Mining and Sustainable Development

20th WORLD MINING CONGRESS & EXPO2005 7 – 11 NOVEMBER 2005, TEHRAN, IRAN “Mining and Sustainable Development”

20th WORLD MINING CONGRESS & EXPO2005

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Modelling of sedimentary deposits of Kaolin clays, in continental environment: application to the Charentes deposits, France Jean-Pierre Rolley Mohammad Koneshloo Marc Vinches CMGD, Ecole des Mines d'Alès,France 20th WORLD MINING CONGRESS & EXPO2005

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Presentation Plan • Introduction The world of Kaolin

Geographic and geological setting of the deposit

• Traditional Method Deposit  product • The Analysis of Data & Situation • Discussion & Conclusion


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What is a kaolin? kaolin : Rock composed of kaolinites group minerals Kaolinite, Dickite, Nacrite, and Halloysite

A 7 °A: Kaolinite

Alteration Aluminosilicates

A 10 °A:

Clays

Illite

Hydrothermal Process

A 14 °A: A pseudo-Sheets and Fiberous Facies 20th WORLD MINING CONGRESS & EXPO2005

Chlorites Smectites

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Rainin g

Marine sedimentation

Continental sedimentatio n

Hydro20th WORLD MINING CONGRESS & EXPO2005

Therma l

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KAOLINITIQUE BASSIN of CHARENTES In the north of

Aquitain Bassin « terres blanches » means « white soil »

Various properties for application in different industries. 20th WORLD MINING CONGRESS & EXPO2005

Ref: www.ign.fr

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Geological Setting

Geological map of the Charente Basin area. The kaolin quarries are located where the sand overburden does not exceed 30m. 20th WORLD MINING CONGRESS & EXPO2005

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Geological sections showing the distribution of the kaolinite layers


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AGS MINERAUX • •

Deposit



European leader in the production of calcined kaolin Key Numbers 2002 Annual turn-over:43 million Euros Annual production :743 KT Work force :305 Persons

Extraction



Crushing 

Calcination

and grinding 20th WORLD MINING CONGRESS & EXPO2005

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Source of data : Drilling

Core Recuperation

Choice of clay parts

Large Grid

Small Grid

Creation of Data Base Definition of parametres to be analysed

Choice of the blocks based on core drilling data

Preparation of samples for analysis Survey of variations on the site Analysis of Samples 20th WORLD MINING CONGRESS & EXPO2005

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To Be OR NOT TO BE, Representativity ? 20th WORLD MINING CONGRESS & EXPO2005

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Estimation • Traditional Methods • Geostatistical Methods • Recently Developed Methods Neural Networks Simulation, Fuzzy logic

•

Combination of these Methods

Geostatistics at a glance: Variogram; Kriging; Weighted Average


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Directional Variograms of Accumulation of Al2O3 MD Deposit

Semivariogramme

30 25

-45

20

-75

15

-15

10

15

5

45

0 0

20

40


60

75

m 80 14

Sources of Error for an Estimation • • • • •

The Important Factors : Loss of information: X ---X X X ? X X ? ? ? ? Geological Incertitude : x y x y yy Insufficient knowledge to interpret the phenomena Discontinuity , interruption, different phenomena A B C D E f w t w e K L v N O P Q R S T 123 • Noise

MMMMMMM

MMMMMMM


MMMMM MMM

M

M

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ANALYSIS OF THE QUALITY OF DATA • Lack of information • Problem of regularization • Discontinuity, interruption and peculiar phenomena • Insufficient knowledge to interpret the phenomena • Bimodal Population • Different types of criteria 20th WORLD MINING CONGRESS & EXPO2005

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Continental sedimentation Complexity in form and pattern


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Discontinuity

Distance = 6 m Nom Snd S3.01750

Ptoit

Y

407315

Fac 17,5 18 18,5 19 19,5 20 20,5 21 21,5 22 22,5 23 23,5 24 24,5 25 25,5 26 26,5 27 27,5 28 28,5 29 29,5 30 30,5 31 31,5 32 32,5 33

344337

Pf 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82

Z

Nom Snd 119 S5.05298

Al2O3

Ptoit

X

Y

407320

Fac 17,5 18 18,5 19 19,5 20 20,5 21 21,5 22 22,5 23 23,5 24 24,5 25 25,5 26 26,5 27 27,5 28 28,5 29 29,5 30 30,5 31 31,5 32 32,5 33

85 85 11 11 11 11 11 11 13 13 13 13 13 13 13 13 13 13 15 15 15 15 13 13 13 13 13 13 13 13 13 13

344340

Z 119

Pf

Al2O3

11,25 11,25 11,25 11,59 11,59 11,59 11,46 11,46 11,78 11,78 11,78 11,78 11,67 11,67 11,67 11,67 11,4 11,4 11,4 11,4 11,18 11,18 11,18 11,18 10,77 10,77 10,77 10,63 10,63 10,63

36,3 36,3 36,3 36,83 36,83 36,83 36,37 36,37 37,53 37,53 37,53 37,53 36,82 36,82 36,82 36,82 36,8 36,8 36,8 36,8 36,61 36,61 36,61 36,61 34,75 34,75 34,75 35,04 35,04 35,04

Minimum 14.5 m of the clay series

0 ??

X

Discontinuity of the properties : Brutal changes of properties cause some problems for mathematical estimation methods, because they tend to smooth the results


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Bimodal Population of K2O 200 160

160

134

120 89

80

146

113 115 81

54

90 68 66 63

82

76

39

40

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K2O Grade in % 20th WORLD MINING CONGRESS & EXPO2005

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1, 6

1, 5

1, 4

1, 3

1, 2

1, 1

1

0, 9

0, 8

0, 7

0, 6

0, 5

0, 4

0, 3

0, 2

0

0, 1

Number of Regularized samples

[< 0,6] et [> 0,6]; Chez MD

Natural Phenoma are Frameworks of Estimation • The geological situation is complex: The differents geological processes can produce a mix of statistical populations in space and time. • Loss of information can hide the logical relationship between data, thus the actual relation will be interpreted as a random or hasardous relation. • Obviously, the scale of observation (sampling grid) must be adapted to the scale of the essential phenomena. • After the sedimentation process disturbs the original relation between data. 20th WORLD MINING CONGRESS & EXPO2005

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The envisaged solutions • Working in the new space of geometry • Taking into account the genesis of the history of the deposits • Investigate the relation between variables


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γ(h) 20

200

15

150

10 5

Comparison of the calculated variograms in a Cartesian system (Plan 50 m) in the NE part of BR deposit for Al2O3 (top), and on the projected values of the surface of sedimentation on a plane. (parameters of variograms, direction: 60° and tolerance: 15°)

Semi Var

100

Pair

50

0

Pair

In the Cartesian system

0 30

60

90

120

150

180

210

240

h(m)

γ(h) 30

On the surface of sedimentation

25

250 200

20

150

15 100

10 Semi Var Pair

5 0 30

60

50 0

90 120 150 180 210 240 h(m)


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Pair

Non Cartesian system

Genetic difference 50

SW

40 30

NE

20 10

60

58

56

More

Al203(%)

54

52

50

48

46

44

0

42

Relative frequency(%)

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Relative frequency of Al2O3 grade in hard kaolin of the second series in the north eastern part of BR deposit and the south western part of the deposit which contains a canalized type sediment 20th WORLD MINING CONGRESS & EXPO2005

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Statistical comparison Deposit parameter LOI Al2O3 TiO2 Fe2O3 Na2O K2O CaO MgO SiO2 P2O5

BR Ave 13.6 42.5 1.37 1.38 0.07 0.70 0.15 0.12 53.2 0.06

St Dev 1.8 4.3 0.40 0.87 0.04 0.47 0.06 0.07 3.8 0.03

MD Ave St Dev 12.4 1.5 38.8 4.0 1.45 0.45 1.47 0.78 0.06 0.03 0.81 0.40 0.17 0.04 0.14 0.07 56.8 3.7 0.04 0.03

SG Ave 11.4 36.5 1.50 1.47 0.06 1.17 0.07 0.19 58.6 0.06


BC St Dev 0.9 2.5 0.14 0.25 0.03 0.28 0.03 0.04 2.4 0.02

Ave 11.9 37.6 1.77 1.48 0.07 0.73 0.07 0.14 57.5 0.06

St Dev 0.8 2.7 0.46 0.60 0.03 0.31 0.04 0.04 3.6 0.02

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Sum of frequency in each class is 100 60 50 40 30 20 10

Sandy Clay

Semi grassy with grains

Semi grassy

Grassy with grain

>= 50

48-50

46-48

44-46

42-44

40-42

38-40

36-38

34-36

32-34

30-32

28-30

>28

0

Grassy

Hard Kaolin

Sum of frequency in each class is 100

30

20

10

Grassy with grain

Grassy

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>= 50

48-50

46-48

44-46

20th WORLD MINING CONGRESS &Semi EXPO2005 Sandy Clay grassy with grains Semi grassy

42-44

40-42

38-40

36-38

34-36

32-34

30-32

28-30

>28

0

Hard Kaolin

Principal Component Analysis (PCA) Deposit of SG & BC


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Principal Component Analysis (PCA) Deposit of BR & MD


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DISCUSSION AND CONCLUSION •The complexity of the geological setting due to the presence of different geological processes which can produce a mixture of statistical populations in space and in the time scales is one of the main difficulties of the utilization of geostatistical estimation tools. •The lack of information can hide the logical relationship between data, and then the actual relationship will be interpreted as a random or hazardous relation. The scale of observation (sampling grid) must be adapted to the scale of the essential phenomena and the precision on grades specified by the customers.


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DISCUSSION AND CONCLUSION

• Post-sedimentation processes have disturbed the general sedimentary relation between data, so the geological phenomena related to this processes must be taken into account for estimation. They can be used as a guide to divide the deposits into the more geologically homogeneous sub-domains. • Sedimentary forms are very important for the calculation of the variograms and as a guide to link data during kriging. 20th WORLD MINING CONGRESS & EXPO2005

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Thank you for your attention


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END


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