding field in the table]

Form Field Name Source Table or Query Source Table Field Name Controls

1_Deposittbl_frm

Group Name 1_Deposittbl GroupName None—free form

DepID 1_Deposittbl DepID Manual entry is not allowed; value is 

automatically generated

MRDS 1_Deposittbl MRDS 8-digit integer from the Deposit ID field in the USGS 

NewMRDS1 database

Deposit Name 1_Deposittbl Name None—free form

Property 1_Deposittbl Property None—free form

Deposit_WgtAvg_qry_

subform Deposit_WgtAvg_qry Calculated field Manual entry is not allowed; value is calculated automatically by the query Deposit_WgtAvg_qry

Latitude 1_Deposittbl Latitude None—should be an integer between −90 and 90

Longitude 1_Deposittbl Longitude None—should be integer between 180 and 180

Country 1_Deposittbl Country Limited to countries listed in the look-up table Province_LU

Province 1_Deposittbl Province Limited to a province listed in the look-up table Province_LU 

Other names 1_Deposittbl Name_other None—free form

Includes 1_Deposittbl Includes None—free form

Site Activity 1_Deposittbl SiteActivity Limited to a term listed in the look-up table SiteActivity_LU

Production 1_Deposittbl Production Check box limits entry: box checked for yes, unchecked for no

Deposit Type 1_Deposittbl DepositType Limited to terms in the look-up table DepositType_LU

DepositSubtype 1_Deposittbl DepositSubtype Limited to terms in the look-up table DepositSubtype_LU

2_Resourcestbl_frm

ResID 2_Resourcestbl ResID Limited to a value in the fieldResID in the table 2_Resourcestbl

Subpart 2_Resourcestbl Subpart None—free form

Resource category 2_Resourcestbl ResourceCat Limited to term in the look-up table ResourceCat_LU

Resource standard 2_Resourcestbl ResourceStd Limited to term in the look-up tabl e ResourceStd_LU

Year(s) 2_Resourcestbl EstYear None—free form

ASCu grade 2_Resourcestbl ASCu_grade None—free form

Ag grade 2_Resourcestbl Ag_grade None—free form

ASCu amount 2_Resourcestbl ASCu_amt None—free form

Ag amount 2_Resourcestbl Ag_amt None—free form

Ore (mt) 2_Resourcestbl Ore_MT None—free form

Cu grade 2_Resourcestbl Cu_grade None—free form

Co grade 2_Resourcestbl Co_grade None—free form

Cu equivalent 2_Resourcestbl Cu_equiv None—free form

Au grade 2_Resourcestbl Au_grade None—free form

Cu amount 2_Resourcestbl Cu_amt None—free form

Co amount 2_Resourcestbl Co_amt None—free form

Cu_cutoff 2_Resourcestbl Cu_cutoff None—free form

Au amount 2_Resourcestbl Au_amt None—free form

Reference Page 2_Resourcestbl Reference None—free form

Deposit_WgtAvg_qry_subfrm

DepID Deposit_WgtAvg_qry DepID One-to-one link to 1_Deposittbl

Ore (mt) Deposit_WgtAvg_qry Ore (mt) Calculated field

Cu (%) Deposit_WgtAvg_qry Cu (%) Calculated field

Co (%) Deposit_WgtAvg_qry Co (%) Calculated field

DepRef_MM_Subform

RefNo 4_Referencetbl RefNo RefNo field from DepRef_qry

Deposit Reference 4_Referencetbl Reference None—free form

ResRef_MM_Subform

RefNo 4_Referencetbl RefNo RefNo field from ResRef_qry

Resources Reference 4_Referencetbl Reference None—free form

 1An abbreviated version of Mineral Resources Data System or MRDS (also known as NewMRDS) is available to the public on the 

Web at http://tin.er.usgs.gov/mrds/ or at http://mrdata.usgs.gov/.
112 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table A5. Design and table structure of mineral deposits data table, 1_Deposittbl.

Field Name Data Type Data Size Description

DepID Number Long Integer Primary key—Unique deposit identification number.

GroupName Text 50 Name assigned to one or more deposits that can be grouped because of distance rules.

Property Text 50 Name of property or lease.

Name Text 255 Name of deposit.

Name_other Text 255 Historical names or spelling variations used for deposit.

Includes Text 255 Names of properties or sites that are subsets of the property.

SiteActivity Text 50 Description of the exploration or operational activity at time of source publication 

(active, development, exploration, inactive, mined out, prospect, unknown, and 

no entry).

Country Text 50 Country name(s) where deposit is located.

Province Text 50 Province name where deposit is located.

Latitude Number Double Latitude of center of mine or ore body, in decimal degrees, WGS 84 datum.

Longitude Number Double Longitude of center of mine or ore body, in decimal degrees, WGS 84 datum.

DepositType Text 75 Deposit type/model associated with deposits in this database (list of values is 

provided in the look-up table DepositType_LU)).

DepositSubtype Text 50 Deposit subtype/model associated with deposits in this database (list of values is 

provided in the look-up table DepositSubtype_LU). 

MRDS Number Long Integer ID number of property in USGS MRDS database.

Production Boolean (Yes/No) N/A Yes, or check mark = this deposit has produced. No, or blank = no known production or only artisanal mining.

and Mushoshi deposits, each its own separate record. Mineral 

rights are leased according to previously established (usually 

surveyed) land parcels. Each parcel will have a formal legal 

description. However, it is common for companies to refer to 

these parcels as a property or project.

Name is a unique identifier for the deposit, a site with 

reported production, or an estimate of the tonnage and grade 

of mineralized rock.

Name_other and Includes contain other names by which 

the deposit may be known, or the deposit includes (especially 

useful for larger deposits that include multiple pits or workings which may be listed to eliminate any confusion over what 

is included in the definition of the deposit).

Latitude and Longitude coordinates of the approximate 

center of a mine or ore body were derived from publications 

and examination of Google Earth images in comparison with 

the GIS data (see appendix B). Some of the deposits have been 

mined and are visible on Google Earth or other satellite imagery. Some reports contained maps, which were georegistered 

to determine the locations, and in some instances a location 

was specified in another coordinate system or projection. All 

the data were converted to geographic coordinates, WGS 84 

datum.

DepositType and DepositSubtype (see table A3) use the 

same terms as the Type and Subtype fields of the Deposit and 

Prospects GIS database (see appendix B). MRDS contains the 

deposit’s identifier as used in the USGS global database of 

mines and prospects known as Mineral Resources Data System or MRDS.7

 Production contains a check box to indicate 

whether or not the deposit was mined and has known production. The box is checked to indicate that, yes, the deposit has 

been mined, and if there is known production those values are 

given in the resource table, 2_Resourcestbl. The box is not 

checked (empty) to indicate, no, the deposit is not known to 

have produced, or if mining was artisanal in nature, or if only 

small amounts of ore were removed for exploration purposes. 

This box is unchecked for about three quarters of the deposits because they are in the exploration stage and have never 

produced ore.

2_Resourcestbl Table

The mineral resources data table, 2_Resourcestbl table, 

contains published copper, cobalt, silver, and gold resource 

and production data for sediment-hosted copper deposits in the 

7

An abbreviated version of Mineral Resources Data System or MRDS 

(also known as NewMRDS) is available to the public on the web at http://tin.

er.usgs.gov/mrds/ or at http://mrdata.usgs.gov/.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 113

CACB. A brief description of each of the 20 fields is provided 

in table A6. All resource and production values are in metric 

tons (tonnes) for both raw ore and contained metal. Grades are 

either weight percent (base metals) or grams per metric ton 

(precious metals). In many cases, the resources were reported 

in million metric tons or thousand metric tons, so they were 

converted to metric tons to eliminate potential misinterpretation of the values by many orders of magnitude.

EstYear is the year(s) for which the resource or production was reported. Often a recent publication will cite an 

estimate made decades ago, thus the year of the reference is 

not always an accurate indication of when the estimate was 

really made.

Cu_cutoff contains values for copper cutoff grade, 

usually reported as an economic cutoff using metal prices at 

the time of disclosure. In the few instances where a list of 

resources at various cutoff grades was published for a deposit, 

we selected the cutoff that the company used for its computations and report discussions, even if a potentially larger tonnage at lower grade was also reported. Cutoff grade is subject 

to economic filters and may change with time. For example, a 

deposit for which grade and tonnage was calculated at a cutoff 

grade of 0.5 weight percent Cu at a time of low metal prices, 

might be given a lower cutoff grade if and when the price 

rises substantially. Cutoff grade may also vary as technology 

changes.

All the fields ending with “_amt” (for Cu, ASCu8

, Co, 

Ag, and Au) store data for the amount of contained metal in 

the ore (Ore _MT). Data were included only if reported in 

the source publication. It appeared that this was commonly 

computed in the source publication by multiplying the tons 

of ore times the grade (and dividing by 100 to account for 

the grade in percent). Numbers may, or may not be rounded, 

depending on how they were reported. In some cases, this is 

the reported recovery from processing the ore. In those cases, 

the ResourceCat field will be classified as production. Keep in 

mind that if the value reported is actual production, that would 

be the amount recovered and does not account for loss or 

waste in the recovery process, which can be significant. Acidsoluble copper-equivalent amounts (ASCu_amt), were only 

available for fewer than 10 percent of the deposits.

Subpart lists the specific subarea of the deposit for 

which values are reported for any resources or production. 

Some deposits contain or represent several different ore bodies; values for each ore body are reported individually.

3_Referencetbl Table

The reference data table, 3_Referencetbl, contains full 

citations of sources used for deposit, resource, and production 

information (table A7). Published (stable) sources are cited 

in full USGS bibliographic style. For unpublished (publicdomain) sources, we give as much information as possible so 

that the reader can locate the reference. 

Many of the sources were company Web sites (URL and 

date accessed are provided in the citation). By nature, Web 

sites may not be permanent. In fact, many have vanished 

in the short duration of this data compilation, which makes 

reconfirming some of the data difficult, if not impossible. This 

is especially true of Web sites for companies that have been 

bought, sold, merged, changed name, been acquired by other 

companies, or have failed and cease to exist. 

Look-up Tables

Look-up tables provide lists and descriptions of values 

(terms) used in the data tables; they maintain a one-to-many 

relationship with the data tables for fields of the same name. 

DepositType_LU table

The deposit-type look-up table, DepositType_LU (table 

A8), contains a list and description of terms in the DepositType field of the 1_Deposittbl data table. This table is related 

one-to-many to DepositType field in the 1-Deposittbl table 

(fig. A1). 

DepositSubtype_LU table

The deposit-subtype look-up table, DepositSubtype_LU 

(table A9), contains a list and description of terms in the 

DepositSubtype field of the 1_Deposittbl data table. This table 

is related one-to-many to DepositSubtype field in the 1_Deposittbl data table (fig. A1).

Province_LU table

The province and country look-up table, Province_LU 

(table A10), contains a list of provinces and the countries in 

which they occur. Although the DRC is in transition from 

11 provinces to 25 provinces, the new boundaries were not 

available, thus the look-up table only contains the 11 original 

provinces.

ResourceCat_LU table

The mineral resource categories look-up table ResourceCat_LU (table A11) contains a list and description of terms 

used by workers in the CACB to describe the level of knowledge of the resources and reserves. These terms are based 

on the standards accepted by most nations for reporting of 

resources and reserves (described in the next section, ResourcStd_LU table). 

ResourceStd_LU table

The resource standard look up table ResourceStd_LU 

(table A12) provides a list of acronyms for the organizations that defined the standard resources terms used in the 8

Acid soluble Cu
114 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

 Table A6. Design and table structure of mineral resources data table, 2_Resourcestbl. 

Field Name Data Type Data Size Description

ResID Number Long Integer Primary key1

 —a unique identification number resource record.

DepID Number Long Integer Foreign key2

 —Identification number in the 1_Deposittbl table for the deposit to which this 

resource relates.

EstYear Text 50 Year of resource estimation, year resource estimation was published, or year(s) of production.

Ore_MT Number Double Metric tons of resources or production (as ore, not metal).

Cu_grade Number Double Grade of copper, in weight percent.

ASCu_grade Number Double Grade of acid soluble copper, in weight percent.

ASCu_amt Number Double Metric tons of acid soluble copper.

Cu_amt Number Double Metric tons of contained copper metal.

Cu_equiv Number Double Copper equivalent, in weight percent.

Cu_cutoff Number Double Cutoff grade for copper used to make resource estimate, in weight percent.

Co_grade Number Double Grade of cobalt, in weight percent.

Co_amt Number Double Metric tons of contained cobalt metal.

Ag_grade Number Double Grade of silver, in parts per million (equals grams per ton).

Ag_amt Number Double Metric tons of contained silver.

Au_grade Number Double Grade of gold, in parts per million (equals grams per ton).

Au_amt Number Double Metric tons of contained gold.

ResourceCat Text 36 Type of reserve or resource classification.

ResourceStd Text 20 Standard used to define the resource classification from ResourceStd_LU look-up table.

Subpart Text 50 Sub-part of a deposit for which resources are reported.

RefPage Text 50 Page number in reference where resource data came from. Format is RefID (page no.).

 1The primary key is a field that contains a value (can be numeric, alphanumeric, or character) that is unique for each record or row in the table.

Table A7. Design and table structure of reference data table, 3_Referencetbl.

Field Name Data Type Data Size Description

RefNo Number Long Integer Primary key—A unique reference record identification number.

Reference Memo N/A Complete citation in USGS format.

2

Foreign key is a field containing a value or string that is used to establish relations among tables in a relational database.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 115

Table A8. Structure and content of deposit-type look-up table, DepositType LU table.

Field Name Data Type Data 

Size Description

DepositType Text 50 Primary Key—Deposit type name from pick-list. Same as Subtype field in GIS (see appendix B).

DepositTypeDesc Text 255 Description of the DepositType term.

Values for DepositType

Sediment-hosted stratabound copper deposit

Structurally controlled replacement and vein

Unclassified Cu

Unclassified Cu, supergene enrichment

Table A9. Structure and content of deposit-subtype look-up table, DepositSubtype_LU.

Field Name Data Type Data 

Size Description

DepositSubtype Text 50 Primary key – Deposit subtype name from pick-list. Corresponds to the “type” field in the GIS 

(see appendix B).

DepositSubtypeDesc Text 255 Description of the DepositSubtype term.

Values for DepositSubtype

Reduced-facies, carbonate écaille

Reduced-facies, ore shale

Sandstone, Roan arenite

ResourceStd field of the deposit data table 1_Deposittbl or in 

the Resource Standard box in the form 1_Deposittbl_frm. 

SiteActivity_LU table

The site activity look-up table, SiteActivity_LU (table 

A13), contains terms that are used to describe the current mining activity at the deposit site. 

Junction Tables

In a relational database, it is not possible to directly link 

tables that are related many-to-many and query them properly. 

Trying to do this will create a matrix of all possible combinations, which is not what we want to do. In essence, junction 

tables provide one-to-many links between tables. The deposits 

table has a one-to-many relation to the junction table and the 

reference table has a one-to-many relation to the junction 

table. Similar relationships are also established between the 

resources data table and the junction table and the reference 

data table and the junction table (fig. A1). Two junction tables 

were constructed to link data tables that have a many-to-many 

relationship. Foreign keys in the junction tables link to primary keys in the data tables.

DepReftbl_MM table

The deposit reference junction table, DepRef_MM (table 

A14), links the deposit and reference data tables 1_Deposittbl 

and 3_Referencetbl, respectively (fig. A1).

ResReftbl_MM table

The resource reference junction table, ResRef_MM 

(table A15), links the resource and reference data tables 2_

Resourcestbl and 3_Referencetbl, respectively (fig. A1).

Internally Generated Table for Switchboard

Microsoft Access® automatically generated an internal 

table, Switchboard Items (table A16), when the Switchboard 

form was created (see Forms section). It is used by the software to keep track of items used by the form and to invoke 

custom commands as requested by the user.

Queries

Queries serve two purposes in this database: (1) computation of the total endowment (tonnage, weighted average 
116 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table A10. Structure and content of the province and country look-up table, Province_LU.

Field Name Data Type Data 

Size Description

Province Text 50 Name of province from pick-list; field corresponds to Province field in 1_Deposittbl data table.

Country Text 50 Name of country in which the province occurs. Field corresponds to country field in 1_Deposittbl data 

table.

Values for Provinces

Bandundu Democratic Republic of the Congo

Bas-Congo Democratic Republic of the Congo

Équateur Democratic Republic of the Congo

Kasai-Occidental Democratic Republic of the Congo

Kasai-Oriental Democratic Republic of the Congo

Katanga Democratic Republic of the Congo

Kinshasa Democratic Republic of the Congo

Maniema Democratic Republic of the Congo

Nord-Kivu Democratic Republic of the Congo

Orientale Democratic Republic of the Congo

Sud-Kivu Democratic Republic of the Congo

Central Zambia

Copperbelt Zambia

Eastern Zambia

Luapula Zambia

Lusaka Zambia

Northern Zambia

North-Western Zambia

Southern Zambia

Western Zambia
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 117

Table A11. Structure, content, and description of terms in the mineral resource categories look-up table, ResourceCat_LU.

Field Name Data Type Data Size Description

ResourceCat Text 75 Primary key—Type of resource, reserve, or production.

ResourceCatDesc Memo N/A Description of the term in the ResourceCat field.

Values for Resource Category

Indicated SAMREC—An “Indicated Mineral Resource” is that part of a Mineral Resource for which tonnage, densities, shape, physical characteristics, grade, and mineral content can be estimated with a reasonable level 

of confidence. It is based on exploration, sampling, and testing information gathered through appropriate techniques from locations such as outcrops, trenches, pits, workings, and drill holes. The locations 

are too widely or inappropriately spaced to confirm geological and/or grade continuity but are spaced 

closely enough for continuity to be assumed.

Indicated +inferred This is the sum of the indicated and inferred resources.

Inferred SAMREC—An “Inferred Mineral Resource” is that part of a Mineral Resource for which tonnage, grade, 

and mineral content can be estimated with a low level of confidence. It is inferred from geological 

evidence and assumed but not verified geological and (or) grade continuity. It is based on information 

gathered through appropriate techniques from locations such as outcrops, trenches, pits, workings, and 

drill holes that may be limited or of uncertain quality and reliability.

Measured SAMREC—A “Measured Mineral Resource” is that part of a Mineral Resource for which tonnage, densities, shape, physical characteristics, grade, and mineral content can be estimated with a high level of 

confidence. It is based on detailed and reliable exploration, sampling, and testing information gathered 

through appropriate techniques from locations such as outcrops, trenches, pits, workings, and drill holes. 

The locations are spaced closely enough to confirm geological and grade continuity.

Measured+indicated This is the sum of the measured and indicated resources.

Measured+indicated+inferred This is the total mineral resources—the sum of the measured, indicated, and inferred resources.

Ore reserve Total reserves if terms proven or probable are not specified.

Other Category undefined (leave comment).

Probable SAMREC—A “Probable Mineral Reserve” is the economically mineable material derived from a Measured and (or) Indicated Mineral Resource. It is estimated with a lower level of confidence than a Proved 

Mineral Reserve. It is inclusive of diluting materials and allows for losses that may occur when the material is mined. Appropriate assessments, which may include feasibility studies, have been carried out, 

including consideration of, and modification by, realistically assumed mining, metallurgical, economic, 

marketing, legal, environmental, social, and governmental factors. These assessments demonstrate at the 

time of reporting that extraction is reasonably justified.

Production Production—for any year or years. Years may be added parenthetically.

Proved SAMREC—A “Proved Mineral Reserve” is the economically mineable material derived from a Measured 

Mineral Resource. It is estimated with a high level of confidence. It is inclusive of diluting materials and 

allows for losses that may occur when the material is mined. Appropriate assessments, which may include 

feasibility studies, have been carried out, including consideration of and modification by realistically assumed mining, metallurgical, economic, marketing, legal, environmental, social, and governmental factors. 

These assessments demonstrate at the time of reporting that extraction is reasonably justified.

Proved+Probable Also called a “mineral reserve,” this is the sum of the proved and probable reserves that meets one of the 

accepted country coding classifications.

Reserve Term generally refers to reserves numbers that predate or are not defined by existing resource codes.

Resource Resource is assumed to be some combination of measured, indicated, demonstrated, or inferred.

Total endowment Total endowment is the remaining reserve/resource plus historic production combined to estimate the 

original amount of mineral resources.
118 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table A12. Structure, content, and description of terms in the mineral resource standards look-up table, ResourceStd_LU.

Field Name Data 

Type

Data 

Size Description

ResourceStd Text 50 Primary key—Acronym for the code used in reporting mineral resources and reserves.

ResourceStdDesc Text 255 Full name of the ResourceStd code.

Values for ResourceStd

Acronym Description

CIM NI1

 43-101, Canadian Institute of Mining, Metallurgy, and Petroleum Standards and Guidelines for Valuation of Mineral 

Properties (CIM Standing committee on Reserve Definitions, 2005).

JORC Australasian Joint Ore Reserves Committee—Code for Reporting Mineral Resources and Ore Reserves (The Joint Ore 

Reserves Committee, 2004).

NA Not applicable, the data is production, not resources.

None No Standard.

SAMREC South African Mineral Resource Committee’s South African Code for the Reporting of Exploration Results, Mineral 

Resources and Mineral Reserves (The Southern African Institute of Mining and Metallurgy and Geological Society of 

South Africa, 2007).

Table A13. Structure, content, and description of terms in the site activity look-up table, SiteActivity_LU.

Field Name Data 

Type

Data 

Size Description

SiteActivity Text 50 Primary key—Term that describes the status mining activity at the site.

SiteActivityDesc Text 255 Definition of SiteActivity terms.

Values for SiteActivity Description

active The deposit is being mined at the time of information.

development The deposit is being prepared for mining. This is a transitory phase between exploration and active.

exploration Active exploration is being done. This may include geochemical sampling, geophysics, geologic mapping, 

and drilling.

inactive The deposit was being mined but has stopped before the deposit was mined out.

mined out The deposit is considered completely mined out (depleted).

prospect Minor exploration has occurred.

unknown Status of current activity at the deposit is uknown.

1

NI stands for National Instrument.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 119

Table A14. Structure and content of the deposit reference junction table, DepRef_MM.

Field Name Data Type Data Size Description

DepRefID AutoNumber Long Integer Primary key—Unique numeric identifier for associated (paired) foreign keys (DepIDFK 

and RefNoFk).

DepIDFK Number Long Integer Foreign key—Numeric identifier for each deposit; links to DepID, the primary key field in 

the deposit data table 1_Deposittbl.

RefNoFk Number Long Integer Foreign key—Numeric identifier for source reference; links to RefNo, the primary field in 

reference data table 3_Referencetbl.

Table 15. Structure and content of the resource reference junction table, ResRef_MM.

Field Name Data Type Data Size Description

ResRefID AutoNumber Long Integer Primary key—Unique numeric identifier for associated (paired) foreign keys (ResIDFK 

and RefNoFk).

ResIDFK Number Long Integer Foreign key—Numeric identifier for resources; links to ResID, the primary key field in 

the resources data table 2_Resourcestbl.

RefNoFK Number Long Integer Foreign key—Numeric identifier for source reference; links to RefNo, primary key field 

in reference data table 3_Referencetbl.

Figure A1. Relations among the 11 Access data tables. (Note that ∞, the symbol for infinity, represents “many” as in 

one-to-many or many-to-many.)
120 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Figure A2. List of tables in the database.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 121

 Table A16. Structure and content of the Switchboard Items table. 

 [Note that this table is not user generated and therefore may not be modified]

Field Name Data Type Data Size Description

SwitchboardID AutoNumber Long Integer Number is automatically generated by Access.

ItemNumber Number Integer Primary key—Row number for items on the Switchboard.

ItemText Text 255 Text of items on Switchboard form.

Command Number Integer Code that identifies one of the commands available.

Argument Text 255 Name of the form, report or switchboard to run.

grade, and copper and cobalt content) of the individual 

deposits and spatially related groups of deposits in the CACB 

(table A17) and (2) link 3_referencetbl records to 1_depositbl 

and 2_resourcestbl tables (DepRef_qry, ResRef_qry). The 

queries in this database were formed using SQL (Structured 

Query Language) tools in Microsoft Access®: the built-in GUI 

(Graphical User Interface) tools were sufficient to create all of 

the query designs.

The reason tonnages and grades for the deposits and 

deposit groups are calculated through a series of queries is that 

Access (database) does not have the same functions as Excel 

(spreadsheet). The @sumproduct and @sum functions that that 

are available in Excel and could be used to calculate weighted 

averages are not available in Access®. An alternative is to write 

code, but as new versions of software are released or upgraded, 

code can become obsolete. One of the easier ways to make 

computations in Access® is by using the built-in features to create a series of linked queries (table A17). 

In the case of the CACB data, there are resource records 

in which a total copper grade might not be given, but a tonnage of metal is known. In these cases, the query first checks 

for a grade (Cu_grade field) and uses it. If no grade is given, 

it selects the amount of metal (stored in Cu_amt field) and 

uses that value. If there is only an acid soluble copper grade 

(ASCu_grade field), then that value is used. Every resource 

record has at least one value in one of those three fields for 

copper. The order of selection of the field to use is controlled 

by our evaluation of which field has the most reliable value. 

Grades of total copper (Cu_grade) are always the preferred values. Values for cobalt are treated similarly except there is only 

either a grade (Co_grade field) or amount of metal (Co_amt 

field), but no acid-soluble equivalent. 

The coding used to do the complex selection of data and 

calculations for both the deposits and groups are the same and 

are shown below. The complete SQL coding can be viewed 

by examining the queries in the database using SQL View 

option when in Design View. Different outputs are due to the 

differences in selection of records to use. In the case of the 

deposits, the resources are calculated using information in 

the 2_Resourcestbl table that is related to the deposit names 

found in the field called Name in the 1_Deposittbl. For groups, 

resources are calculated on the group names found in the field 

called GroupName. Queries that contain the word “sum” use 

the simple Access sum function. 

The sections below briefly describe each query, provide 

the SQL code and portray the GUI interface (Design View). 

See the Users’ Guide section for how to invoke these queries.

Deposit_SumTons_qry Query

The query, Deposit_SumTons_qry (fig. A3), sums the 

resource and production tonnage records to produce a total 

tonnage for each deposit.

Deposit_TonsxGrade_qry Query

The query, Deposit_TonsxGrade_qry (fig. A4), calculates 

the product of tonnage times copper and cobalt grades for each 

resource record in the 2_Resourcestbl table. If no grade is 

given, the query checks to see if a value exists for the amount 

of copper and cobalt. If so, it uses that value. The result is 

divided by 100 to convert from percent. Output from this 

query is passed to the query Group_SumGradexTons_qry.

Deposit_SumGradexTons_qry Query

The query Deposit_SumGradexTons_qry (fig. A5) uses 

output from the Deposit_TonsxGrade_qry query to sum the 

tonnage of copper and cobalt in a deposit.

Deposit_WgtAvg_qry Query

The query, Deposit_WgtAvg_qry (fig. A6), calculates 

the weighted average copper and cobalt for each deposit. The 

query produces a list of deposit names with total tonnage, and 

average grade of copper and cobalt for each.

Queries and Calculations Performed on Groups 

of Deposits

Group_SumTons_qry Query

The query, Group_SumTons_qry (fig. A7), sums the 

resource and production tonnage records for each deposit 

group to produce a total tonnage for the deposit group.
122 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table A17. List of queries and brief description of output and use in other queries.

[NA, not applicable]

Query Output Query in which output is used 

Deposit_SumTons_qry Total tonnage of ore (in metric tons) for each deposit. Deposit_WgtAvg_qry

Deposit_TonsxGrade_qry Amount of metal in each resource or production record. Deposit_TonsxGrade_qry

Deposit_SumGradexTons_qry Total tonnage (in metric tons) of copper and cobalt 

metal, for each deposit.

Deposit_WgtAvg_qry

Deposit_WgtAvg_qr Total tonnage (in metric tons) and weighted average copper and cobalt grades (in percent), for each deposit.Query run from command button on Switchboard 

form “Run Deposit grade/ton Query” button.

Group_SumTons_qry Total tonnage of ore (in metric tons) for each deposit 

group.

Group_WgtAvg_qry

Group_TonsxGrade_qry Amount of metal in each resource or production record. Group_SumGradexTons_qry

Group_SumGradexTons_qry Total tonnage (in metric tons) of copper and cobalt 

metal, for each deposit group.

Group_WgtAvg_qry

Group_WgtAvg_qry Total tonnage (in metric tons) and weighted average 

copper and cobalt grades (in percent), for each 

deposit group.

Query run from command button on Switchboard 

form “Run Group/Deposit grade/ton Query” 

button.

DepRef_qry Used to link RefID from 3_Referencetbl table with 

1_Deposittbl table.

NA

ResRef_qry Used to link RefID from 3_Referencetbl table with 

2_Resourcestbl table.

NA
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 123

SQL code:

SELECT [2_Resourcestbl].DepID, [1_Deposittbl].Name, [1_Deposittbl].DepositType, [1_Deposittbl].DepositSubtype, 

Sum([2_Resourcestbl].Ore_MT) AS SumOfOre_MT, [1_Deposittbl].Latitude, [1_Deposittbl].Longitude

FROM 1_Deposittbl INNER JOIN 2_Resourcestbl ON [1_Deposittbl].DepID=[2_Resourcestbl].DepID

GROUP BY [2_Resourcestbl].DepID, [1_Deposittbl].Name, [1_Deposittbl].DepositType, [1_Deposittbl].DepositSubtype, 

[1_Deposittbl].Latitude, [1_Deposittbl].Longitude;

Figure A3. Deposit_SumTons_qry query design view and Structured Query Language (SQL).
124 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

SQL code:

SELECT [1_Deposittbl].DepID, [2_Resourcestbl].Ore_MT, IIf([Cu_Grade]>0,[Cu_Grade]/100*[Ore_MT],IIf([Cu_amt]>0,[Cu_

amt],[ASCu_grade]/100*[Ore_MT]))

AS Cuxtons, IIf([Co_Grade]>0,[Co_Grade]/100*[Ore_MT],[Co_amt]) AS Coxtons

FROM 1_Deposittbl INNER JOIN 2_Resourcestbl ON [1_Deposittbl].DepID = [2_Resourcestbl].DepID;

Figure A4. Deposit_TonsxGrade_qry query design view and Structured Query Language (SQL).
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 125

SQL code:

SELECT Deposit_tonsXgrade_qry.DepID, Sum(Deposit_tonsXgrade_qry.Cuxtons) AS SumOfCuxtons, Sum(Deposit_ 

 tonsXgrade_qry. Coxtons) AS SumOfCoxtons

FROM Deposit_tonsXgrade_qry

GROUP BY Deposit_tonsXgrade_qry.DepID;

Figure A5. Deposit_SumGradexTons_qry query design view and Structured Query Language (SQL).
SQL code: SELECT Deposit_sumTons_qry.DepID, Deposit_sumTons_qry.Name, Deposit_sumTons_qry.DepositType, Deposit_sumTons_qry.DepositS

sumTons_qry.SumOfOre_MT AS [Ore(tonnes)], 100*[SumOfCuxtons]/[SumofOre_MT] AS [Cu(pct)], 100*[SumOfCoxAS [Co(pct)], [SumOfOre_MT]*[SumOfCuxtons]/([SumofOre_MT]*100) AS [Cu(tonnes)], [SumOfOre_MT]*[SumOfCMT]*100) AS [Co(tonnes)], Deposit_sumTons_qry.Latitude, Deposit_sumTons_qry.Longitude FROM Deposit_sumGradexTons_qry INNER JOIN Deposit_sumTons_qry ON Deposit_sumGradexTons_qry.DepID = Deposit_sumTons_q

Figure A6. Deposit_WgtAvg_qry query design view and Structured Query Language (SQL).
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 127

SQL code:

SELECT [1_Deposittbl].GroupName, Sum([2_Resourcestbl].Ore_MT) AS SumOfOre_MT

FROM 1_Deposittbl INNER JOIN 2_Resourcestbl ON [1_Deposittbl].DepID = [2_Resourcestbl].DepID

GROUP BY [1_Deposittbl].GroupName;

Figure A7. Group_SumTons_qry query design view and Structured Query Language (SQL).
128 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Group_TonsxGrade_qry Query

The query, Group_TonsxGrade_qry (fig. A8), is used in 

the calculation of grades for each deposit group. It calculates 

the product of tonnage times copper and cobalt grades for 

each resource record in the 2_Resourcestbl table. If no grade 

is given, the query checks if a value exists for the amount of 

copper and cobalt and divides the result by 100. If no copper 

grade or amount is given, it uses the acid soluble copper grade 

to calculate the metal tonnage for each deposit group.

Group_SumGradexTons_qry Query

The query, Group_SumGradexTons_qry (fig. A9), uses 

output from the Group_TonsxGrade_qry query to add the tonnage of metals for a deposit group.

Group_WgtAvg_qry Query

The query, Group_WgtAvg_qry (fig. A10), calculates the 

weighted average copper and cobalt for each deposit group. 

The query produces a list of group names with total tonnage, 

and average grade of copper and cobalt for each group.

Queries Used to Provide Lists of References

DepRef_qry Query

The query, DepRef_qry (fig. A11), connects the deposit 

records to their source reference. It is used in the 1_Deposittbl_frm to display the deposit information and the associated 

references.

ResRef_qry Query

The query, ResRef_qry (fig. A12), is similar to the 

DepRef_qry, but it links the resource information to its source 

reference. The 2_Resourcestbl_frm form used the output of 

this query to display resource and references for each deposit.

Forms

Forms provide a means of identifying the database 

(Splashscreen), performing user-specified functions (Switchboard), incorporating data provided by the user simultaneously into multiple tables; and viewing snapshots of data by 

record. The names and brief descriptions of each form are 

given in table A18. Subforms and some forms are designed to 

be placed on other forms. 2_Resourcestbl_frm and forms with 

the suffix “subform” should not be opened independently and 

resized, or else they will not display properly on the 1_Depositstbl_frm form into which they were made to fit.

Database Identification

Splashscreen Form

The form, Splashscreen (fig. A13), displays briefly (5 

seconds) whenever the database is opened. Splashscreen 

provides the citation for the publication in which this database is included and a standard USGS disclaimer. To read 

the splashscreen for longer than 5 seconds (in Access version 

2003)9, go to Forms, highlight Splashscreen, right click, and 

select Design View.

Switchboard Form

Processing options are accessed through three selection 

buttons on the Switchboard form. (fig. A14) which opens 

immediately after the splashscreen. A description of each 

option is provided in table A19.

1_Deposittbl_frm Form

The form 1_Deposittbl_frm (fig. A15) is the primary data 

entry form. It contains 44 data entry boxes, some of which 

reference subforms to display related information from multiple 

tables. Titles for the data entry boxes correspond (from left to 

right in the form) to field names in the various data tables as 

given in table A4.

2_Resourcestbl_frm Form

The form 2_Resourcestbl_frm (fig. A16) can be used for 

data entry and for viewing resource and production information. It contains 19 data entry boxes and a subform titled 

Resources Reference. The main entry form, 1_Deposittbl_frm, 

uses the resources data entry form to display resources and 

(or) production associated with a single deposit. Do not 

attempt to resize the form 2_Resourcestbl_frm because it may 

not display properly on the form 1_Deposittbl_frm.

Deposit_WgtAvg_qry_subform Form

The form, Deposit_WgtAvg_qry_subform (fig. A17), is 

used to display deposit tonnage and grade values (outlined in 

pink) on the main data-entry form, 1_Deposittbl_frm. These 

values are generated by the query Deposit_WgtAvg_qry. Do 

not resize this form, or it will not display properly within the 

form 1_Deposittbl_frm.

9

In Access version 2010, go to View and select Design View.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 129

Table A18. Description of the forms in the Central African Copperbelt (CACB) database.

Form Name Form Description

Splashscreen Form displays the reference for this report and a disclaimer.

Switchboard From automatically opens after the Splashscreen fades and provides buttons for three custom actions.

1_Deposittbl_frm Master data entry form, used to edit and view all related data for a deposit. 

2_Resourcestbl_frm Subform used on 1_Deposittbl_frm to display resources and related references.

Deposit_WgtAvg_qry_frm Form that shows calculated tonnage and grade values. Form used as subform on 1_Deposittbl_frm form.

DepRef_MM_Subform Subform uses DepRef_qry to show references related to deposit information on 1_Deposittbl_frm.

ResRef_MM_Subform Subform uses ResRef_qry to show references related to resource information on 2_Resourcestbl_frm 

and 1_Deposittbl_frm.

Table A19. Description of operations that can be performed using the Switchboard form.

Button Name Description of Action performed

Open data entry form Immediately opens the 1_Deposittblfrm form.

Run deposit tonnage and 

grade query

Runs the Deposit_WgtAvg_qry query, which calculates the total tonnage and weighted average grade for 

individual deposits.

Run grouped deposits total 

endowment query

Runs the Group_WgtAvg_qry query, which calculates the total tonnage and weighted average grade for 

defined groups of deposits that meet the distance rules for the associated deposit model.

Source Reference Forms

DepRef_MM_Subform Form and ResRef_MM_

Subform form

The deposit references form, DepRef_MM_Subform 

(fig. A18), displays reference(s) that are sources of information about the deposit, whereas the resource references form 

ResRef_MM_Subform (fig. A19) displays reference(s) that 

are sources of resource information for the deposit. The data 

appear as subforms (outlined in light blue) on the forms 

1_Deposittbl_frm or 2_Resourcestbl_frm, respectively. Do not 

attempt to resize either reference form or they may not display 

properly within the deposit or resource forms.

Macros

Access uses macros to automatically perform functions. 

The simple macro, Macro1 (fig. A20), automatically opens the 

switchboard form immediately after the splashscreen closes.

Users’ Guide

How to use the Access Database

The database property attribute is set to “read-only”. To make 

any modifications to data or database design, the file property must 

be changed in Windows. We recommend that you make a copy of 

the database, save it with a new name (something like CentralAfricaSedCu_EDITED.mdb or CACBSedCu_REVISED.

mdb), and change the property so it is no longer read-only. (After 

copying the file, highlight the copy in Windows Explorer, right 

click, select Properties, and click on the “Read-only” box to 

unselect.) Your copy is now ready for editing.

The following sections will walk you through opening, browsing, and computing resource endowments in the 

database. In anticipation of commonly asked questions, we 

have also provided a section for what we anticipate might be 

the most frequently asked questions (FAQ) 

Open Access Database 

Open the backup or duplicated file. Do not open the 

original file unless you have confirmed that it is “read only”. 

(You may be asked “Do you want to block unsafe expressions?” if the Tools/Macro/Security is not set to “Low.” 

Answer “No” or parts of the database will not work. This 

may be followed by “Do you want to open this file or cancel 

the operation?” Click “Open.”)10

The splashscreen (fig. A13) will appear (and close after 

5 seconds) followed by the startup, or switchboard, form 

with 3 action buttons (fig. A14).

10Alternatively, there may be a yellow security warning bar at the top of the 

page. Click on “Enable Content” to continue.
130 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

SQL code:

SELECT [1_Deposittbl].GroupName, [2_Resourcestbl].Ore_MT, IIf([Cu_Grade]>0,[Cu_Grade]/100*[Ore_MT],IIf([Cu_

amt]>0,[Cu_amt],[ASCu_grade]/100*[Ore_MT])) AS Cuxtons, IIf([Co_Grade]>0,[Co_Grade]/100*[Ore_

MT],[Co_amt]) AS Coxtons

FROM 1_Deposittbl INNER JOIN 2_Resourcestbl ON [1_Deposittbl].DepID = [2_Resourcestbl].DepID

ORDER BY [1_Deposittbl].GroupName;

Figure A8. Group_TonsxGrade_qry query design view and Structured Query Language (SQL).
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 131

SQL code:

SELECT Group_tonsXgrade_qry.GroupName, Sum(Group_tonsXgrade_qry.Cuxtons) AS SumOfCuxtons, Sum(Group_

tonsXgrade_qry.Coxtons) AS SumOfCoxtons

FROM Group_tonsXgrade_qry

GROUP BY Group_tonsXgrade_qry.GroupName;

Figure A9. Group_SumGradexTons_qry query design view and Structured Query Language (SQL).
SQL code: SELECT [1_Deposittbl].GroupName, [1_Deposittbl].DepositType, [1_Deposittbl].DepositSubtype, Group_sumTons_ qry.SumOfOre_MT AS [Ore(tonnes)], 100*[SumOfCuxtons]/[SumofOre_MT] AS [Cu(pct)], 100*[SumOfCoxtons]/[SumofOre_MT] AS [Co(pct)], [SumOfOre_MT]*[SumOfCuxtons]/([SumofOre_ MT]*100) AS [Cu(tonnes)], [SumOfOre_MT]*[SumOfCoxtons]/([SumofOre_MT]*100) AS [Co(tonnes)] FROM (1_Deposittbl INNER JOIN Group_sumTons_qry ON [1_Deposittbl].GroupName = Group_sumTons_qry.GroupName) INNER JOIN Group_sumGradexTons_qry ON [1_Deposittbl].GroupName = Group_sumGradexTons_qry. GroupName GROUP BY [1_Deposittbl].GroupName, [1_Deposittbl].DepositType, [1_Deposittbl].DepositSubtype, Group_sumTons_qry. SumOfOre_MT, 100*[SumOfCuxtons]/[SumofOre_MT], 100*[SumOfCoxtons]/[SumofOre_MT], [SumOfOre_MT]*[SumOfCuxtons]/([SumofOre_MT]*100), [SumOfOre_MT]*[SumOfCoxtons]/ ([SumofOre_MT]*100) ORDER BY [1_Deposittbl].GroupName; Figure A10. Group_WgtAvg_qry query design view and Structured Query Language (SQL).
SQL code: SELECT [1_Deposittbl].DepID, [1_Deposittbl].GroupName, [1_Deposittbl].Property, [1_Deposittbl].Name, [1_Deposittbl].Name_other, [1

[1_Deposittbl].SiteActivity, [1_Deposittbl].Country, [1_Deposittbl].Province, [1_Deposittbl].Latitude, [1_Deposittbl].LDepositType, [1_Deposittbl].DepositSubtype, [1_Deposittbl].MRDS, [1_Deposittbl].Production, DepRef_MM.DepIDFMM.RefNoFk, [3_Referencetbl].Reference, [3_Referencetbl].RefNo FROM 3_Referencetbl INNER JOIN (1_Deposittbl INNER JOIN DepRef_MM ON [1_Deposittbl].DepID = DepRef_MM.DepIDFK) ON DepRef_MM.RefNoFk; Figure A11. DepRef_qry query design view and Structured Query Language (SQL).
SQL code: SELECT [2_Resourcestbl].ResID, [2_Resourcestbl].DepID, [2_Resourcestbl].EstYear, [2_Resourcestbl].Ore_MT, [2_Resourcestbl].Cu_gr

ASCu_grade, [2_Resourcestbl].ASCu_amt, [2_Resourcestbl].Cu_amt, [2_Resourcestbl].Cu_equiv, [2_Resourcestbl].Cu

Resourcestbl].Co_grade, [2_Resourcestbl].Co_amt, [2_Resourcestbl].Ag_grade, [2_Resourcestbl].Ag_amt, [2_Resourc[2_Resourcestbl].Au_amt, [2_Resourcestbl].ResourceCat, [2_Resourcestbl].ResourceStd, [2_Resourcestbl].Subpart, [2ResRef_MM.ResIDFK, ResRef_MM.RefNoFK, [3_Referencetbl].Reference, [3_Referencetbl].RefNo FROM 3_Referencetbl INNER JOIN (2_Resourcestbl INNER JOIN ResRef_MM ON [2_Resourcestbl].ResID = ResRef_MM.ResIDFK) ORefNo = ResRef_MM.RefNoFK; Figure A12. ResRef_qry query design view and Structured Query Language (SQL).
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 135

Figure A13. View of the splashscreen form.

Figure A14. View of the switchboard form showing data entry and query options. 
136 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Figure A15. Form view of the deposit data-entry form for the Konkola deposit, DepID = 79.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 137

Figure A16. View of the resource data-entry form 2_Resourcestbl_frm for ResID = 1.

Figure A17. View of the deposit tonnage and grade form, Deposit_WgtAvg_qry_subform.

Figure A18. View of the deposit references form DepRef_MM_Subform.
138 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Figure A19. View of the resources references form ResRef_MM_Subform.

Figure A20. Design View of the macro Macro1.

Browse Database 

Select the “Open Data Entry Form” button on the switchboard to browse the database. This opens the master data entry 

form, 1_Deposit_frm (fig. A21).

The deposits form 1_Deposittbl_frm displays data that 

are stored in the three main data entry tables (1_Deposittbl, 

2_Resourcestbl, and 3_Referencetbl).

There are two main areas on the deposits form (1_deposittbl_frm) (fig. A21). The upper part displays identification information (fig. A22), and the lower part (mint-green 

background) displays resource data (fig. A23). Each part 

corresponds to a numeric identifier (DepID and ResID, respectively) and an associated list of references. Identification information is stored in the table 1_Deposittbl; the resource data 

is from the table 2_Resourcestbl. Blue-outlined boxes in each 

part display the references cited from the master table of references, 3_Referencetbl. Contents of each field are described in 

the Tables subsection of Database Design (see table A4).

The upper part of the form (fig. A22) contains basic site 

identification information for the entire deposit such as its 

name, identification, location, and other details. Contents of 

each field (table A5) are described in the previous section of 

this chapter. 

The lower part of the form (fig. A23) displays the 

resource and production records for the deposit. Only one 

resource record is viewed at a time on this form; how to view 

all of the records will be discussed a little later.

Note that two record numbers are displayed at the bottom 

left corners of both the lower frame (2_Resourcestbl_frm) and 

at the lower left of the outer frame (1_Deposittbl_frm). These 

are circled on figs. A22 and A23. When viewing the entire 

1_Deposittbl_frm, the lowermost represents a unique numeric 

identifier within the deposits table, the upper represents an 

identifying number in the resources table. Be extremely careful to not confuse these numbers with those for DepID and 

(or) RefID, because the record number can change when the 

data tables are sorted or filtered. Therefore, do not assume, 
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 139

for example, that deposit record 1 (of 124) will always be 

the Karu East deposit. But Karu East will always correspond 

to DepID = 1. Similarly, resource record 1 (of n) generally 

will not correspond to ResID = 1. You can scroll through the 

records in either frame by navigating with the arrows on the 

lower left or typing the record number directly into the white 

box (blank space). Click on the symbol “|<” (vertical bar 

followed by arrowhead pointing to the left) to view the very 

first record, or on “>|” (vertical bar followed by arrowhead 

pointing to the right) to view the very last record. Click on the 

symbol “>*” (greater than symbol followed by an asterisk) to 

append a new blank record at the end of the file (you must be 

in write mode to add records). Again, be very careful not to 

confuse record number with the value in DepID or ResID.

Identification Information in 1_Deposittbl_frm

The file is automatically numbered (currently 1-131, 

missing some numbers that were assigned to records that have 

been merged or deleted) in the DepID field (second from left 

in the green RESOURCE area of the form). The record number for each deposit may change depending on how the file is 

sorted, but the DepID (upper right, green circle on fig. A22) 

will never vary. 

Also embedded in this upper form, outlined in pink (fig. 

A22), is the computation of the overall grade and tonnage, or 

total endowment of the individual deposit (not the Group). 

This is a computed field, described in the previous section. 

We’ll describe how it is derived after the resource information 

discussion that follows.

Resource Information in 2_Resourcestbl_frm and 

1_Deposits_frm

The lower part of the main form (mint-green background) 

displays resource data for the deposit which is stored in the 

table 2_Resourcestbl: We’ll refer to these data as the Resource 

Records. Each deposit can have many Resource Records, 

although most have only one or two. These are numbered 

similarly to the overall deposit records (Record count at lower 

left of frame, but each has a unique ResID number) and can 

be thought of as subrecords. All of the resource (and production) values included in the database are used to compute the 

total endowment of each deposit. Total endowment is reported 

as a single grade and tonnage in the embedded, pink-outlined 

box in the upper part of the identification form (figs. A21 and 

A22).

For example, the record for the Konkola deposit, (DepID 

79) lists 19 resource subrecords (circled in red on fig. A24), 

all of which are used to compute the endowment (fig. A24). 

Many of these records list production for specific time periods, 

or resources for different parts of the deposit (scroll through 

Records 1 through 19 using the arrows at lower left and look 

at the Resource Category field. For example, you will see 

that resources are categorized as “production” for ResID 

14, “inferred resource” for ResID 208 (for a subpart of the 

deposit, Konkola North--South Limb), and “inferred” for 

ResID 209 (for another subpart, Konkola North--East Limb). 

Most deposits have many fewer subrecords because the production and resource data are not as well documented.

Reference Information

References cited are listed at the base of each of the 

two parts of the entry form 1_Deposittble_frm within boxes 

outlined in light blue. Due to space constraints, only one 

reference can be viewed in the Form View. However, there is 

a scroll bar on the right edge of each box (outlined in blue) 

that indicates that more data exists in the database and the user 

should scroll to view the other references. Another way to see 

all the references at once is to print them (see next section).

Calculating Resource Endowments

The “how” of this computation is described in the first 

part of this chapter. Endowment may be recomputed by using 

the second button on the Switchboard (fig. A14): “Run Deposit 

grade/ton Query.” 

Print Records

All the records can be printed from the form 1_Deposittbl_frm. The fields will expand, if necessary (for example 

to show all the references), and multiple resource records will 

also print. Open 1_Deposittbl_frm in Access. Select “File”, 

then “Print” then “All.” To print a subset of the records, run a 

filter, then print “All.” To print only one record, view it, and 

select Print/Selected Records(s).

Frequently Asked Questions (FAQs)

What happens when a query button I selected is on the switchboard screen?

The Switchboard form (fig. A14) provides three options. 

The left-most button opens a form that includes a view of all 

data table records associated with a single deposit from which 

a user can enter new data, delete or replace existing data, or 

add a new deposit record. The middle button runs a query 

which shows the deposit record number, deposit name, deposit 

type, deposit subtype, total tonnage, weighted average copper 

and cobalt grades, latitude, and longitude for each deposit 

record in a spreadsheet format. This is not editable, but can be 

copied to a spreadsheet program (for example, the Excel file 

CACB_deposits.xls included with this report). The right-most 

button runs a query that does the same thing (minus the latitude and longitude) for deposit groups, which are used for the 

development of the associated CACB sediment-hosted copper 

deposit models. The results of this query are given in the Excel 

file CACB_groups.xls that is included with this report.
140 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Figure A21. Deposit entry form, 1_Deposittbl_frm, opens when “Open Data Entry Form” button is selected from switchboard.
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 141

Figure A22. Upper part of data entry form, 1_Deposit_frm. (Window was resized by dragging the lower right corner upwards to hide 

lower part of the form but still retain the record count in the bottom of the frame. Note the record number circled in red at the lower left 

and DepID circled in green at upper right.)

Figure A23. Lower part of the main 1_Deposittbl_frm is 2_Resourcestbl_frm (treated like a subform). (Note the record number circled at 

the lower left.)
142 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Figure A24. Record for the Konkola Deposit showing 19 resource subrecords (red circle), all of which are combined to compute 

the endowment (pink outline). (Scroll bar to view additional Deposit References is circled in blue.)
Appendix A. Relational Database of Sediment-Hosted Copper Deposits, Resources, and Production 143

How do I navigate through the deposit table form?

Navigation through the 1_Deposittbl_frm (figs. A15, 

A21, A24) can be done by using the tab key or a mouse. The 

tab order is left to right, top to bottom. Dropdown menus in 

selected fields provide a list of acceptable terms. To search 

on any field, simply click the cursor in the field, use Edit/

Find on the upper tool bar (or Ctrl F), and type what it is you 

wish to find (not case sensitive). To jump to another record or 

subrecord, use the Record number field or arrows on the lower 

right. If more references are available than fit on the screen, a 

scroll bar will appear on the far right edge of the References 

part of the form. Simply drag the scroll bar, or use the Page Up 

or Page Down button on the keyboard. This database works 

the same way as most other databases. (And as long as the 

database is set “Read-only” you can’t accidently mess it up.)

How do I find a record for a particular site or all the sites for 

a particular property?

The form can be “filtered” to view specific information. 

In Access 2000 - 2003, from the menu select Records/Filter/

Filter By Form. (In Access 2010, the Filter By Form command 

is found under the Home tab, in Sort & Filter, Advanced). 

Type the information you want to filter in the appropriate 

box. Wildcards are permitted by starting the filter term with 

“like” followed by the term and wildcard characters (asterisk 

* for multiple characters, question mark ? for single characters) all in quotes (for example, in the Deposit Name box the 

string [like “bal*”] (without the brackets) will find the Baluba 

deposit record). Access is not case sensitive.

How do I print the data for all the deposits, a set of deposits, 

or a specific deposit?

All the records can be printed from the 1_Deposittbl 

form. Open the form and select File/Print/All. The fields will 

expand, if necessary, so that all the resource records and references will print. Printing to Adobe PDF printer, if available, 

will create an easily searchable PDF document (for example, 

the PDF file Data Entry Form.pdf included with this report). 

The form is designed to print records on a letter size, portrait 

view page. The pages will break on individual records. In 

some cases, multiple pages are necessary to print one record. 

To print a subset of records, run a filter (see FAQ 3, 

above) and select File/Print/All. This will print only the 

filtered results. To print only one record, make sure that is 

the record you are viewing, then select File/Print/Selected 

Record(s). Printing has been tested only with two HP printers 

and an Adobe PDF printer: there are no guarantees that this 

will work with all printers.

Why doesn’t the form look the way I expect it to look? 

Most of the forms are meant to be used on other forms, not 

by themselves. It is possible for the user to open any form and 

make changes in the size of that form (in design view mode). If 

this happens and you save the changes, that form might then be 

larger than the space reserved on the form that it was designed 

to be embedded in and may not display or print correctly. The 

main form is designed to allow the user to print records on 

8.5 × 11 paper (with only 0.5 in. margins right and left and 

1 in. top and bottom) and a change, especially if the subform is 

wider, may cause a partial print page for any part of the form 

that is wider than maximum width allowed by the printer. Every 

printer is different. Check that the output for only one record is 

acceptable before attempting to print many records.

What do I need to do to update a record?

Any record may be updated or changed if the file is not 

set for “read only”. Values for DepID, ResID, and RefNo are 

automatically assigned when data is entered into the tables 

(or forms) 1_DepositTbl, 2_Resourcestbl, or 3_Referencetbl, 

respectively; therefore, these fields cannot be edited. Most 

fields can be modified or updated directly on the 1_Deposittbl_frm. New records can be added using the data entry 

form, but it is preferable to revise existing records. Records 

should be deleted through the tables, not from the forms, 

because cascading deletes are set for any record in 1_Deposittbl so as to remove associated 2_Resourcestbl records. Do 

not keep any resource records that you do not want, because 

statistics are computed assuming that all resource records are 

necessary and correct.

Acknowledgments

The authors are grateful to our colleagues in academia 

and industry to encouraging us to prepare this compilation, 

directing us to relevant information, and sharing unpublished 

data with us. In particular, we acknowledge David Broughton 

(Ivanplats Limited), Murray W. Hitzman (Colorado School of 

Mines), and Jonathan Woodhead (Colorado School of Mines).

Jane Hammarstrom of the USGS in Reston provided comments on an early version of this report. USGS colleagues Daniel Mosier, James Bliss, and Pamela Dunlap, with the USGS, 

provided helpful and timely technical reviews of the final report.
144 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

References Cited 

Cox, D.P., Lindsay, D.A., Singer, D.A., Moring, B.C., and 

Diggles, M.F., 2003, revised 2007, Sediment-hosted copper 

deposits of the world—Deposit models and database: U.S. 

Geological Survey Open-File Report 03-107, v. 1.3, 53 p. 

(Also available at http://pubs.usgs.gov/of/2003/of03-107/.)

Fortin, Paul, 2006, Gécamine future prospects: accessed 

9 February, 2010, at http://www.canaccordadams.

com/NR/rdonlyres/AA6A5FD-19EA-4A36-8D2DA217ECC2C2D7/0/Gecaminespresnetation.pdf, 32 p.

Freeman, P.V., comp., 1988, Description of mineral deposits 

on the Copperbelt (and Kabwe, Nampundwe): Lukasa, 

Zambia, [Consolidated Copper Mines Ltd. (ZCCM) unpublished company report], 88 p.

Kirkham, R.V., Carriere, J.J., Laramee, R.M., and Garson, 

D.F., 1994, Global distribution of sediment-hosted stratiform copper deposits and occurrences: Geological Survey 

of Canada Open File 2915b, 256 p. 

Kirkham, Rodney, and Broughton, David, 2005, Supplement 

to the sediment-hosted stratiform copper ore system, in 

Hedenquist, J.W., Thompson, J.F.H., Goldfarb, R.J., and 

Richards, J.P., eds., Economic Geology—One hundredth 

anniversary volume 1905-2005: Littleton, Colorado, Society 

of Economic Geologists, Inc., p. 609–642.
Appendix B. Spatial Databases for Sediment-Hosted Stratabound and Structurally Controlled Replacement 145

Appendix B. Spatial Databases for Sediment-Hosted 

Stratabound and Structurally Controlled Replacement and Vein 

Copper Deposits and Prospects, Central African Copperbelt, 

Democratic Republic of the Congo and Zambia

By Heather L. Parks, J. Douglas Causey, Paul D. Denning, Timothy S. Hayes, John D. Horton, Michael J. 

Kirschbaum, Cliff D. Taylor, Anna B. Wilson, Niki E. Wintzer, and Michael L. Zientek

Introduction

Databases and maps of the location, size, and geologic 

type of known mineral deposits and occurrences are essential 

components of mineral resource assessment studies. Three 

spatial databases provide data for use in an assessment of 

undiscovered sediment-hosted copper resources in the Central 

African Copperbelt (CACB) in the Democratic Republic of 

the Congo (DRC) and Zambia. The CACB is a large oresystem that formed sediment-hosted stratabound and structurally controlled replacement and vein (SCRV) copper deposits. 

Aboriginal cultures produced copper from this region as early 

as the 7th century; European companies started producing copper in the early 1900s. 

The spatial databases are presented as Esri shapefiles, 

which contain spatial and descriptive data for deposits and 

prospects, ore bodies, and open pits. These databases can be 

queried in a geographic information system (GIS) to portray 

the distribution, geologic setting, and resource potential of 

copper deposits and to model grade and resource tonnage in 

the region. Examples of maps that can be created from the 

three shapefiles are shown on figures B1, B2, and B3.

Overview of Spatial Databases

The spatial databases are briefly described in table B1. 

They are provided in vector format as Esri shapefiles and 

packaged with a look up table for unit descriptions, a metadata file, list of references cited, and a brief descriptive ASCII 

text file in the compressed archive file sir2010-5090j_GIS.

zip which is available on the Internet at http://pubs.usgs.gov/

sir/2010/5090/j/.

Deposits and Prospects

The spatial database for deposits and prospects, CACB_

deposits_prospects, is an Esri point shapefile that contains 

spatial and descriptive data for 529 deposits and prospects 

and 21 group sites which represent sediment-hosted copper 

and structurally controlled replacement and vein deposits 

and prospects in the CACB. It provides locations of deposits 

and prospects, in addition to descriptive information for use 

in a GIS and for estimating undiscovered mineral resource 

endowments.

The dataset was created, in part, from pre-existing compilations, reports, and maps of copper deposits and prospects. 

Descriptive data from digital files were normalized and 

combined into a single shapefile; data for sites with multiple 

records then were resolved to provide a single record for each 

site. Information for tonnage and grade were derived from the 

Microsoft Access® database CACB_sedCu_deposits.mdb (see 

appendix A). Group sites were created to represent multiple 

sites that have been grouped together using a 500-meter 

aggregation distance for the purposes of grade and tonnage 

modeling. These sites can be identified using the “SiteStatus” 

field in the attribute table. Examples of group sites are shown 

in figures B1 and B3. 

The positional accuracy of the location for each site was 

checked against mineral occurrence maps and figures from 

reports. Locations of many sites were derived from coordinates provided in reports and databases; some were manually digitized from figures and maps in reports. Deposit and 

prospect locations were corrected using the highest resolution data available. For example, a 1:100,000-scale map 

took precedence over a 1:1,000,000-scale map for the site 

location. Some locations of developed sites were compared 

against mines visible on satellite imagery on Google Earth1

and were shifted accordingly. The maps and satellite images 

used different datums; we converted all reference material to 

the same datum (WGS, 1984) when we corrected locations.

We investigated a variety of data: published and unpublished, open access and licensed, public and propriety. Sites 

that could not be verified using publicly available data were 

excluded from the compilation. Examples of the types of 

1

http://www.google.com/earth/index.html.
KOV Mupine Komoto East Dikuluwe Mashamba West Mashamba East Musonoie T17 West Katanga Kamoto KOV Kamoto Principal Mashamba East Kamoto Etang DIMA Mupine Oliveira Kamoto East Kamoto North Mashamba Musonie T17 Kamoto Principal Kamoto-KOV-Musonie-Mupine Dikuluwe Kamoto Etang West Mashamba East West Kamoto-KOV-Musonie-Mupine group of deposits 25°22'E 25°24'E 25°26'E 10°42'S 10°45'S Political boundaries from U.S. Department of State (2009). Africa Lambert Conformal Conic Projection. Central meridian, 26° E., latitude of origin, 0°. ZAMBI

DEMOCR

OF T

24°E 

10°S 12°S 0 1 2 KILOMETERS 0 0.5 1 MILES Sediment-

name sh

Orebody e

red - Mas

Open pit, n

italics - M

EXP

Sediment-

name sh

DIMA group of deposits 

Table B1. Map showing points for deposits, points for grouped deposits, the areal extent of ore bodies, and open pits in the northwestern part of th

Copperbelt in the Democratic Republic of the Congo (ore body outlines modified from Dixon and others, 2009). Dashed boxes show the clusters of dtonnage and grade modeling.
25°22'E 25°24'E 25°26'E

10°42'S

10°45'S

ZAM

DEMOCR

OF T

24°E 

10°S12°S

EXPL

OO

0 1 2 KILOMETERS0 0.5 1 MILES

Political boundaries from U.S. Department of State (2009).Landsat imagery from http://services.arcgisonline.com/arcgis/services.Africa Lambert Conformal Conic Projection. Central meridian, 26° E., latitude of origin, 0°.

Area 

Table B2. Landsat image showing the areal extent of ore bodies and open pits in the northwestern part of the Central African Copperbelt in the Dem

Congo (ore body outlines modified from Dixon and others, 2009).
Konkola Saddle Lode East Musoshi Konkola North Area A or Saddle Lode Centre Kakosa South Orebody - Extension Konkola South Limb Kirila Bomwe North Orebody North Limb Central Kirila Bomwe North Orebody North Kirila Bomwe North Limb East Orebody West Konkola Saddle Lode West Konkola East Limb Kirila Bomwe South Orebody North Kirila Bomwe South Orebody Duplicate Konkola West Fitwaola Musoshi Fitwaola Konkola-Musoshi Konkola East Limb Konkola South Limb Konkola Orebody No.2 Kirila Bomwe South No.1 Konkola Saddle Lode East Kirila Bomwe North Orebody West Kirila Bomwe South Orebody North Kakosa South Orebody - Extension Kirila Bomwe North No.3 Konkola West Kirila Bomwe South Orebody Duplicate Konkola North Orebody North Limb East Konkola Area A-Saddle Lode Center Konkola Saddle Lode West 27°45'E 27°50'E 27°55'E 12°20'S 12°25'S 

27°

12°S 15°S EX

0 2 4 KILOMETERS 0 1 2 MILES DEMOCR

REPUB

OF THE C

Sediment

name sh

Orebody 

red - Mu

Sediment

name sh

 Musoshi Political boundaries from U.S. Department of State (2009). Landsat imagery from http://services.arcgisonline.com/arcgis/services. Africa Lambert Conformal Conic Projection. Central meridian, 26° E., latitude of origin, 0°. 

Table B3. Landsat image showing deposits, grouped deposit, and areal extent of ore bodies for the Konkola-Mutoshi area in the Central African C

Democratic Republic of the Congo and Zambia (ore body outlines modified from Wolf, 1976; Chileshe and Kulkarni, 1992; and Simposya and Hart, 20
Appendix B. Spatial Databases for Sediment-Hosted Stratabound and Structurally Controlled Replacement 149

Table B1. Description of digital data files for spatial databases (geographic information systems, GIS).

File Name File Description

Compressed archive file containing spatial databases, associated metadata files, references, and readme.txt

sir2010-5090j_GIS.zip GIS and associated files: Esri shapefiles, metadata (*.xml), references (*.xlsx, and *.txt), and 

readme.txt (ASCII text).

Esri shapefiles

CACB_deposits_prospects.shp Sediment-hosted (stratabound and SCRV) Cu deposits and prospects.

CACB_open_pits.shp Sediment-hosted Cu deposit open pits.

CACB_orebodies.shp Sediment-hosted Cu deposit ore bodies.

Relational table

Unit_look_up_table.xlsx Table with unit names and descriptions that can be joined to the Unit field in the shapefile 

CACB_deposits_prospects.shp.

Metadata –eXtensible markup language (XML) format (*.xml) files 

CACB_deposits_prospects_metadata.xml Metadata for shapefile of deposits and prospects.

CACB_open_pits_metadata.xml Metadata for shapefile of open pits.

CACB_orebodies_metadata.xml Metadata for shapefile of ore bodies.

List of full references

GIS references.txt List of short references used in shapefiles and complete references.

GIS references.xlsx Table listing short references used in shapefiles and complete references.

information used are summarized in table B2; a complete list 

of sources used can be found in the references file provided 

with the databases.

Table B3 lists the fields in the database and the information contained in each. The site name (listed in the field 

“Name”) is based upon the most frequent usage in publicly 

available sources. Codes in the field “Unit” are based on 

Cailteux and others (2007) correlation of units in Zambia and 

the Democratic Republic of the Congo. A look up table has 

been included and can be joined with the “Unit” field in a GIS 

to obtain definitions of the unit codes. Table B4 shows the 

Katangan Supergroup stratigraphic unit lithologic descriptions 

and the correlation between Zambian and DRC units.

Ore Bodies 

The spatial database for copper ore bodies, CACB_orebodies, is an Esri polygon shapefile that contains spatial and 

descriptive information for 101 polygons representing 95 

copper deposits hosted in sedimentary rocks which have been 

defined by exploration. Its purpose is to document the areal 

extent (as projected to the surface) of known ore bodies in the 

Central African Copperbelt and to constrain estimates of mineral resource endowment for the region. The extents of several 

ore bodies are shown in plan view in figures B1, B2, andB3.

Areal extents of ore bodies were manually digitized from 

plan-view maps that were georeferenced for use in a GIS. The 

shape of an ore body can reflect geologic contacts, economic 

cutoff limits, and (or) property boundaries. Table B5 lists the 

fields in the database and the information contained in each. Ore 

bodies were given the name of the deposit to which it belonged.

Open-Pit Mines

The spatial database for open pits, CACB_open_pits, is 

an Esri polygon shapefile that contains spatial and descriptive 

information for 85 polygons representing 76 open-pit mines 

of sediment-hosted copper deposits in the CACB. It provides 

the areal extent of open pit mining and was designed for use in 

mineral assessments to constrain estimates of mineral resource 

endowment. The extents of several open pits are shown in plan 

view in figures B1 and B2.

Surface extents of open pits were manually digitized 

from Google Earth satellite imagery and the data were then 

imported into an Esri shapefile format. The open pits were 

given the same name as that of the corresponding mine seen 

in Google Earth or corresponding deposit or prospect. Table 

B6 lists the fields in the database and the information contained in each.
150 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table B2. Examples of the types of sources used to compile the CACB_deposits_prospects shapefile.

Data type Citation

Information in the public domain 

Report Guernsey (1952)

Report with map François (1974)

Report with spatial database Kirkham and others (1994)

Spatial databases Cox and others (2003); Kirkham and others (2003); Huderek (2008a,b, 2010)

Licensed and proprietary information

Proprietary minerals database Infomine1

, Intierra2, Metals Economic Group3

Spatial databases GeoPubs (1998); Veselinovic-Williams and Frost-Killian (2003); Chartry and Franceschi (2004); 

Zambia Geological Survey Department, written commun., 2006; Musée Royal de l’Afrique 

Centrale (2008); Laghmouch (2008b)

Unpublished minerals reports Freeman (1988); Armand François, written commun., 1996

1

http://www.infomine.com/.

2

http://www.intierra.com/Homepage.aspx.

3

http://www.metalseconomics.com/default.htm.
Appendix B. Spatial Databases for Sediment-Hosted Stratabound and Structurally Controlled Replacement 151

Table B3. Definitions of user-defined fields in the attribute table for the shapefile CACB_deposits_prospects.

Field name Description

Deposit_ID Unique numeric identifier for site.

DepID Numeric identifier which correlates to DepID in the data table 1_Deposittbl in the Microsoft Access database 

CACB_sedCu_deposits.mdb (see appendix A).

Group_name Name for cluster of deposits which are grouped together (and for which resource data are aggregated) in order to 

describe and model grade and tonnage; correlates to GroupName in the data table 1_Deposittbl in the Microsoft 

Access database CACB_sedCu_deposits.mdb (see appendix A).

Name Name of site.

Name_other Other names used for the site.

Includes Names of deposits that were grouped based on proximity (see use of the 500 meter rule in appendix A); list may 

overflow into the field “Includes2.”

Includes2 Continuation of list of names of deposits that were grouped based on proximity (see use of the 500 meter rule in 

appendix A).

Katangan Entry identifies if site is located in the Katangan Supergroup or not; “yes” for hosted in the Katangan Supergroup, 

“no” for not located in Katangan Supergroup.

Type Mineral deposit type.

Subtype Sediment-hosted copper subtype.

SiteStatus Status of site; prospect – grade and tonnage values are not provided, deposit – grade and tonnage values are provided, and group – represents multiple deposits within 500 m of each other that have been grouped together due 

to 500 meter aggregation rule.

Latitude Latitude in decimal degrees, −90.00000 to 90.00000. Negative south of the equator.

Longitude Longitude in decimal degrees, −180.00000 to 180.00000. Negative west of the Greenwich meridian.

Country Country in which the site is located.

State_Prov State or province in which the site is located.

Age_range Age of host rock in standard divisions of geologic time.

Comm_major Major commodities in decreasing order of economic importance.

Tonnage_Mt Ore tonnage in millions of metric tons; zero indicates no data.

Cu_pct Average copper grade in weight percent; zero indicates no data.

Co_pct Average cobalt grade in weight percent; zero indicates no data.

Con_Cu_t Contained copper in million metric tons; zero indicates no data.

Comments Miscellaneous comments.

HostRocks Simplified lithologic description of host rocks.

Unit Geologic map unit label in which site is located; see table 3 for detailed information relating label to rock unit description.

Footwall Lithology of footwall rocks.

Hangwall Lithology of hangingwall rocks.

Mineralogy Ore and gangue minerals in approximate order of abundance.

Ref_short Short reference; abbreviated citation for reference; full reference is provided in references file.

Tctnic_set Tectonic setting; entry describes the type of associated structural feature.

Complex Tectonic complex; name of the associated structural feature.
152 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Table B4. Description of Katangan lithologies used in the “Unit” field (modified from Cailteux and others, 2007).

[Note: Descriptions of units younger and older than the Katangan Supergroup are not included in this table]

SUPERGROUP GROUP SUBGROUP FORMATION LITHOLOGY

Katangan

Kundelungu – Ku 

(formerly Upper 

Kundelungu 

- Ks)

Biano - Ku 3 arkoses, conglomerates, argillaceous sandstones

Ngule - Ku 2

Sampwe - Ku 2.3 dolomitic pelites, argillaceous to sandy siltstones

Kiubo - Ku 2.2 dolomitic sandstones, siltstones and pelites

Mongwe - Ku 

2.1 dolomitic pelites, siltstones and sandstones

Gombela - 

Ku 1

Lubudi - Ku 1.4 pink oolitic limestone and sandy carbonate beds

Kanianga - Ku 

1.3 carbonate siltstones and shales

Lusele - Ku 1.2 pink to grey micritic dolomite

Kyandamu - Ku 

1.1 Petit Conglomérat (glacial diamictite)

Nguba – Ng 

(formerly Lower 

Kundelungu 

- Ki)

Bunkeya - Ng 2

Monwezi - Ng 

2.2 dolomitic sandstones, siltstones and pelites

Katete - Ng 2.1

dolomitic sandstones, siltstones and shales in 

northern areas; alternating shale and dolomite 

beds (“Série Récurrente”) in southern areas

Muombe - Ng 1

Kipushi - Ng 1.4 dolomite with dolomitic shale beds in 

southern areas

Kakontwe - Ng 

1.3 carbonates; Zn-Cu-Pb

Kaponda - Ng 

1.2

carbonate shales and siltstones; “Dolomie 

Tigrée” at the base

Mwale - Ng 1.1 Grand Conglomérat (glacial diamictite)

CONGO ZAMBIA

GROUP SUBGROUP FORMATION LITHOLOGY LITHOLOGY FORMATION SUBGROUP

Roan R

Mwashya 

(formerly 

Upper 

Mwashya) 

- R4

Kanzadi - R 4.3 sandstones or alternating siltstones and shales dolomitic shales, 

grey to black 

carbonaceous 

shales, 

quartzites

Mwashia Mw 

1.1

Kafubu - R 4.2 carbonaceous shales

Kamoya - R 4.1

dolomitic shales, siltstones, sandstones, including 

conglomeratic beds and cherts in variable 

position

Dipeta - R 3

Kansuki - R 3.4 (formerly Lower Mwashya): dolomites including 

volcaniclastic beds; Cu-Co

dolomites to arenitic dolomites 

interbedded 

with dolomitic 

shales; intrusive gabbros 

(formerly 

Carbonate 

Unit or Upper 

Roan)

Bancroft 

Kanwangungu 

RU 1 and 

RU 2 Kirilabombwe

Mofya - R 3.3 dolomites, arenitic dolomites, dolomitic 

siltstones

R 3.2

argillaceous dolomitic siltstones with 

interbedded sandstone or white dolomite; 

intrusive gabbros

R.G.S. - R 3.1 argillaceous dolomitic siltstones 

(“Roches Greso-Schisteuses”)

shales with grit

 (Antelope 

Clastics)

Kibalongo 

RL 3

Mines - R 2

Kambove - R 2.3

stromatolitic, laminated, shaly or talcose dolomites; locally sandstone at the base; interbedded siltstones in the upper part; Cu-Co

dolomite, argillite 

beds at top Chingola RL 4

Kitwe

Dolomitic shales 

- R 2.2

R 2.2.2 and 3: dolomitic shales containing 

carbonaceous horizons; occasional dolomite 

or arkose

arkoses, sandy 

to dolomitic 

argillites

Pelito-arkosic 

RL 5

R 2.2.1: arenitic dolomite at the top and dolomitic shale at the base; pseudomorphs after 

evaporite nodules and concretions; Cu-Co

arenites, 

argillaceous 

dolomites, 

argillites, 

dolomites, 

evaporites; 

Cu-Co

Ore Shale 

RL 6

Kamoto - R 2.1

stromatolitic dolomite (R.S.C.), silicified/arenitic 

dolomites (R.S.F./D.Strat.), grey argillaceous 

dolomitic siltstone at the base (Grey R.A.T.); 

pseudomorphs after evaporites at the contact 

with RAT.; Cu-Co

R.A.T. - R 1 red argillaceous dolomitic siltstones, sandstones and pelites

 (“Roches Argilo-Talqueuses”)

conglomerates, 

coarse arkoses 

and argillaceous siltstones

Mutonda

Mindola - 

base of the R.A.T. sequence - unknown quartzites Kafufya RL 7

< 900 Ma basal pebble and cobble conglomerate

pebble and 

cobble conglomerate

Chimfunsi

± 2,050 Ma KIBARAN and PRE-KIBARAN
Appendix B. Spatial Databases for Sediment-Hosted Stratabound and Structurally Controlled Replacement 153

Table B5. Definitions of user-defined attribute fields in the shapefile CACB_orebodies.shp.

Field name Description

Orebody_ID Unique numeric identifier for ore body.

Name Name of deposit to which ore body belongs; correlates to Name in the shapefile CACB_deposits_prospects and to 

Name in the shapefile CACB_open_pits. (Multiple ore bodies can exist for one deposit.)

DepID Numeric identifier which correlate to DepID in the data table 1_Deposittbl in the Microsoft Access database CACB_

sedCu_deposits.mdb (see appendix A).

Group_name Name of group to which ore body belongs. Groups represent clusters of deposits which are grouped together (and for 

which resource data are aggregated) in order to describe and model grade and tonnage; correlates to GroupName in 

the data table 1_Deposittbl in the Microsoft Access database CACB_sedCu_deposits.mdb (see appendix A).

Area_km2 Area of the areal extent (as projected to the surface) of the ore body, in square kilometers.

Ref_short Short reference; abbreviated citation for reference; full reference is provided in references file.

Table B6. Definitions of user-defined attribute fields in the shapefile CACB_open_pits.shp.

Field name Description

OpenPit_ID Unique numeric identifier for open pit.

Name Name of deposit to which open pit belongs; correlates to Name in the shapefile CACB_deposits_prospects and to 

Name in the shapefile CACB_orebodies.

DepID Numeric identifier which correlate to DepID in the data table 1_Deposittbl in the Microsoft Access database CACB_

sedCu_deposits.mdb (see appendix A).

Group_name Name of group to which open pit belongs. Groups represent clusters of deposits which are grouped together (and for 

which resource data are aggregated) in order to describe and model grade and tonnage; correlates to GroupName in 

the data table 1_Deposittbl in the Microsoft Access database CACB_sedCu_deposits.mdb (see appendix A).

Area_km2 Area of open pit, in square kilometers.

Ref_short Short reference; abbreviated citation for reference; full reference is provided in references file.
154 Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted Copper Deposits

Acknowledgments

The authors are grateful for helpful and constructive 

technical reviews provided by USGS colleagues James Bliss, 

Pamela Dunlap, and Daniel Mosier.

References Cited

Cailteux, J.L.H., Kampunzu, A.B., and Lerouge, C., 2007, The 

Neoproterozoic Mwashya-Kansuki sedimentary rock succession in the Central African Copperbelt, its Cu-Co mineralization, and regional correlations: Gondwana Research, v. 

11, no. 3, p. 414–431.

Chartry, G., and Franceschi, G., comps., 2004, Mineral occurrences database and GIS map of the Democratic Republic 

of [the] Congo: Royal Museum for Central Africa, scale 

1:2,000,000, CD-ROM.

Chileshe, B.C., and Kulkarni, R.V., 1992, Konkola Deep mining project—Concept and planning: Mine Water and the 

Environment, v. 11, no. 3, p. 1–15.

Cox, D.P., Lindsey, D.A., Singer, D.A., and Diggles, M.F., 

2003, revised 2007, Sediment-hosted copper deposits of 

the world—Deposit models and database: U.S. Geological 

Survey Open-File Report 03–107 version 1.1, 50 p. (Also 

available online at http://pubs.usgs.gov/of/2003/of03-107/.)

Dixon, Roger, Simposya, Victor, Takolia, Ebrahim, Waldeck, 

Wally, Salter, Henrietta, von Wielligh, Anton, Naismith, 

Alan, Cilliers, Petrus, and McNeill, R., 2009, An independent technical report on the material assets of Katanga 

Mining Limited, Katanga Province, Democratic Republic 

of Congo (“DRC”): SRK Consulting Technical Report, 

prepared for Katanga Mining Ltd., March 17, 2009, 216 p. 

(Also available at http://www.sedar.com.)

François, Armand, 1974, Stratigraphie, tectonique et minéralisations dans l’arc cuprifère du Shaba (République du Zaïre) 

[Stratigraphy, tectonics and mineralizations in the Shaba 

copper-bearing arc (Republic of Zaire)] in Bartholomé, 

Paul, ed., Gisements stratiformes et provinces cupriferes 

[Stratiform deposits and cupriferous provinces]: Liège, Belgium, La Société Géologique de Belgique, p. 79–101.

Freeman, P.V., comp., 1988, Description of mineral deposits 

on the Copperbelt (and Kabwe, Nampundwe): Lukasa, 

Zambia, [Consolidated Copper Mines Ltd. (ZCCM) unpublished company report], 88 p.

GeoPubs, 1998, Geological dataset of the Central African 

Copperbelt: Essex, England, GeoPubs [dataset purchased 

from http://www.geopubs.co.uk/home.htm and downloaded 

on December 16, 2009].

Guernsey, T.D., 1952, A prospector’s guide to mineral occurrences in Northern Rhodesia: Salisbury, Charter House, 91 p.

Huderek, Richard, 2008a, Katangan Copperbelt: Google Earth 

KML file, accessed July–September 2009 and October 2010, 

at http://maps.google.com/maps/ms?ie=UTF8&hl=nl&oe=

UTF8&msa=0&msid=118078989952556264569.00044e1e

24afa04af0cca&output=kml.

Huderek, Richard, 2008b, Zambian_copperbelt.kml: Google 

Earth KML file, accessed July 8, 2009, and October 2010, at 

http://maps.google.com/maps/ms?hl=en&gl=us&ie=UTF8

&oe=UTF8&msa=0&msid=118078989952556264569.0004

51715e9f065a35bbe&output=kml.

Huderek, Richard, 2010, Katangan copperbelt.kml: Google 

Earth KML file, accessed July 6, 2011, at http://maps.google.

nl/maps/ms?ie=UTF8&oe=UTF8&msa=0&msid=118078989

952556264569.00044e1e24afa04af0cca&output=kml.

Kirkham, R.V., Carrière, J.J., and Rafer, A.B. comp., 2003, 

World distribution of sediment-hosted, stratiform copper 

deposits and occurrences: Geological Survey of Canada, 

unpublished, accessed Sept 26, 2009, at http://apps1.gdr.

nrcan.gc.ca/gsc_minerals/index.phtml?language=en-CA.

Kirkham, R.V., Carrière, J.J., Laramee, R.M., and Garson, 

D.F., 1994, Global distribution of sediment-hosted stratiform copper deposits and occurrences: Geological Survey 

of Canada Open File 2915b, 256 p.

Laghmouch, M., comp., 2008, L’Arc cuprifère du Katanga: 

géologie et minéralisations (2007)—GIS and raster [Katanga 

copper arc - geology and mineralization]: Tervuren, Belgium, 

Royal Museum of Central Africa, scale 1:500,000, CD-ROM.

Musée Royal de l’Afrique Centrale, 2008, Carte géologique de 

la République Démocratique du Congo, Region de KolweziKalukundi-Likasi, Parties occidentale et centrale de l’arc 

cuprifère du Katanga [Geological map of the Democratic 

Republic of Congo, Kolwezi Region-Kalukundi-Likasi Parties of Western and Central Katanga Copper Arc]: Tervuren [Belgium], Musée Royal de l’Afrique Centrale, scale 

1:200,000, CD-ROM.

Simposya, V.M., and Hart, P.C.L, 2008, Technical report on 

the mineral resources for the Konkola North Copper project, 

Chililabombwe, Zambia: SRK Consulting Project Number 

384408, prepared for TEAL Exploration and Mining Co., 

March 2008, 78 p. (Also available at http://www.sedar.com.)

U.S. Department of State, 2009, Small-scale digital international land boundaries (SSIB)—Lines, edition 10: Boundaries and Sovereignty Encyclopedia (B.A.S.E.), U.S. Department of State, Office of the Geographer and Global Issues.

Veselinovic-Williams, M., and Frost-Killian, S., 2003 [2007], 

Digital international metallogenic map of Africa: Council 

for Geoscience, South Africa and Commission for the Geologic Map of the World, scale 1:5,000,000, CD-ROM.

Wolf, K.H., ed., 1976, Handbook of strata-bound and stratiform ore deposits: Amsterdam, Elsevier, 585 p.
Produced in the Menlo Park Publishing Service Center, California

Manuscript approved for publication September 12, 2012

Layout and design by Judy Weathers
Taylor and others—Global Mineral Resource Assessment—Descriptive Models, Grade-Tonnage Relations, and Databases for the Assessment of Sediment-Hosted 

Copper Deposits—With Emphasis on Deposits in the Central African Copperbelt, Democratic Republic of the Congo and Zambia—Scientific Investigations Report 2010–5090–J