industrial minerals deposit models - usgs · are reporte.d . only when they are significant at the...

U. S. DEPARfMENT OF THE INTErtiOR U.S. GEOLOGICAL SURVEY

Industrial Minerals Deposit Models: Grade and tonnage models

edited by

G.J. Orris and J.D. Bliss

Open-File Report

92-437

This report is preliminary and has not been reviewed for conformity with U.S. Geological Survey editorial standards or with the North American

Stratigraphic Code. Any · use of trade. product or firm names is for · descriptive purposes only and does not imply endorsement by the U.S. .

Government.

TABLE OF CONTENTS

Page

Introduction …………………………………………………………….1

Grade and tonnage model of serpentine- hosted asbestos (8d) ………………………………………………..2

Grade, tonnage, and deposit-specific model of diamond kimberlite pipes (12) ……………………………………5

Preliminary grade and tonnage model of lithium pegmatites (13b) ……………………………………………………11

Contained material model of feldspar in pegmatites (13e) ……………………………………………………14

Preliminary grade and tonnage model of quartz veins and pegmatites (13g) ……………………………………….17

Preliminary grade and tonnage model of wollastonite skarns (18g) …………………………………………………………20

Grade and tonnage model of amorphous graphite (18k) ………………………………………………………23

Grade and tonnage model of fumarolic sulfur (25m) …………….26

Preliminary grade and tonnage model of fluorite veins (26b) …………………………………………………………..29

Preliminary grade and tonnge model of barite veins (27e) …………………………………………………………..32

Preliminary grade and tonnage model of sandstone/quartzite silica (30e) …………………………………35

Grade and tonnage model of bedded barite (31b) ………………...40

Preliminary contained material model of sedimentary kaolin (31k) …………………………………………43

Preliminary contained material model of limestone (32g) ……………………………………………………..45

Preliminary grade and tonnage model of bedded celestite (35a.1) ………………………………..47

Preliminary grade and tonnage model of potash-bearing bedded salt (35a.2) ………………………………50

Preliminary grade and tonnage model of marine bedded gypsum (35a.5) ……………………………………………53

Preliminary grade and tonnage model of lacustrine borates d(35b.3) ……………………………………….56

Preliminary grade and tonnage model of lacustrine gypsum (35b.9) ……………………………………………………..60

Preliminary solute model of sodium carbonate brines (35b.21) ……………………………………………………...63

Grade and tonnage model of disseminated flake graphite (37f) ………………………………………………………..67

Preliminary contained material model of residual kaolin (38h) ………………………………………………………....71

Grade, volume, and deposit-specific models of diamond placers (39d) ………………………………………….73

Preliminary grade and tonnage model of silica sand (39I) …………………………………………………….78

References ………………………………………………………………81

Appendix A: Country Codes …………………………………………82

·> .

INTRODUCTION

This report consists ofa series of grade, tonnage, and other depositspecific models for industrial minerals similar to those found · in U.S. Geological Survey (USGS) Bulletin 1693 (Cox and Singer,1986) ; Most of these models are ·new, others are updates of models originally .published .. in Cox and Singer (1986), and three of the models have been preViously published in non-USGS publications and are included here for the convenience of model users. Correlations between grades anq tonnages_ are reporte.d . only when they are Significant at the 5 percent level. Country codes for the deposits listed in this report may be found in AppendiX A. Model numbers refer to the classification system used by · Cox and Singer (1986) and modified by Orris and Bliss (1991) . .. Descriptive models for most of the quantitative models in . this report can ·be found in Orris and Bliss (1991) or in Cox and Singer (1986).

The user should·be also be aware of the following items: . · · Deposits, except for diamond placers, were not grouped by the

authors using distance rules such as those used to model ·· polymetallic veins (Bliss and Cox, 1986) or low-sulfide Au-quartz veins (Bliss, 1986}. However, some deposits as reported ate probably composed of multiple bodies of mineralization. The grade distributions for barite veins, sandstone-quartzite silica, bedded bartte, silica sand, martne bedded gypsum, and

· bedded cefestite exhibit extreme economic bias towards high grades. . · · .· . . ·. . · The grade distributions of wollastonite, potash in bedded salt, lacustrine gypsum, and lacustrine borates are normal. For several deposit types, grades • and ore tonnages were not

· · available, · but contained material figures were used to construct models. · · "' · . · In all cases, all known production and re&erves were used to . estimate deposit size, but the user should be aware that marty industrial mineral deposits are never formally evaluated for · reserves (reserve . figures ·are · geologic estimates and not drilled . · ore bodies) artd production figures may be incomplete. For some deposits, the exact physical nature of a deposit is not known. Some deposits may be single lenses or veins: others · could be groups of lenses or veins within a single stratigraphic horizon or host rock. · · . . · Some deposit types such as different types · of pegmatites, skarns, and brines may be as reflective of economic divisions as geologic differences.

1

Model8d

GRADE AND TONNAGE MODEL OF SERPENTINE-HOSTED ASBESTOS

By G.J. Orris

An earlier version of this model was published by Orris ( 1986a). Deposits· in this model are single deposits composed of stockworks of chrysotile asbestos. Grade is reported as percent of asbestos fibers with no distinction made between cross and slip fibers. There is no significant correlation between grade and tonnage in this model. See figs: 1. 2.

DEPOSITS

Name Country Name Country

Abitibi CNQU Kwangchon SKOR Advocate CNNF Lake Asbestos CNQU Asbestos Hill CNQU Las Brtsas ClBA Asbestos Island CNQU Lili CNQU Baryulgil AUNS Lewis Brook CNNF Be11 Mine CNQU Loghar AFGH Belvidere USVT Maizerets CNQU Bird-Ginn (Matheson) CNON McAdam CNQU Black Lake CNQU McDame CNBc British Canadian CNQU Midlothian CNON Caley CNIT Moladezhnoye USSR Carey /East Broughton CNQU Morro Dois Irmaos BRZL CanaBrava BRZL Msauli SAFR

· Cassiar Mine CNBC Munro CNON Clinton Creek CNYT National CNQU Coalinga USCA Nicolet Asbestos CNQU Continental CNQU Normandie/Penhale CNQU Copperopolis USCA · Pontbriand CNQU Courvan CNQU Qala-el-Nahl SUDN Cranboume CNQU Reeves CNON Daffodil CNON Rex CNYT Eagle USAK Roberge Lake CNQU Gilmont CMQU St. Adrien Mtn. CNQU Golden Age CMQU St. Cyr CNQU Havelock Mine SWAZ Santiago Papalo MX.CO Hedman CNON Sayan USSR Ingessana Hills SUDN Shihmien CINA Jeffrey CNQU Steele Brook CNQU King-Beaver Mine CNQU Tuolumne USCA Kinlock SAFR Windsor CNQU Kolubara-Azbet YUGO Woodsreef Mine AUNS Kudu Asbestos Mine ZIMB Zidani GREC

2

Serpentine-hosted Asbestos

0.7

~ C/)

0 0.6 c.. r;q Q

~ 0.5 0

z 0 § 0.4 0 c..

~ c.. 0.3

0.0~--~~--~-----L-----L----~----~--~~--~~--_.~~~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

Figure 1. Tonnage model for serpentine-hosted asbestos.

3

Serpentine-hosted Asbestos

1.0

0.9

0.8

~ · -0.7

CJ)

0 0.. r:tl

0.6

0 ~ 0 .;,o.s z 0 § 0 0..

0.4

~ 0.. 0.3

0.2

0.1

0.0~--~~--_.----~--~~----~--~--~~--~~----~0--~ 0.01 0.025 0.063 0.16 0.4 1.0 2.5 6.3 16 40 100

·ASBESTOS GRADE IN PERCENT

Figure 2 . Grade model for serpentine-hosted asbestos.

4

Model 12

GRADE, TONNAGE, AND DEPOSIT-SPECIFIC MODELS OF DIAMOND KIMBERLITE PIPES

By James D. Bliss

COMMENT: In addition to size and grade, average carat size and percentage of diamonds of industrial grade are needed to characterized diamond kimberlite pipes. Also included is a target-area model of outcrop areas. Classification of kimberlite pipes and kimberlite dikes is not always clear and one or more diamond kimberlite dikes may have been included. Data sets are rarely complete and resulted in various number of deposits used in each model. Percentage of industrial diamonds was not used from the Letlhankane and Jwaneng pipes. Both are outliers on a scatter plot of diamond grade and percentage of industrial diamonds. There is no significant correlation between grade and tonnage. There is significant correlation between largest diamond size and tonnage (r=0.82, n=10), and between outcrop area and tonnage (r=O. 74, n~18). See figs.3-7.

DEPOSITS

Name Country Name Counby

Bultfontein SAFR Letseng-La-Terai LSTO De Beers SAFR Majhgawan INDA Dokolwayo SWAZ Mir USSR Dutoitspan SAFR Monastery SAFR Finsch SAFR Mwadwi (W1lliamson) TNZN Frank Smith SAFR Orapa BOTS J agersfontein SAFR Premier SAFR Jwaneng BOTS Sloan 1 & 2 usco Kamfersdam SAFR Udatchnaya USSR Kimberley .SAFR Venetia SAFR Koffiefon tein . SAFR Victory No. 1 CINA Letlhankane (DKl) BOTS Wesselton SAFR Letlhankane (DK2) BOTS Zarnitsa USSR

5

DIAMOND KIMBERLITE PIPES

0 n c 20

0

0.8

~ C/)

0.7

0 0.. ril 0 0.6 ~ 0 z 0.5 0 § 0 0.. 0.4

~ 0..

0.3

o .o~· ----._----~--~----~----~~--~--~~--_.--~~--~ 0.0016 0.0063 . 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION METRIC TONS

Figure 3 . Tonnage model of diamond kimberlite pipes. ·

6

·. ~ (j) 0 ~ ~ Q

C:r.c 0

z 0 § 0 ~

~ ll.t

DIAMOND KIMBERLITE PIPES 1.0

0 n .. 20

0.8

0.7

0

0.6 0

0.5

0.4

0.3

o .o~--~~~~----._-4~----~--~~--~--~~----~--~ 0.032 0.056 0.1 0.18 0.32 0.56 1.0 1.8 3.2 5.6 10.0 .

DIAMOND GRADE IN CARATS PER METRIC TON

Figure 4. Model of diamond grade distribution in diamond kimberlite pipes.

7


0 n - . 24

~ 0.7

rJ) 0 c.c

0.6 r.l 0 ~ 0

0.5 z 0 §

0.4 0 c.c 0 ~ 0.3

0

0 .0~--~----~----~--~----~~--~~~--~~----~--~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

OUTCROP AREA (ha)

Figure 5. Model of outcrop areas of diamond · kimberlite pipes.

8 .

~ Cf)

~ f:rl Q

~ 0 z 0 § 0 0..

@ 0..

i_


1.0

n- 12

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0 .0 L..----L--.....1....---1---'-----IL--.....I....---L-..1---'---'----'--...,....J 0 10 20 30 40 50 60 70

PERCENTAGE OF INDUSTRIAL DIAMONDS

Figure 6 . Model of the percentage of industrial diamonds in diamond kimberlite pipes .

9

80 90 . 100


n ,.. 9

. :0.8 0

~ 0.7

0 (/') 0 .0-t 0.6 C:z:l 0 ,,

Cz.c 0 0.5 z 0 0

§ 0.4

a: ~ 0

Cl. 0.3

0.0081 0.07

0.04 0.1 0.25 0 .63 1.6 4.0 10.

' AVERAGE DIAMOND SIZE IN CARATS

Figure 7. Model of average diamond size.

10

Model l3b

GRADE AND TONNAGE MODEL OF LITHIUM PEGMATITES

By J.D. Bliss and G.J. Onis

The grades and tonnages in this model are for the distribution of lithium v - minerals, especially spodumene, in pegmatites. Other commodities,

commonly from other zones of the pegmatite may also be of economic interest. The deposits are composed of single pegmatites or groups of closely spaced pegmatites. There is no significant correlation between grade and tonnage in this model. See figs. 8, 9.

DEPOSITS

Name

Ann (Ann Dyke) Assinica Lake Aumacho Authier Bernie Lake Bet (Best Bet) Big (Murphy~ UM) BIN (LI) Bouvier Buck/Coe Buckham Lake Conway Duwl Eagle Elk Fl (J.M., Lit) Georgia Lake Goldreef HID (lita) lnternatlonal _Lithium Irgon Jake .jarnanak Jean Lake Jim (Greg, Ben) KI (Hidden Lake) Kings . Mountain Lac La Croix Lens Lit (Green Bay)

Counby .

CNNT CNQU CNON CNQU CNMN CNNT CNNT CNNT CNQU CNMN CNNT CNON CNQU CNMN CNNT CNNT CNON CNMN CNNT CNQU CNMN CNNT AFGH CNON CNNT CNNT USNC CNON CNNT CNMN

1 1

Name

Lower Pasghushta Lucy (Lucy No. 1) Lun-Echo (Mavis Lake) MAC (McDonald) Manono McVittie Mount Marion MUT (J.S.J.-2) Nama Nite (LI) Obok-tong Ontario Lithium Paint Pasghushta Paskhi Pidlite Dike Quebec Lithium Root Lake (McCombe) Sao Jose da Safira Shamakit Spot Taghawlor -Tanyang Thor (Echo, Tanco) Tsangal

. Vegan Violet VO (Cota) Wisa Lake Yaryhgul

Countiy

AFGH CNMN CNON CNNT ZIRE CNON AUWA CNNT CNON CNNT SKOR . CNON CNNT AFGH AFGH USNM CNQU CNON BRZL . AFGH CNMN AFGH SKOR CNNT AFGH CNON CNMN CNNT CNON AFGH

Lithium in Pegmatites

~ C/l

0.7

0 ~ ~ 0

0.6

~ 0 0.5 z 0 § 0.4 0 ~

~ ~

0.0 ~--~~------._~----~--~~----~----~----~----~----~ 0.0016 O.Cl063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

Figure 8. Tonnage model for lithium pegmatites.

12

Lithium in Pegmatites

1.0

~ (/'J

0.7

0 0-c 0.6 ril Q

~ 0.5 0

z 0 § 0.4

~

~ 0.3

GRADE IN PERCENT Li20

Figure 9. Grade model for lithium pegmatites.

13

Model13e

GRADE AND TONNAGE MODEL OF FELDSPAR IN PEGMATITES

.By J.D. BUss and G.J. Orris

This model shows the contained feldspar within pegmatites. This distribution represents those pegmatltes that have been worked by hand or could be worked by hand. Other commodities, commonly from other zones of the pegmatite, may also be of economic interest. See fig. I 0 .

DEPOSITS


Am beau CNOT Foxton CNOT Besner CNOT Friction USAZ Big Boulder usco Furlong CNOT Bobs Lake CNOT Gardner CNOT Botelhos BRZL Genesee No. 2 CNOT Brignall CNOT Gleason-Campbell CNOT Burnham CNOT Gole CNOT C.F. McQuire CNOT Gunter CNOT Cameron CNOT Hickey CNOT Cameron & Aleck CNOT Holmes CNOT Canadian CNOT Hop pins CNOT Canadian Bexyllium CNOT Imperial CNOT Card CNOT Jenkins CNOT Carey CNOT Keays CNOT Caruaru · BRZL Keyfortmore CNOT Causeway CNOT Kirkham CNOT Charles CNOT Loughrin Township CNOT Christie Township CNOT MacDonald CNOT Clora May usco Magnetawan CNOT Conger CNOT Mahoney & Morin CNOT Consolidated Feldspar CNOT Martin CNOT Craig CNOT Mattawa · CNOT Crystal No. 8 usco McQuire & Robinson CNOT Cubar CNOT Mendels CNOT Devil's Hole usco Mink Lake CNOT Dryden Township CNOT Morin & Neault CNOT Elizabeth CNOT Mt Pleasant CNOT Equador BRZL Muqul BRZL Eureka CNOT Nepawassi Lake CNOT F. Raymond CNOT Norrero CNOT Federal CNOT O'Brien & Fowler Feldspar Quarries CNOT (Calvin Township) CNOT Five Mile CNOT

14

" Name Countty Name Countiy

O'Brien & Fowler Rowe;s ·North Mine usco (March Township) CNOT . Silver Queen CNOT

O'Brien & Fowler T.H. Craig CNOT . (Mattawan Township) CNOT Thompson CNOT

Ojaipee CNOT Tough CNOT Orser CNOT Truelove CNOT Orser-Kraft CNOT W.B. Cameron CNOT Outpost USAZ W.J. Barr CNOT Patterson CNOT Wanup (Davis Perth CNOT Township) CNOT Prince & Prince CNOT Wanup (Dill Township) CNOT Purdy CNOT Watson No. 2 & 3 CNOT · Purdy Mica CNOT Wheeling CNOT Reeves CNOT Wilson CNOT

.,~ Reynolds CNOT Winnipeg CNOT Rock Lake· CNOT Woodcox CNOT Rosemont usco Woods CNOT

15

Feldspar in Pegmatites

0.8 ~

~ 0.7

en 0 0.. ~

0.6 0 ~ 0 0.5 z 0 § 0

0.4 p.. . o · 0::: 0.. 0.3

O .OL---~----~~--~--~~--_.~--~~--~--~----~--~ 0.006 0.02 0.1 0.4 1.6 6.3 25 100 400 1600 6300

TiiOUSAND TONNES

Figure 10. Contained tonnage model of feldspar in pegmatites.

16

Model 13g

GRADE AND TONNAGE MODELS OF QUARTZ VEINS

By G.J. Orris

The quartz in this model is of interest for its silica content and not for • quartz crystals. The deposits consist of single veins or pegmatltes or , closely clustered groups of veins. There is no significant correlation

between grade and tonnage in quartz veins and pegmatltes. See figs. 11 . . 12.

DEPOSITS

Name Countzy Name Country

Bahia Kino MXCO lahey USMT Brown USMT langsjokullen SWDN Corral Gulch USMT Leu USMT Diamond Cove CNNF Mejdasen SWDN El Novillo USMX Palmyra ·USVA Freeman Lake USID Petty Creek USMT Getberget SWDN Quartz Creek USMT Haines . Point USMT Ranaka BOTS La Scie CNNF Veta Grande USNV Lac Bouchette CNQU West Beach CNNB

17

~ C/)

~ ~ ~

~ 0 z 0

~ 0 ~

~

QUARIZVEIN

0.7

0.6

0.5

0.4

0.0~--~~--~--._ ____ _.~----------~----~--~~--~----~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100

MILLION METRIC TONS

Figure 1·1. Tonnage model for quartz in veins and pegmatltes.

18

400 1,600

~ C/l 0 ~ r:tl 0 rx. 0 z 0

~ ~

~

7 L

QUARTZ VEIN

1.0

0.7

0.6

0.5

0.4

0 .. 3

94. 0.0 '--_ ___._ __ _._ __ ....___ _ __._ __ _._ __ ....___ _ __._ __ ........_ __ ..L..--1--....I..Jl

0 10 20 30 40 50 60 70 80

GRADE IN PERCENT Si02

Figure 12. Grade model for quartz in veins and pegmatltes.

19

90 100

ss.=.J 99.

Modell8g

GRADE AND TONNAGE MODEL OF WOLLASTONITE SKARNS

By G .J. Orris

There is signjficant correlation between grade and tonnage in this model (r = - 0 .581). The grade distribution for this model is normal, not lognormal. See figs. 13, 14.

DEPOSITS


Deershead USNY Mineral Hill CNBC Del oro CNON Motueka NZLD Ethiudna AUSA Mouth Kopaonik YUGO Fox Knoll USNY Mt. Grove CNON Garies SAFR· Nakpai USSR Kimmerica GREC Oak Hill USNY Lapeenranta FNLD Puumala FNLD Lewis USNY Sandy Bay NZLD Limestone Creek AUTS San Martin-Lolkidongai KNYA South Body MXCO Mann ora CNON Sechelt CNBC

20

WOLlASTONITE SKARN 1.0

~ (/)

0.7

0 c.. ~ 0

0.6

~ 0 z 0.5

0 § 0 0.4 c..

~

0.0~--~-----L--~~~--~--~----~~--~----~--~~--~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

. Figure 13. Tonnage model for wollastonite skarns.

21

"1.0

0.9

'.: 0.8

~ 0.7

rJ)

0 0.. 0.6 w 0 rz.. ~- 0.5 z 0

~ 0.4

~

0.1

10

WOLLASTONITE SKARN

20 30 40 50 60 70 90 100

GRADE IN PERCENT WOLLASTONITE

-Figure 14. Grade model for wollastonite skarns.

22

Model 18k.

GRADE AND TONNAGE MODEL OF AMORPHOUS GRAPHITE

By James D. Bliss and David M. Sutphin

COMMENT: Classification of deposits into amorphous and disseminated flake

is not always clear and this may lead to some deposits being misclassifi.ed

(also see disseminated flake graphite) . Amorphous-graphite deposits have

been mined using mechanized and hand methods. In the latter case. the

grade and tonnage reported may be for the hand-sorted ore. This can result

in higher grades and lower tonnages then if the mines were worked

mechanically. The mix of mining methods probably accounts for some of the .

irregularities see in the distribution of data points in the model. See Sutphin

and Bliss ( 1990) for a comparison between amorphous and disseminated flake

graphite deposit types. See figs. 15, 16.

DEPOSITS

Name Country Name COuntry

Amakaze JAPN Mutale SAFR Asahina JAPN Nippon JAPN Bukovik Mt. YUGO Noginskoje USSR Chinoya JAPN Ohara JAPN Chubang SKOR Pail eng TIWN Collinsville AUQL Sanya-Wolmyong SKOR East Heilongjiang CINA Shirogahara JAPN Hanaki JAPN Sogung SKOR Hatakedani JAPN Takase JAPN Kaerim SKOR Takimoto JAPN Kanekawa JAPN Tonic hi MXCO Kureyka USSR Trabajo y Fe MXCO Kurosawa JAPN Tsutsu JAPN Lourdes MXCO Tung Shan CINA Mount Bauple AUQL Undereliffe Mountain AUNS Mtubatuba SAFR

23

CJ)

c CJ)

0 0... w . 0 u.. 0 z 0 t-a: 0 0... 0 a: 0...

AMORPHOUS GRAPHITE ·

1.0 0

n =31 0

0.8 0

0

0

0.7 0

0

0

0.6 0

0.5

0.4

0.3

0

0 0.0 ~-__. ________ _..... __ _._ ___ :-'-__ ....._ _ __...__'"'--£ __ __._ __ __,

0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100

HUNDRED THOUSAND METRIC TONS

Figure 15. Tonnage model for amorphous graphite (modified from Sutphin and Bliss, 1990).

24

400 1,600

AMORPHOUS GRAPHITE

0 n = 31

~ C/'J

0.7

0 P.,. · til ··0.6 0 ~ 0 z 0.5

0 § 0 p..

0.4

@ p..

0.3

0

0

0.0~--~---+~----~----~~~----~----~--~~--~----~ 0 10 20 30 40 50 60 70 80

CARBON GRADE IN PERCENT'

Figure 16. Grade model for amorphous graphite (modified from Sutphin and Bliss, 1990) .

25

90 100

Model 25m

GRADE AND TONNAGE MODEL·OF FUMAROLIC SULFUR

By Keith Long

There is no significant correlation between grade and tonnage in this model. See figs . 17. 18.

DEPOSITS

Name Countiy Name Country

Abra de Chutinza CILE Leviathan USNV Aucanquilcha CILE Luz Marina BLVA Cerro Bayo AGTN Ocana BLVA Cerro Orero AGTN Ocana CILE Chocosuela I CORI Ollague - Santa Rosa CILE Chocosuela II CORI Piedra Parada CILE Coquimbo CILE Polan CILE Crater Group USCA Purace CLBA Dos Conos AGTN Rio Grande AGTN El Desierto BLVA Rosario CILE El Portal - Cabana BLVA Rosario del Rey BLVA El Tatlo Este CILE Saciel CILE Golovnin USSR Salar de Azufrera CILE Gongora CORI San Pablo de Napa BLVA Hilda Mary AGTN Sillayhuay BLVA Huallatlre CILE Sillillica CILE Irruputuncu CILE Tacora CILE Ishizu JAPN. Tahapaca CILE Juan de la Vega CILE Takinosawa JAPN Julia AGTN Tocarauri CILE Kengtzeping TIWN Volcan Overo AGTN La Fortuna CORI Volcan Viejo CORI

26

Fumarolic Sulfur

~ 0.7

U) 0 ~ C:z:l

0.6 Q

~· t

~ 0 0.5 z 0 § 0 ~

0.4

0 g:

1.6 6.3 25 100 400 1,600

MILLION TONNES

Figure 17. Tonnage model for fumarolic sulfur.

27

Fumarolic Sulfur

~ · 0.7

rJ) 0 ~ ~

0.6 0 ~ 0 ' 0.5 z 0 § 0.4 0 ~

~ 0.. 0.3

GRADE IN PERCENT S

Figure 18. Grade model for fumarolic sulfur.

28

Model26b

GRADE AND TONNAGE MODEL OF FLUORITE VEINS.

By G.J. Orris

This model does not include deposits with a significant barite component. There is no significant correlation between grade and tonnage in this model. See figs. 19, . 20.

DEPOSITS

Name Countiy Name Counby

Achemeche MRCO Jebel Tirremi MRCO Argentelle FRNC Le Barlet FRNC Baton-Whangapeka NZLD Longstone Edge-Buffalo SAFR Sallet Hole UKEN Canxixe MZMB Macossa MZMB Chioco-Djanguire MZMB Muscadroxiu-Genna Director Mine CNNF Tres Montis ITLY El Hamman MRCO Okorusu-Marburg NAMB Escarro FRNC Osor SPAN Fission (Richardson) CNON Pakozd HUNG Great Eagle USNM Sierra du Lujar SPAN Hlabisa SAFR White Eagle USNM Huckleberry Mine USNM Zwartkloof SAFR Jebel Semeih SUDN

29

FLUORITE VEINS

n = 25

~ (/) 0

0.7

~ fil 0

0.6

~ 0 0.5 z 0 § 0

0.4

~

~ ~ 0.3

0 .0~--~~--~~--_. ____ ~_.--~----._~--~--~~--~----~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

.... Figure 19. Tonnage model for fluorite veins .

30

FLUORITE VEINS

n = 25 .

0.7

~ C/)

0 0.6 c.. ril Q ~ 0.5 0 z 0 § 0 c..

0.4

~ 0.3

0.2

0.0~--~----~~--~----~~~----~~~~----~--~~--~ 0 10 20 30 40 50 60 70 80 90 100

FLUORITE GRADE IN PERCENT CAF2

Figure 20. Grade model for fluorite veins.

31

Model27e

GRADE AND TONNAGE MODEL OF BARITE VEINS

By G.J. Orris ·

There is no significant correlation between grade and tonnage in this model. The grade distribution for this model reflects extreme economic bias towards high grade deposits. See figs. 21, 22.

DEPOSITS


Asht Mostec MXCO Madam Howard Plain AUTS Affensou . ALGR Madsen Mine USWA Barite Mountain CNYT Mata :MRCO Bear Mine USNV McKeller CNON Beulah AUTS Montega (Mont 'Ega) ITLY Bogus?.ow PLND Mouzai les Minesa ALGR Cliefden Springs AUNS Noarlunga AUSA Cobargo AUNS Oraparinna AUSA ·Collier Cove CNNF Palestro Narrows ALGR Cranbrook AUWA Pemathy Lagoon AUSA Darreh IRAN Porres FRNC Dorchester CNNB Premier Langmuir · CNON Gouraya ALGR Sangilyn AFGH Hamiz Dam ALGR St. Fabien (Roy-Ross) CNQU Ibitlara BRZL Tarhwacht Mine MRCQ Inverway AUNT Taza (Tarza) MRCO Jebel Ighoud MRCO Wildcat USNV Keddara/Palestro ALGR Zelmou MRCO La can FRNC Zouggara ALGR Les Porres FRNC

. 32

BARITE VEINS

n = 39

0.9 0

0.8

~ 0.7

C/J 0 o.c 0.6 Cl:l 0 ~ 0 0.5 z 0

0 § 0.4 0 0 0 o.c 0

~ o.c 0.3

. 0.2

0.1

0.004 0.11 0.0 L....-----'----'--L----'-------......__ __ ..__...._____.~...-..,_--~, __ ,_L___;_ _ __,

0.004 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400

MILLION TONNES

Figure 21 . Tonn~ge model for barite veiris.

33

BARITE VEINS

1.0

. \

~ 0.7

ffl 0 &l 0.6

Q

~ 0 0.5 z 0 § 0 0-c g 0-c

60. 91. 98.

BARITE GRADE IN PERCENT BaS04

Figure 22. Grade model for barite veins.

34

GRADE AND TONNAGE MODEL OF· SANDSTONE/QUARTZITE SILICA

By G.J. Orris

Model30e

There is no significant correlation between grade and tonnage in this . model. Iron oxide and alumina contents may restrict the usage of the silica derived from these deposits. See figs . 23, 24. 25, 26.

DEPOSITS


Aorere NZLD Joyceville CNON Burchill Road . CNNB Kati-Takalyar AFGH Chashma-1-Shafa AFGH Landsllp Hill NZLD Chegoggin Quartzite CNNS Leeds Metals CNQU Chesnaye Lake CNQU Leven AUTS

·Delmas SAFR Lobatse BOTS Dicks Point CNNF Nantucket Island CNNB Ditsotswane Hill BOTS Paddle CNON Dun ville CNNF Petit Lac Malbaie CNQU Fortune CNNF Plumbago Creek USWY Grey River - Gulch Reefton NZLD

Cove CNNF St. Vianney CNQU Hajigak AFGH Unidentified Quartzite Hastings . AFGH Deposit CNIA Jabal Burmah SAAR White Head Island CNNB

35

0.9

0.8

~ .0.7

en

~ 0.6 0 ~ 0 0.5 z 0

~ 0.4

0..

~ 0..

0.1

SANDSTONE/QUARTZITE SILICA

0.0~--~----~----~--~~--~--~~----~~--~----~--~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

' Figure 23. Tonnage model for sandstone/ quartzite silica.

36


~ 0.7

{/)

0 ~ ril

0.6

Q

~ 0 0.5

z 0 § 0.4 0 ~

~ 0.3

0.2

0.1

87. 97.

0.0~--~----~----~--~----~----~--~----~--~~--~ 0 10 20 30 40 50 60 70 80 90 100

GRADE IN PERCENT Si02 99._j

. Figure 24. Grade model for sandstone/quartzite silica.

37


1.0

n = 28

~ r -C/)

0 0.6 0.. ~ 0 ~ 0 0.5

z 0 § 0 0..

0.4

~ · 0.3

0.2

0.18 0.32 0.56 1.0 3.2 5.6 10.0

IRON CONTENf IN PERCENT Fe203

Figure 25. Iron model for sandstone/ quartzite silica.

38


. 1.0

n = 28

~ rJ)

0.7

0 0.6 p..

~ 0 ~ 0 0.5

z 0 § 0 p..

0.4

~ 0.3 p..

0 .0~--~-----L----~----~--~----~----~~--~--~~--~ 0.032 0.056 0.1 0:18 0.32 . 0.56 1.0 1.8 3.2 5.6 10.0

ALUMINUM CONTENT IN PERCENT Al203

Figure 26. Alumina model for sandstone/quartzite silica.

39

Model3lb

GRADE AND TONNAGE MODEL OF BEDDED BARITE

By G.J. Orris

There is · no significant correlation between grade and tonnage in this model. This model is an updated version of a previously published model (Orris, 1986b) . See figs. 27, 28.

DEPOSITS


Balleynoe Homes take CNBC (Silvermines) IRLD Kempfield AUNS

Ban Thimontha .THLD Khuzdar PKTN Barite (Moose) CNYT La Minita MXCO Barite'Mountain CNYT Magnet Cove USAR Barite Valley SWAZ. Mangampeta North INDA BawHinKhao THLD Mangampeta South INDA. Big Stubby AUWA Mazatan MXCO Brookfield CNNS Meggen GRMY CamamuBay BRZL Mel CNIT Castle Island USAK Mountain Springs USNV Cathy (Walt) CNYT Nimiuktuk USAK . Chang do NKOR Phu Mai Tong THLD Cirque Cl'4"BC Rammelsberg GRMY Cobachi :MXCO Rein CNIT Democrat USCA Savercool USCA Dodge ZIMB Schoonaard SAFR El Portal USCA Snake Mountain USNV Farenjal AFGH Tea CNIT Foss-Ben Eagach UKSL Uribe USWA Greys tone USNV Walton CNNS Gurrunda· AUNS Weekaroo AUSA

40

BEDDED BARITE

1.0

n = 43

~ 0.7

(/)

0 a.. 0.6 w 0 ~ 0 {).5

0 z 0 0 0

§ 0 0.4 0 0 0 a.. 0 @ 0 a.. 0.3

400 1,600

MILLION TONNES

Figure 27. Tonnage model for bedded barite.

41

BEDDED BARITE

0.9

0.8

~ 0.7

Cl) 0 ~ 0.6 fil Q

~ 0 0.5

z 0 § 0.4

0 ~

~ ~ 0.3

0.2

0.1

0 10 20 30 40 50 60 70 80 90 100

BARITE GRADE IN PERCENT

Figure 28. Grade model for bedded barite.

42

.!i

Model 3lk

PRELIMINARY CONTAINED MATERIAL MODEL OF SEDIMENTARY KAOLIN

By G .J. Orris

Grade information was insufficient for a grade model. This model is for contained kaolin. See fig. 29.

DEPOSITS


Bovill USID Onakawana Lignite Boralesgamuwa SRIL Area CNON Bratunac YUGO Ploemeur-D'Arvor FRNC Escalera VENE Ploemeur-Morbihan FRNC Etsubora JAPN Pugu Hills TNZN Iwate Hine JAPN Rio Capim BRZL Jart BRZL Stanford Clay Deposit USID Kalabsha EGPT Wadi Sallah SAAR Khushaym Radi SAAR Wankie ZIMB Maomtng CINA Wilkinson Kaolin USGA Meudon FRNC Xuzhou CINA

43

~ rf) ·o 0.. ~ 0 ~ 0 z 0 § 0 0..

~

SEDIMENTARY KAOLIN

1.0

0.7

0.6

0.5

0.4

0.3

0.0~~~----~-----L----~----~----~--L-L---~~--~----~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,000

MILLION TONNES

Figure 29. Contained kaolin model for · sedimentary kaolin deposits.

44

•'?--

Model32g

PRELIMINARY CONTAINED MATERIAL MODEL OF LIMESTONE

By G .J. Orris

This is a contained material model and no distinction is made as to the type of end usage. Insufficient grade and chemical data were available for further modeling. See fig. 30.

DEPOSITS


Amador Camacho MXCO Nkalagu NIGR Bamyon-1 AFGH Onigbolo BENN Blue Rocks AUNS Pilkington AUQU Borenore AUNS Rosebrook AUNS Cabano CNQU San Pedro MXCO Cal-White USCA Santa Ana MXCO Ewekoro NIGR Sormony CNNB Glencoe CNNS Tin Hrassan UVOL Kingsdale AUNS Umm a1 Ghirban SAAR Lower Cove Bay CNNF Wazo Hill TNZN Mount Frome AUNS White Hope USCA Mountain Springs USCA Yacuses BLVA

45

0.9

0.8

~ 0.7

en ~ fil Q

~ ... 0.5 z 0

§ 0.4

~

~ 0.3

LIMESTONE

0.1 0.4 100 400 1,600

MILLION TONNES

Figure 30. Contained material model for limestone.

46

Model35a.l

PRELIMINARY GRADE AND TONNAGE MODEL OF BEDDED CELESTITE

By G .J. Orris

). There-is no significant correlation between grade and tonnage in this model. See figs. 31, 32.

DEPOSITS

Name Countzy Name Country

Black Butte USAZ Nuevo Leon MXCO Kaiser (Loch Quesseir EGPT

Lomond, Enon) CNNS San Agustin MXCO Kunduz (Qonduz) AFGH Tangt-Murch AFGH Montevive SPAN Unnamed QATR Montezuma Claims USAZ Nakhjir-Dashte Kavir

(Molkabad) IRAN

47

CELESTITE

~ 0.7

r/) 0 c.. P:l 0.6

0 ~ 0 0.5 z 0 § 0.4 0 c.. ~ c.. 0.3

o.o~--~----~----~----.__.~-----4----~----~--~~--~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

Figure 31. Tonnage model for marine bedded celestite.

48

1.0

. 0.9

0.8

~ 0.7

rJ) 0 ~ 0.6 Q

~ 0 ~· 0.5 z 0

§ 0.4

~ @ Cl.4 0.3

0.2

0.1

CELESTfl'E

0 .0~--~----~----~----~~~----~----~----~--~--~~ 0 10 20 30 . 40 50 60 70 80 90 100

CELESTITE GRADE IN ·PERCENT SrS04

Figure 32. Grade model for marine bedded celestite.

49

Model35a.2

GRADE AND TONNAGE MODEL OF POTASH-BEARING BEDDED SALT

ByG.J. Onis

Some of the deposits in this model consist of multiple mineralized horizons which may be hundreds of meters apart stratigraphically. There is no significant correlation between grade and tonnage in this model. See figs. 33. 34.

DEPOSITS


Alsace FRNC Uobregat SPAN Canamex CNMN Malargue AGTN Cardona SPAN McAuley - St. Lazare CNMN Carlsbad USNM Plumweseep CNNB Colonsay (Central Rocanville CNSK

Canada) CNSK Rosar.io do Catete BRZL Denison-Potacan CNNB Russell CNMN Esterhazy CNSK Salt Springs CNNB Holle CNGO Zielitz EGER

50

~ 0.7

C/J 0 0.. 0.6 rxl Q

ex.. 0 "'().5 z 0 § 0.4 0 0..

~ 0.3

POTASH-BEARING BEDDED SALT

n = 17

0

0.4 400 1,600 6,300

MILLION TONNES

Figure 33. Tonnage model for potash-bearing bedded salt.

51

~ 0.7

(/')

0 &s 0.6

0 ~ 0 0.5 z 0

~ 0.4 0 ~

~ ~ 0.3

POTASH-BEARING BEDDED SALT

0

0

0

0

0

0

POTASH GRADE IN PERCENr K20

Figure 34. Grade model for potash-bearing bedded salt.

52

n = 17

Model35a.5

PRELIMINARY GRADE ·AND TONNAGE MODELS OF MARINE BEDDED GYPSUM

By G.J . Orris

) There is no significant .correlation between grade and tonnage in this . model. This model is a miX of districts/areas and single deposits. The

districts/areas may contain more than one deposit. See figs. 35. 36.

DEPOSITS


~laineFm- Pouillon FRNC Southwest Oklahoma USOK Suria Malableh SOML

Cloud Chief USOK Tabernas SPAN F1atBay CNNF Tavemy FRNC Fort McMurray Weatherford-Clinton

(Athabasca) CNAL District USOK Glangevin EIRE White Mesa USMX Peace Point CNAL Windermere CNBC Pen chard FRNC

53

MARINE BEDDED GYPSUM

~ 0.7

Cl)

0 ~ 0.6 C::;l 0 ~ 0 0.5 z 0 § 0.4 0 ~

@ ~

0.0~--~----~----~----~~~--~~--~~----~--~~--~ 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600 6,300 25,000

MILLION TONNES

Figure 35. Tonnage model for marine gypsum . .

·.

1.0

0.9

0.6

~ 0.7

C/)

~ rxl 0.6 ~

~ 0 0.5 z ., 0 § ~ ~ ~

0.1

MARINE BEDDED GYPSUM

0.0~--~----~----~----~--~----~----~----~--~~~~ 0 100

GRADE IN PERCENT GYPSUM

Figure 36. Grade model for marine gypsum.

55

Model35b.3

PRELIMINARY GRADE AND TONNAGE MODEL OF LACUSTRINE BORATES .

By G.J. Onis

In addition to grade and tonnage mod.els (figs. 37, 38), the distribution of the colemanite content of the borate mineralization is shown in figure 39. There is no significant correlation between borate grade and tonnage in this model, nor is there a significant correlation between percent borate and percent colemanite. However, there is a strong negative correlation (r = -0.654) between tonnage and percent of borate mineralization composed of colemanite.

DEPOSITS


Bigadic TRKY Maria* USCA Billie USCA Monte Blanco USCA Boraxo USCA Played Out USCA Callville Wash Rho (Kramer Junction)

{Anniversary Mine) USNV USCA Corkscrew USCA Sigma USCA DeB ely USCA Terry USCA Ernet TRKY Upper Biddy · Gerstley I USCA McCarthy USCA Gerstley II USCA Widow No. 3 (New Grand View USCA Widow)• USCA In yo USCA Widow No. 7 {Old Lizzy V. Oakley USCA Widow)* USCA Lower Biddy

McCarthy USCA

56

lACUSTRINE BORA.TES

0.9

'0.8

~ 0.7

en g lo'oo4 0.6 0

~ 0.5 z · 0 § ~ 0.4

0 g: 0.3

0.2

0.1

0.04

0.1 400 1,600

MILLION TONNES

· Figure 37. Tonnage model for lacustrine borates.

57

LACUSTRINE BORATES

n = 23

~ 0.7

Cf)

~ ~ 0.6 0 ~ 0 0.5 z 0 §

0.4 0 ~

~ ~ 0.3

GRADE IN PERCENT B205

Figure 38. Tonnage model for lacustrine borates.

58

LACUSTRINE BORATES

~ 0.7

rn ~ ~

0.6

Q

~ 0 z 0 § ~ ~ p..

PERCENT OF MINERALIZATION COMPOSED OF COLEMANITE

Figure 39. Percent of borate mineralization as colemanite.

59

Model35b.9

PRELIMINARY GRADE AND TONNAGE MODELS OF LACUSTRINE GYPSUM

By G.J. Orris

There is no significant correlation between grade and tonnage in this model. See figs . 40, 4L

DEPOSITS

Name

Apex Boologooro Station Central Wash

· Gemshok Hollow Lake MacDonnell Marion Lake Parcoola Snow Lake

Countzy

USNV AUWA USAZ SAFR AUSA AUSA AUSA AUSA

60

Name

Spider Lake Streaky Bay Tromen-Auguilc6 Vaca Muerta Yarra Yarra Lakes Yzerfontein

Countiy ·

AUSA AUSA AGTN AGTN AUWA SAFR

LACUSTRINE GYPSUM

~ 0.7

(/') 0 ~ r:q 0

0.6

~ 0 0.5 z 0 §

0.4 0 A.c 0 15: 0.3

0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

Figure 40. Tonnage model for lacustrine gypsum.

61

LACUSTRINE GYPSUM

1.0

~ 0.7

(j) 0 p.. ril Cl

0.6

~ 0.5 z 0 § 0.4 0 p..

@ p.. 0.3

GYPSUM GRADE IN PERCENT

Figure 41 . Grade model for lacustrine gypsum.

62

Model35b.21

CONSTITUENT MODELS OF SODIUM CARBONATE (SULFATE, CHLORIDE) BRINES

By G.J. Orris

There is significant correlation between the solutes in this model. SOdium carbonate is correlated with sodium sulfate (r = 0.683), sodium · carbonate with sodium chloride (r = 0. 704). and sodium sulfate with · sodium chloride (r = 0.863). See figs. 42-44.

DEPOSITS ·

Name Country Name. Country

Black Lake USCA Lake van TRKY Borax Lake USCA Lonar Lake ETHP Hail~.r (Hailaeh) CINA Mono Lake USCA Harney Lake USOR Omak Lake USOR Jess Lake USNB Pretoria Salt Pan SAFR Lago Texcoco MXCO Soap Lake USOR Lake Abert USOR Sua Pan BOTS Lake Magadi KNYA Summer Lake USOR

63

Soditrm carbonate (sulfate) brines

n = 16

~ rJ)

0 .7

0 o..c Cil 0.6 Q

~ 0 0.5 z 0 § 0

0.4

flc

~

0.0 '-----'---.......L..-----I....L....--"'-f-----'--............ -'---......._--"'-------'....._ _ __. 0.4 1.0 2.5 6.3 16 40 100 250 630 1600 4000

SODIUM CARBONATE GRADE IN GRAMS PER LITER Na2C03

Figure 42. Solute model for sodium carbonate brines.

64

Sodium carbonate (sulfate) brines

n • 16

0.9

0.8

~ 0.7

fJ) 0 ~ ril 0.6 0 ~ 0 0.5 z 0 §

0.4 0 ~

·~ ~ 0.3

0.2

0.1

0.0~--~--~~----~----~--~----~----~----~--~~--~ 0.4 1.0 2.5 6.3 16 40 100 . 250 630 1000 4000

SODIUM SULFATE GRADE IN GRAMS PER LITER OF Na2S04

Figure 43. Solute model for sodium carbonate biines . .

65

Sodium carbonate (sulfate) brines . -

n = 16

~ 0.7

en 0

0.6 0.. P::l Q

rz.. 0 0.5

z 0 § 0.4 0 0..

@ 0.. 0.3

0.0~--~~--~----~--~~--~----~~--~----._--~~--~

0.4 1.0 2.5 6.3 16 40 100 250 630 1600 4000

SODIUM CHLORlDE GRADE IN GRAMS PER LITER NaCl

Figure 44. Solute model for sodium carbonate brines.

66

GRADE AND TONNAGE MODEL OF DISSEMINATED FLAKE GRAPHITE·

By James D. BUss and David M. Sutphin

Model37f

Disseminated flake graphite deposits have been mineduusing predominantly mechanized methods. Classification of deposits into amorphous and . disseminated is not always clear and this may lead to some deposits being misclassified (also see amorphous graphite). There is no significant correlation between grade and tonnage in this modeL This model has been prebiously published in a non-USGS publication (Sutphin and Bliss, 1990). See Sutphin and Bliss ( 1990) for a comparison between amorphous and

·disseminated flake graphite deposit types. See figs. 45, 46.

DEPOSITS

Name Country Name Counby

Ambatornitamba :MDGS Girard USPA Amo. JAPN Globe USCA Andasifahatelo :MDGS Graphex CNQU Ashidani JAPN Gumbu SAFR Azad Kashmir PKTN Hainan Island CINA Bell Graphite CNQU Harcourt CNON Black Donald CNON Ito tone MZMB Bosiljgrad YUGO Kanziku KNYA Buryat USSR Kashmiri PKTN Cal Graphite CNON Katsuno JAPN Canadian Graphite CNQU Kingston CNON Carter Lake USCA Kirkham CNON Ceylon USAL Kongodo JAPN Cheong-pyong -(# 1 04) SKOR Konstantin CZCL .· Cheong-pyong (#33.43) SKOR Koppio AUSA ChungNam SKOR Kropfmiihl GRMY ChungPuk SKOR Kyeryong SKOR Cornell USCA Uu-Mao CINA Cup Lake CNON Lynx ZIMB Dawn 71 SAFR Madurai INDA Dun Raven CNQU _ Marovintsky MDGS Faliarano MDGS Mestry-vrch CZCL Federal Carbon USPA Mont Laurier CNQU Fermont CNQU Monte Nipacue MZMB

· Genda JAPN Munglinup River AUWA

67

Name Country Name Count:Iy

Naoi JAPN Samgong SKOR National Graphite CNON Satemua MZMB Nhanhar MZMB Shihung SKOR Njoka ZMBA Skaland Grafitrerk NRWY Notre-Dame-du-Laus CNQU Southwestern USTX Oaxaca MXCO Soyusnoye USSR Orrwell CNQU · Ta:skazgan USSR Oryu SKOR Tayginsk USSR Pasumpon- Telixtlahuaca MXCO

Muthuramalingam INDA Timmins CNON PedraAzul BRZL Todd CNON Pennsylvania Graphite USPA Tonkin-Dupont CNON Pickering Valley USPA Tsavo KNYA · Pollan Lake- Uley AUSA (Reindeer Lake) CNSK Virginia Graphite CNON Port Clarence USAK Yongwon SKOR Princeton CNON Zaval'yevsky USSR Pyontack SKOR

68

~ C/)

&: (l:l 0 ~ 0 z 0 § 0 0..

@ 0..

DISSEMINATED GRAPHITE FlAKE

1.0 0 0

0.8

0.7

0.6

0.5

0.4

0.3

0.0~--~----~~~~--~----~~~~--~~---Y----~--~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400

HUNDRED THOUSAND METRIC TONS

Figure 45. Tonnage model for disseminated graphite (modified from Sutphin and Bliss, 1990).

69

1,000

0.9

0.8

~ 0.7

CfJ 0 ~

0.6 w 0 ~ 0

0.5 z 0 §

0.4 0 0..

~ 0.3

DISSEMINATED FLAKE GRAPHITE

GRAPHI1E GRADE IN PERCENT

Figure 46. Grade model for disseminate graphite (modified from Sutphin and Bliss, 1990).

70

n .. 83

Model38h

PRELIMINARY CONTAINED MATERIAL MODEL FOR RESIDUAL KAOLIN

By G.J. Orris

There was insufficient information to construct a grade model for this deposit type. See figure 47.

DEPOSITS

Name Count:Iy Name Count.Iy

Cerro Copeyal VENE Nagai Parker PKTN Escalera VENE Palmira BLVA Eureka AGTN Sanchong SKOR Hags tad SWDN Tala-Barfek AFGH Karacevo YUGO Top ira GUYN Km 88 VENE Weipa AUQL Linden GUYN

71

Residual Kaolin

0.0 ......__-.JI __ __._ __ ..L-.1.. __ ....._ __ ........,_ __ .._ _ ____..__-'-____... __ _._ __ ___,~

0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION TONNES

Figure 4 7. Contained material model for residual kaolin.

72

' .....

Model39d

GRADEt VOLUME, AND DEPOSIT-SPECIFIC MODELS OF DIAMOND PLACERS

By James D. Bliss

COMMENT: In addition to size and grade, average carat size and percentage of diamonds of industrial grade are needed to characterize diamond placers. Most deposits are alluvial but several are residual placers over kimberlite pipes. Beach placers are excluded. Given the type of data available, data on workings within 1.5 km were considered to be a single deposit. Several deposits are large in area with workings of unknown spacing. Deposits must have diamond grade and volume to be included m. those models. However. reporting on average carat size and percentage of diamonds of industrial quality was less frequently available and all reported values for these characteristics were used in the models whether or not associated grade and volume data were available. The percent of diamonds of industrial quality is correlated with deposit size (r = 0.93, n = 7) if the Prairie Creek residual placer is excluded from the analysis. Other commodities known to have been

· produced from diamond placers, but not modeled, include Au, PGE, Ta205, and other types of gemstones. See figs. 48-51.

DEPOSITS

Name Count:Iy Name Count:Iy ·

Acorn Security INDO Limestone Creek AUWA Aredor GNEA Lower Smoke Creek AUWA BauleBasin GNEA Lucapa-Andrada-Bingara Field AUNS Cuango River ANGL Birim River GHNA Mabuki TNZN Boabab TNZN Mwamanga TNZN Bosh off TNZN Namaqualand SAFR Copeton AUNS Potaro Field GUYA CampoSampaio .BRZL Prairie Creek USAR Feijao Cru . BRZL Raw Bean BRZL Hlane SWAZ Rio Caroni VNZL Koidu Field SRLN Tejucana BRZL Kolmanskop SAFR Upper Smoke Creek AUWA Kurupung Field GUYA Vila Santa Maria BRZL

73

Diamond Placers

0 n .. 25

~ C/)

0.7

0 0... C:Q 0.6 Q

~ 0 0.5 :z: 0 § 0.4 0 0... '

~ 0... 0.3

,, 0. 0 L...----"'--__.. __ __,_ __ -'-'""---'----"------4---"L-.-----t.-----L.-------1

0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

MILLION CUBIC METERS

Figure 48. Size model for diamond placers.

74

Diamond Placers

~ r/)

0.7

~ .. 0.6 r:il 0 tz.. 0 z 0 § 0 P.c

~ · P.c

0.5

0.4

0.3

0 .0~--~-----LL---~----~----~--~L---~----~----~----~ 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100

DIAMOND GRADE IN CARATS PER CUBIC METER

400 1,600

Figure 49. Diamond grade model for placer diamonds.

75

Diamond Placers

1.0

n - 14

~ C/)

0.7

0 c..c ~ 0.6 ~

~ 0 0.5 z 0 § 0 c..c 0 ~ 0.3

0 .0 '-------'------'-1---........L.--1---L-~-.,_._ __ .....___---I,____---I __ ___.~... __ __. 0.0016 0.0063 0.025 0.1 0.4 1.6 6.3 25 100 400 1,600

AVERAGE DIAMOND SIZE IN CARATS

Figure 50. Diamond size model for placer diamonds.

76

~ (J) 0 ~ r:z:l 0 ~ 0 z 0 § 0 0..

~

DIAMOND PLACERS

1.0

n = 11

0.8

0.7

0.6

0.5

0.4

0.3

0.0 L------'----'---..___ _ __,_ __ ........... _.___..___ _ __,__.L...-......L....--.&...-.-.1~

0.1 02 0.4 0.8 1.6 3.2 6.3 13 25

DIAMONDS OF INDUSTRIAL · QUALI1Y, IN PERCENT

50 100

Figure 51. Diamond quality model for placer diamond deposits.

77

Model39i

PRELIMINARY GRADE AND TONNAGE MODELS OF SILICA SAND

By G.J . Orris .

There is no significant correlation between grade and tonnage in this model. See figs. 52, 53.

DEPOSITS


AbuDarag- Madeleine Islands upper horizon EGPT (South) CNQU

AbuDarag- Nylstroom SAFR lower horizon EGPT Parengarenga NZLD

Black River JMCA Planknek 43 KS Farm SAFR Cape Flats SAFR Plumbago Creek USWY Demerara River GYNA Red Deer River CNSK Diogenes CNNS Sandy Ground · JMCA Madeleine Islands Weferlingen GRMY

(North) CNQU

78

SILICA SAND

1.0 n = 15

0.9

0.8

~ f/l

0.7

0 ll.. 0.6 ril 0 ~ 0 0.5 z 0 0 § 0.4 0

~ 0 2: 0.3

0.2

0.1

1.3 15. 174.

MILLION· TONNES

Figure 52. Tonnage model for silica sand.

79

SILICA SAND

1.0

0.7

~ Cll

~ C:rl

0.6

Q

~ 0 0.5

z 0

~ 0.4

0 ~

~ 0.3

SILICA GRADE IN PERCENT Si02

Figure 53. Grade model for silica sand.

80

REFERENCES

Cox, D.P .. and Singer, D.A., 1986, Mineral deposit models: U.S. Geological Survey Bulletin 1693, 379 p.

Orris, G.J., i986a, Grade and tonnage model of serpentine-hosted asbestos, in Cox, D .P ., and Singer, D.A., eds., Mineral deposit models: U.S. Geological Survey Bulletin 1693, p. 46-48.

Orris, G.J., 1986b, Grade and tonnage model ofbedded barite, in Cox, D.P., and Singer, D.A, eds., Mineral deposit models: U.S. Geological Survey Bulletin 1693, p. 216-218.

Orris, G.J., and Bliss, J.D., l991. Some industrial mineral deposit models: descriptive deposit models: U.S. Geological Survey Open-File Report 91-llA, 73 p. .

Sutphin, D.M., and Bliss, J.D .• 1990, Disseminated flake graphite and amorphous graphite deposit types--an analysis using grade and tonnage models: Canadian Mining and Metallurgical Bulletin, v. 83, no. 940, p. 85-89.

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Code

AFGH AGTN ALGR ANGL AUNS AUNT AUQL AUSA AUTS AUWA ASTR BENN BLVA BOTS BRZL CILE

·CINA CIBA CNAL CNBC CNGO CNMN CNNB CNNF CNNS CNNT CNON CNQU CNSK CNYf CORI

· CZCL EGPT ETHP FNLD

· FRNC GHNA GNEA GREC GRMY GUYN

APPENDIX A:

COUNTRY CODES

Name ·

Mghanistan Argentina Algeria Angola Australia, New South Wales Australia, Northern Territory Australia, Queensland Australia, South Australia Australia, Tasmania Australia, Westem Australia Austria Beriin Bolivia Botswana Brazil Chile China Colombia Canada, Alberta Canada, British Columbia Congo Canada, Manitoba Canada, New Brunswick Canada, Newfoundland Canada; Nova Scotia Canada, Northwest Territories Canada, Ontario Canada, Quebec Canada. Saskatchewan Canada. Yukon Territory Costa Rica Czechoslovakia Egypt Ethiopia Finland France Ghana Guinea Greece Germany Guyana

82

Code

HUNG ICI.D INDA IRAN IRLD ITLY JAPN JMCA KNYA LSTO MDGS MRCO MXCO MZMB NIGR NKOR NRWY NZLD PKTN PLND QATR SAAR SAFR SKOR SOML SPAN SRIL SRLN SUDN SWAZ SWDN THLD TIWN TNZN TRKY UKSL USAL USAK USAZ USAR USCA US€0 USGA USID USIA USMT USNB

Name

Hungary Iceland India

. Iran Ireland Italy Japan Jamaica Kenya Lesotho Madagascar Morocco Mexico Mozambique Nigeria North · Korea Norway

· New Zealand Pakistan Poland Qatar Saudi Arabia South Mrica South Korea Somalia Spain Sri Lanka Sierra Leon Sudan Swaziland Sweden Thailand Taiwan Tanzania Turkey United Kingdom, Scotland United States, Alabama United States, Alaska United States, Arizona United States. Arkansas United States, California United States, Colorado United States, Georgia United States. Idaho United States, Louisiana United States. Montana United States, Nebraska

83

Code

USNC USNM USNV USNY USOK USOR USPA USSR USTN USTX USVA USVT ·uswA USWY UVOL VENE YUGO ZIMB ZIRE

··ZMBA

Name

United States, North Carolina United States, New Mexico United States, Nevada United States, New York United States, Oklahoma United States, Oregon United States, Pennsylvania formerly of the United Soviet Socialist Republics United States, Tennessee United States, Texas United States, Virginia United States, Vermont United States. Washington United States, Wyoming Upper Volta (Burkina Fasso} Venezuela formerly of Yugoslavia Zimbabwe Zaire Zambia

84

industrial minerals deposit models - usgs · are reporte.d . only when they are significant at the...

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