1

Structural Mapping using PIMA Spectrometer

S. Mondlane

salmond@zebra.uem.mz or sas97sa@gmail.com

Presented @ GIRAF – Geosciences Information in Africa; 23rd – 27th September 2013;

Accra, Ghana

2

Presentation Layout • Introduction

• Mineral identification

• Mapping the degree of alteration in the mineralised shear zones

– Shear zones near the contact between the Bulawayan and Shamvaian Supergroups

– Shear zones on the contact between Bulawayan Supergroup and granites

– Shear zones near the Penhalonga granodiorite

• Results

• Discussion

INTRODUCTION

• East Zimbabwe Craton

• The MMO greenstone is an

important gold mining area

with combined historical

production and estimated

reserves of 128 t of gold

(Forster et al., 1996). There

are 241 old gold mines.

• The MMO area is dominated

by complex geological

history, characterized by

early accretionary structures

and later folding and

shearing. Various types of

brittle-ductile fractures

truncated this sequence

before the introduction of

gold mainly in the late

Archaean

3

4

Introduction

5

The relationships between the Bulawayan and the

overlying Mbeza and Mbeza Vengo sedimentary units is

controversial.

• The structure is a tightly folded synform made up of at

least three east-west striking en echelon synforms gently

plunging eastward at 25 – 30° and separated by tight

antiforms.

430000 440000 450000 460000 470000 480000 490000 500000

7900000

7910000

7920000

Shear zones

Trends

x

x x

x

x

y

y

y

y

y

y y

y

YUTM Coordinates Granites

Inner Granites

0 1000 2000 3000 4000

Zimbabwe

Harare

Mo

za

mb

iqu

e

m Bulawayan

Shamvaian

PENHALONGA

Chazuca

X

6

Gold Mineralization • Gold is controlled by secondary structures (e.g. fault

splays and duplexes), mainly related to dilational

quartz veins. Few Gold deposits are found in

metasedimentary rocks.

410000 420000 430000 440000 450000 460000 470000 480000 490000 500000

7890

000

7900

000

79

100

00

79

200

00

Boa Esperanca

Dot's Luck

Guy FawckesMunhene

ExcelsiorDias Perreira

Marondo

DampBraganca

MimosaShandon

Monarch

RezendeRedwing

TorontoReliance

Kenya Howat's Luck

Champion

Odzi

Quagga

Pilgrim

Chivuma

Gold Deposit

0 5000 10000 15000 20000

Shera zones

Zimbabwe

Harare

Mo

za

mb

iqu

e

UTM Coordinates m

7

Most of the gold in MMO belts is confined to the vicinity of re-activated ductile shear zones

022/52043/56

024/62062-39

??

?

? 021/66200/83

Faul t PlanLnx- 40E

S

0.5 cm

Chloritic-talc schist

Strike and dip

mineralised zones

Spacing of the 2nd

fo l ia tion exagerated

angle betw een the 2 foliation is less than 15.

100 m

8

How do we map structures using PIMA

• The most challenging problem in mineral exploration is finding method(s) that easily map mineralised structures in greenstone belts.

• Once the relationships between the mineralisation and structures (e.g. shear zones) are established, probably the most viable exercise is to devise methods and techniques that can map structures.

9

• The use SWIR spectrometry for mineral exploration has

increased dramatically in recent years. The reflectance

spectrum of a mineral in the SWIR is characteristic.

• Mineral spectrum is unique and depends on composition

and crystallinity.

UV Visible Near Infrared Short Wavelength Infrared Mid IR Far IFMicrowave Radiowave

OH

+ H

2O

H2

O

AlO

H

Fe

OH

Ca

CO

3

+M

gO

H

VIBRATIONAL SPECTRAL

ABSORPTION FEATURES

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Minerals when irradiated by a source of light, selectively

absorb and reflect light in different amounts at specific

wavelengths due to the bending and stretching of

molecular bonds (Clark, 1999)

Mineral group/

composition

Wavelength in nm

OH (structurally bound)

1400 (also 1550 and 1750-1850 in some

minerals)

Water

1400 and 1900

Al-OH

2160-2220

Fe-OH

2230-2295

Mg-OH

2300-2360

CO3

2300-2350 (and also at 1870, 1990 and

2155)

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PIMA SP principles, the PIMA spectrum, PIMA measurements and data processing, and feature extraction.

12

PIMA SP spectrum is characterised mathematically by

spectral parameters, which describe spectral features on

the basis of depth, width, asymmetry, size and wavelength

position of a particular absorption feature.

Spectrum S_06_SSP_Rw (1% SHQ)

85

87

89

91

93

95

97

99

101

1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500

Wavelength (2nm sampling)

Re

fle

cta

nc

e i

n p

erc

en

tag

e

L Should

Depth

Central WL

Width

PIMA Spectra & feature extraction

13

Mineral identification • It is not unique method (Can be used in the field)

• The diagnostic characteristics of each mineral are ideal in pure (no mixing) minerals. Real life (Mixtures)

• Method 1- Comparison of the spectra with spectral library (spectra resulting from analyses and tests under different conditions such as differing grain sizes or mixtures of various materials). It is sensitive enough to map different regions of the spectrum such as a kaolinite versus a halloysite-like feature.

• The result can then be compared with results from other identification methods such as chemistry and petrography.

14

The spectra resemble the mixture of anhydrite,

montmorillonite and halloysite at proportions of

37:32:30 percent.

1300 1500 1700 1900 2100 2300 250032

38

44

50

56

62Spectra of sample 21_Sp_Rw

Nanometer

Refle

ctanc

e (%)

Spectrum of the sample

Reference spectrum

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Mixed Spectrum

• Most minerals generally have major diagnostic absorption wavelengths between 2050 and 2450 nm due to Al-OH, Fe-OH, Mg-OH and CO3 absorption bonds and can be grouped spectrally according to the wavelength position of their deepest absorption feature.

• The spectral mixing can be considered in a simplistic way as a linear process where spectral signatures of different minerals are added together in one spectrum. For example;

• Mixed Spectrum = X% Mineral 1 + Y% Mineral 2 + Z% Mineral 3 +...+ % Mineral n

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Water

Pyrophylite

F e rich Chlorite

Anhydrite

Diaspore

Hornblende

A lunite

Buddingtonite

Nontronite Jarosite

Tremolite

Tourmaline

Dolomite B io tite

Calcite Epidote

M g rich Chlorite

Gypsum

Actino lite M agnesite

Apatite

Aragonite

Antigorite Siderite Phlogopite

Talc

M ontmorillonite

Illite Phengite

M uscovite Kaolinite

Halloysite Dickitite

2000

2050

2100

2150

2200

2250

2300

2350

2400

0 5 10 15 20 25 30 35 40

Absorption (%)

Wav

ele

ngth

in n

m

2nd method: Plotting a scattergram of the deepest

absorption feature of the sample against the wavelength. This

method allows identification of mineral fields according to the

position of the sample in the scatter plot.

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3rd method: similar to the previous method where the

asymmetry is used instead of deepest absorption feature. Method

proved to be powerful tool for discrimination of mineral field that

usually overlap in the scatter plot of deepest absorption feature.

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

1400 1450 1500 1550 1600 1650 1700 1750 1800 1850 1900 1950 2000 2050 2100 2150 2200 2250 2300 2350

Wavelength (nm)

Alunite

Kaolinite

Water

Nontronite

Talc

Actinolite

Asy

mme

try

Chlorite

Water

Kaolinite

Sericite

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Mapping alteration in the mineralised shear zones

1300 1500 1700 1900 2100 2300 2500

31

36

41

46

52

57

Spectra os the samples Sp8_1 to Sp8_4

Nanometer

Refle

ctanc

e (%

)

Sp8_1

Sp8_2

Sp8_3

Sp8_4

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Profile Sp/GF

0

10

20

30

40

1300 1500 1700 1900 2100 2300

Central w avelength (nm)

Depth

of absorp

tion

Profile Sp/GF

0

0.2

0.4

0.6

0.8

1

1.2

1300 1500 1700 1900 2100 2300

Central w avelength (nm)

Assym

etr

y

Water

Water

Talc Talc

Sericite Sericite

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Shear zones near the contact between the Bulawayan and Shamvaian Supergroups

Profile Sp8

0

5

10

15

20

25

30

1800 1900 2000 2100 2200 2300 2400

Central w avelength (nm)

Depth

of absorption

Water

Kaolinite

Nontronite Talc

Profile Sp8

0

1

2

3

4

1800 1900 2000 2100 2200 2300 2400

Central w avelength (nm)

Assym

etr

y

Talc

Nontronite Kaolinite

Sericite

Water

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Sheared contact between Bulawayan Sp-group and granites

Profile Sp1

0

20

40

60

1300 1500 1700 1900 2100 2300

Central w avelength (nm)

Depth

of A

bsorption

Profile Sp1

0

1

2

3

4

1300 1500 1700 1900 2100 2300

Central w avelength (nm)

Assym

etr

y

Water Water

Sericite

Sericite

Kaolinit

e

Kaolinit

e

Kaolinit

e

Kaolinite

22

Shear zones near

the Penhalonga

granodiorite

Profile Sp/Rw

0

10

20

30

40

1300 1500 1700 1900 2100 2300 2500

Central w avelength (nm)

Depth

of absorption

Profile Sp/Rw

0

1

2

3

4

1300 1500 1700 1900 2100 2300

Central w avelength (nm)

Assym

etr

y

Talc

Kaolinite

Water

Sericite

Kaolinite Talc

Kaolinite

Water Sericite

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1

10

100

Sp8

/01/

99

Sp8

/02/

99

Sp8

/03/

99

Sp8

/04/

99

Sp8

/05/

99

Sp8

/06/

99

Sp8

/07/

99

Sp8

/08/

99

Sp8

/09/

99

Sp8

/10/

99

Sp8

/11/

99

Sample number

Min

era

l M

ixtu

re %

Anhydrite

Talc

Kaolinite

Halloysite

Hornblende

Interpretation of the Results

Reflectance parameters (e.g. absorption feature) and the asymmetry index are important for the identification of the minerals in each sample but have proved to be of less significant when it comes to map shear zones and associated alteration, mainly due to mineralogical

mixture reflected

in the spectrum

and to the limited

amount of minerals

revealed by this

technique.

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Approach that considers the % of each mineral in

the mixture in order to identify differences in

proportion and distribution of minerals resulting

from the presence of shear zones

1

10

100

Sp/G

F/01

Sp/G

F/02

Sp/G

F/03

Sp/G

F/04

Sp/G

F/05

Sp/G

F/06

Sp/G

F/07

Sample number

Min

era

l mix

ture

%

Anhydrite

Talc

Kaolinite

Halloysite

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Profile on: ultramafic schists, granodiorite, a disturbed mine area

including old mine dumpsite and a contact between granodiorite

and ultramafic schists. The different minerals at varying

proportions, might be related to the lithologies underneath.

1

10

100

RE

D2

/01

/99

RE

D2

/04

/99

RE

D2

/06

/99

RE

D2

/08

/99

RE

D2

/10

/99

RE

D2

/12

/99

RE

D2

/15

/99

RE

D2

/17

/99

RE

D2

/19

/99

RE

D2

/21

/99

RE

D2

/23

/99

RE

D2

/26

/99

RE

D2

/28

/99

RE

D2

/30

/99

RE

D2

/32

/99

RE

D2

/37

/99

RE

D2

/40

/99

RE

D2

/42

/99

Sample number

Min

era

l m

ixtu

re %

Anhydrite

Talc

Halloysite

Kaolinite

Tremolite

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Conclusion • PIMA spectrometer can be used in the field for

mapping shear zones during exploration programs in the MMO greenstone and similar environments.

• PIMA analysis can be important for validation of the existence or not of shear zones, which could have been defined on the basis of satellite imagery interpretation. This was observed in all profiles that crossed known shear zones which have shown mineralogical anomalies on top of the shear zones.

• PIMA data are only provisional for preliminary stages of exploration programs and this type of data bear the advantage of fast mineralogical results in the field.

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Special thanks to: • de Beers SA • The Organizers and sponsors to this GIRAF 2013

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29

0

5

10

15

20

25

30

S_06_

SSP_R

w_

S_07_

SSP_R

w

S_10_

SSP_R

w

S_11_

SSP_R

w

S_14_

SSP_R

w

S_17_

SSP_R

w

S_19_

SSP_R

w

S_23_

SSP_R

w

S_24_

SSP_R

w_

S_28_

SSP_R

w_

S_30_

SSP_R

w_

S_34_

SSP_R

w_

S_38_

SSP_R

w_

S_41_

SSP_R

w_

Salmpes

Absorp

tion (

%)

(1350 -

1700 n

m)

Iron Parameter