presentation of smam - spectral mapping of alteration minerals

Spectral Mapping

of

Alteration Minerals

A service provided by

S M A M

Applications of SMAM

Case study example

SMAM working procedure

Examples of mineral spectra

SMAM results (alteration zoning)

We interpret mineral spectra recieved with a spectrometer

• Both with the help of different softwares and manually

Wavelength in nanometers

Dep

th o

f sp

ectr

al

feat

ure

s (0

-1)

”we are looking at different absorption features in the spectra”

(OH) bearing minerals: clays, micas, chlorites, talc, epidote, amphiboles, sulphates and carbonates

1100 - 2500 nm vibrational processes

Visible and near infrared (VNIR)

400 - 1100 nm electronic processes

Spectral features relevant to mapping of alteration minerals

• By using an ASD TerraSpec spectrometer we are able to measure 1500 - 2000 m of drill core per

day (1 m intervals). One measurement takes about 5 sec.

• Large data sets of spectra (> 50.000) can be compiled quickly at low cost allowing an in-depth

evaluation of the alteration system to be carried out.

• Simplified: We measure the amount of light reflected from the sample.

Sample (e.g. core, rock chip, grab specimens, powders, outcrops and soils)

Light source (visible-SWIR range)

Detector; an optical cable connects the light source with the TerraSpec

The results are then interpreted with The Spectral Geologist software

Introduction to SMAM

Epithermal alteration systems

Porphyry alteration systems

Kimberlites

IOCG VHMS

Shear veins Skarns

Disseminated gold systems

We are using with and software for:

Mapping alteration minerals in order to identify alteration zones and to define ore bodies.

Analysis of a wide variety of deposit types

Greenschist

belts

Carbonate

hosted base

metals

Common alteration minerals we can measure with SMAM

• Muscovite-paragonit, biotite, phlogopite Micas

• Variations in Fe-Mg chlorite Chlorites

• Tremolite, hornblende, actinolite Amphiboles

• Illite, illite/smectite, kaolinite, dickite Clays

• Jarosite, gypsum Sulfates

• Calcite, dolomite, ankerite, siderite Carbonates

• Fe-tourmaline, tourmaline Tourmaline

The sample can be almost anything – but it has to be dry

Since the TerraSpec is field portable, we can work both inside and out in the field

Case study example




Applications of spectral geology Once the spectral data has been obtained it can be used to identify:

1) Mineral occurrence

• We can map the distribution and/or determine estimates of a particular mineral

species.

2) Changes in mineral proportions

• It is possible to recognize variations in mineral proportions.

3) Mineral composition and crystallinity

• Trends in mineral crystallinity and composition can also be identified in the spectra.

• This allows us to distinguish between different phases of the same mineral.

Dec

reasin

g m

atc

h

1) Mineral occurrence

• Important for example if a specific mineral of interest has an

established relationship with the target mineralization.

Assemblage Histogram

Probable TSA Mineral

% M

atch

es

Kaolinite Illite Muscovite Actinolite Riebeckite Hornblende FeChlorite IntChlorite Biotite Ankerite Siderite FeTourmaline

06

12

18

24

Match

0

154

308

462

615

769

923

1077

1231

1385

1538

1692

1846

2000

>2000

0 = Perfect match

(red)

Assemblage histogram of the mineral distribution as suggested by The

Spectral Geologist software

Mineral occurrence can be viewed for example as

drill-core sections

2) Changes in mineral proportions

Example of muscovite + Fe-chlorite (1) and Fe-chlorite + muscovite (2)

FSFR.2131 Int=3.0 sec

Wavelength in nm

No

rm.

Hu

llQ

(A

ux.

co

lou

r: N

orm

. H

ull

Q)

1400 1600 1800 2000 2200 2400

00.3

0.6

0.9

2258

2491

1412 2350

1916

2208

Depth

0

0.015

0.029

0.044

0.059

0.074

0.088

0.103

0.118

0.132

0.147

0.162

0.176

0.191

0.206

0.221

0.235

0.25

0.265

0.279

0.294

0.309

0.324

0.338

0.353

0.368

0.382

0.397

0.412

0.426

0.441

0.456

0.471

0.485

0.5

1) 2260nm

2350nm

2200nm >white mica

FSFR.2131 Int=3.0 sec

Wavelength in nm

No

rm.

Hu

llQ

(A

ux.

co

lou

r: N

orm

. H

ull

Q)

1400 1600 1800 2000 2200 2400

00.3

0.6

0.9

2204

1411

2490

1918

2257

2349

Depth

0

0.015

0.029

0.044

0.059

0.074

0.088

0.103

0.118

0.132

0.147

0.162

0.176

0.191

0.206

0.221

0.235

0.25

0.265

0.279

0.294

0.309

0.324

0.338

0.353

0.368

0.382

0.397

0.412

0.426

0.441

0.456

0.471

0.485

0.5

2)

2200nm

2260nm

2350nm >iron chlorite

Depth of the 2200nm feature

Depth of the 2250nm feature

Au values

3) Mineral composition and crystallinity • Variations in chemical composition can be detected

as the wavelength positions of features shift consistently

with elemental substitution.

• This provides discrimination of different phases of the

same mineral, based on variations in composition and/or

crystallinity.

• These can be very important indicators in alteration

systems, for example when looking for vectors towards

prospective parts of the alteration system.

In the enhancement you can see the change in composition from Mg- to

Fe- chlorite, as the wavelength increases from 2330 nm (Mg) towards 2350

nm (Fe).

Chlorite chemistry Variations in the wavelength of the chlorite 2340nm absorption feature.

The wavelength of

the sericite 2200nm

absorption feature is

highly variable. This

plot shows some of

the variation.

White mica chemistry Variations in the wavelength of the sericite 2200nm absorption feature.

• The presence of acid pushes the equilibrium towards muscovite, neutral pH pushes it to phengite.

Mica Composition, samples 1 to 9 (Aux colour: Index)

Wavelength in nm

No

rm. H

ullQ

(S

tac

ke

d)

2030 2100 2170 2240 2310 2380

Aux

0

0.348

0.696

1.043

1.391

1.739

2.087

2.435

2.783

3.13

3.478

3.826

4.174

4.522

4.87

5.217

5.565

5.913

6.261

6.609

6.957

7.304

7.652

8

NULL

1

2

3

4

5

6

7

8

9

Short wavelength = muscovite

Long wavelength = phengite, Mg- and Fe-rich

Kaolinite crystallinity Measure the size of the 2160nm doublet.

Kaolinite, samples 1 to 4 (Aux colour: Index)

Wavelength in nm

Hu

llQ

uo

t (S

tac

ke

d)

1500 1800 2100 2400

Aux

0

0.13

0.261

0.391

0.522

0.652

0.783

0.913

1.043

1.174

1.304

1.435

1.565

1.696

1.826

1.957

2.087

2.217

2.348

2.478

2.609

2.739

2.87

3

NULL

1

2

3

4

Poorly ordered Kaolinite

Well ordered

Kaolinite

2160 nm

Comparison of different biotites

• Short wavelength to long wavelength.

• Besides the shift in the wavelength of

the 2250nm feature, the spectrum also

changes symmetry.

b

Wavelength in nm

Hu

llQ

uo

t

1500 1800 2100 2400

0.9

1

19211395

2490

2497

2388

2476

2249

2326

Depth

0

0.022

0.043

0.065

0.087

0.109

0.13

0.152

0.174

0.196

0.217

0.239

0.261

0.283

0.304

0.326

0.348

0.37

0.391

0.413

0.435

0.457

0.478

0.5

b

Wavelength in nm

Hu

llQ

uo

t

1500 1800 2100 2400

0.9

24

0.9

35

0.9

46

0.9

57

0.9

68

0.9

79

0.9

9

1398

2459

2488

24811924

2469

2349

2257

Depth

0

0.022

0.043

0.065

0.087

0.109

0.13

0.152

0.174

0.196

0.217

0.239

0.261

0.283

0.304

0.326

0.348

0.37

0.391

0.413

0.435

0.457

0.478

0.5

Proximal biotite

Distal biotite

Mg-rich

Fe-rich

2248 nm

2257 nm

• The 2250 feature gets larger as it

shifts to longer wavelengths and a

secondary feature at 2390nm, which is

always present in Mg minerals,

becomes less and less apparent as the

2250 wavelength increases.

•The changing shape of the biotite

spectra is mapping a change from Mg-

rich biotite in the proximal part of the

system to Fe-rich in the more distal

areas.

Comparison of different biotites

Short wavelength to long wavelength

The changing shape of the biotite spectra is mapping a change from Mg-rich biotite in the proximal part of the system to Fe-rich in the more distal areas.

b

Wavelength in nm

Hu

llQ

uo

t

1500 1800 2100 2400

0.9

1

19211395

2490

2497

2388

2476

2249

2326

Depth

0

0.022

0.043

0.065

0.087

0.109

0.13

0.152

0.174

0.196

0.217

0.239

0.261

0.283

0.304

0.326

0.348

0.37

0.391

0.413

0.435

0.457

0.478

0.5

b

Wavelength in nm

Hu

llQ

uo

t

1500 1800 2100 2400

0.9

24

0.9

35

0.9

46

0.9

57

0.9

68

0.9

79

0.9

9

1398

2459

2488

24811924

2469

2349

2257

Depth

0

0.022

0.043

0.065

0.087

0.109

0.13

0.152

0.174

0.196

0.217

0.239

0.261

0.283

0.304

0.326

0.348

0.37

0.391

0.413

0.435

0.457

0.478

0.5

Proximal biotite

Distal biotite

Mg-rich

Fe-rich

2248 nm

2257 nm

Cross section of the Fäboliden Au-deposit

Biotite wavelengths plotted along drill holes, short wavelength biotite (blue) correlates with the Au-mineralization.

Theoretical example of picking diamond drill holes and surface samples for SMAM work

- One section along mineralisation zone.

- Sections with ~ 200 m space perpendicular to mineralisation and in major mineralisation zone ~ 100 m spacing.

- Holes situated ~ 25 m to both sides from the section to be included in spectral mapping program.

- Few selected holes from periphery.

- Also surface samples such as grab samples and trench samples can be included to get an surface study.

Project planning

Typical working procedure

1. The project starts with collecting spectral data from for example drill-core, rock chips, powder or crushed material. One measurement takes only a few seconds.

2. The data is then imported into The Spectral Geologist software for interpretation. In TSG you can view your results e.g. as spectra, scatter plots, charts etc.

Fe-chlorite Sericite

Amphibole

Biotite

3. The combined information can then be presented in different formats

Since the TSG data can be exported for use in other softwares, the integration of spectral and for example geochemical data allows relationships between target mineralization and the spectral characteristics of the alteration to be investigated.

On the other hand, you can also work in the opposite direction by importing other necessary data into TSG.

Drill-core sections

Mineral Mapping Pty Ltd

The spectral data can also be

imported to your GIS or 3D software.

2D maps

3D models

OH

Water peak

H2O/OH

Al-OH (White mica)

Fe-OH (Chlorite)

Mg-OH (Chlorite)

Example: Sample with White mica and Chlorite

Amphibole features: Near 1400 nm, and a pair near 2310 and 2380 nm (tremolite has a doublet at ~2315 nm).

Biotite features: A major feature at 2330 nm, commonly with a shoulder near 2380 nm. A subordinate feature is present around 2245-2260 nm.

Chlorite features: There are two major absorption features for chlorite; at 2260 nm and 2350 nm for Fe-chlorite; or at 2250 nm and 2330-2340 nm for Mg-chlorite.

Epidote features: The major feature is near 2340 nm with a sharp, but lesser, absorption near 2258 nm. In these respects it is similar to chlorite, with which it can sometimes be confused. Epidote, however, has its third most diagnostic feature near 1550 nm and fourth feature near 1884 nm.

Muscovite (sericite) features: Fairly sharp features near 1408, 2200, 2348, 2442 nm. A broad "dimple" can occur near 2100 nm.

Scapolite features: Major features at 1420,1478, 2340 and 2358 nm.

Calcite features: Major features at 1880, 1990 and 2340 nm.

Fe-tourmaline: Major features at 2200, 2245, 2300 and 2370 nm.

Spectral features

Minerals are classified by comparing different absorption features, e.g. the wavelength of the minimum, the depth and width of the features etc

Biotite Chlorite, sericite


Tremolite, sericite Biotite, sericite



Calcite Calcite + epidote + sericite

Typical calcite with a broad feature at ca 1400 nm.

Epidote features at 1550 nm, 1830 nm and 2250 nm, sericite feature at 2200 nm.

Dolomite, CaMg(CO3)2

Dolomite = ca 1858 nm, while calcite has ca 1875 nm

Dolomite = ca 1978 nm, while calcite has ca 1995 nm

Dolomite = ca 2320 nm,

while calcite has ca 2330 nm

Results: Wavelength of the 2200nm absorption feature in sericite, plotted against depth

down hole

• Topaz, dickite, pyrophyllite is an assemblage that forms in very acidic conditions.

• The wavelength of the 2200nm absorption feature in sericite reflects the pH of the alteration fluid.

• Topaz-bearing assemblages

have very short mica

wavelengths. In contrast,

albite-rich alteration zones

(alkaline) have very long mica

wavelengths.

• The muscovite to phengite

reaction is controlled by pH.

• In sericite zones, muscovite

means acid fluid; phengite

means alkaline fluid.

• The shift in the white mica

wavelength can be used as a

hydrothermal pH indicator. Depth

Scope 1:782; 782 points, R² =0.325; Aux: Au

Easting

Nort

hin

g

3240 3280 3320 3360

12320

12360

12400

12440

12480

0

0.074

0.148

0.222

0.296

0.37

0.444

0.519

0.593

0.667

0.741

0.815

0.889

0.963

1.037

1.111

1.185

1.259

1.333

1.407

1.481

1.556

1.63

1.704

1.778

1.852

1.926

2

NULL

Scope 1:782; 782 points, R² =0.325; Aux: Wav e_AlOH

Easting

Nort

hin

g

3220 3240 3260 3280 3300 3320 3340 3360 3380

12320

12360

12400

12440

12480

2206

2206.148

2206.296

2206.444

2206.593

2206.741

2206.889

2207.037

2207.185

2207.333

2207.481

2207.63

2207.778

2207.926

2208.074

2208.222

2208.37

2208.519

2208.667

2208.815

2208.963

2209.111

2209.259

2209.407

2209.556

2209.704

2209.852

2210

NULL

Au values AlOH wavelength

1) 2)

Incre

asin

g

Au

va

lue

s

De

cre

asi

ng

wa

ve

len

g

th

TSG scatter plot of Au values (1) and AlOH wavelength (2), horizontal section. The

relationship between high Au values (red and yellow dots) and low AlOH wavelengths (red

and yellow dots) are highlighted in the pictures (© Copyright CSIRO Australia, 2008).

Results: Horizontal maps created with The Spectral

Geologist, Au values imported to the software

• In this example the high Au values correlate with short AlOH

wavelengths

AuvEpidote

Sulphide (asp)

Chlorite

Epidote

Sulphide (asp)

Amphibole_chlorite

Chlorite

Amphibole

Sulphide (asp)

Chlorite

Chlorite

Chlorite

Amphibole

Amphibole

Sulphide (asp)

Chlorite

Sulphide (asp)

Sulphide (asp)

Chlorite

Chlorite

Chlorite

Sulphide (asp)

Chlorite

Amphibole_muscovite

Amphibole

Amphibole

Amphibole

Amphibole

Chlorite

Amphibole_muscovite

Amphibole_muscovite

Amphibole

Amphibole_muscovite

Amphibole_muscovite

Amphibole_muscovite

Amphibole_muscovite

Amphibole

Amphibole

Amphibole_muscovite

Amphibole_muscovite

Amphibole_muscovite

Amphibole_muscovite

Amphibole

Amphibole

Amphibole_muscovite

Amphibole

Amphibole

Amphibole

Amphibole

Amphibole

Amphibole_muscovite

Amphibole

Amphibole_muscovite

Amphibole_chlorite

Epidote

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

NULL

Wavelength

Au gt

0 1.1 2.2

Norm. HullQ

1500 2000 2500

Depth27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

Norm. HullQ

1500 2000 2500

Depth Normal HullQ Au values Classification

Down hole direction --

----

--A

lte

red

zo

ne

----

----

Integration of spectral and geochemical data

Results: Down hole profile, mineralogy/alteration vs. Au,

TSG data exported

Smectite

Illite-Smectite

Illite

Sericite

Kaolinite

Dickite

Pyrophyllite Alu

nit

e

Low Temperature

High Temperature

Low pH Increasing pH

disordered kaolinite

ordered kaolinite

Low crystallinity mica

High crystallinity mica

Short wavelength mica

Long wavelength mica

Simplified phase diagram of an epithermal system

DH1 DH2

Illite

Muscovite

Kaolinite

Dickite

Pyrophyllite

Alunite + Silica

Kaolinite (Steam-heated)

Increasing Kaolinite crystallinity

Increasing Illite Crystallinity

Increasing Illite abundance

Illite-Smectite

Illite-Smectite

Illite wavelength = 2206nm

Decreasing Mica AlOH wavelength

Example of an epithermal system with alteration minerals that can be measured

DH 1 DH 2

DH 1: With SMAM you are able to see the change from smectite-illite, and the decrease in mica AlOH wavelength, which helps you to navigate in the system and

localize the ore body (DH 2).

Example Porphyry Cu-Mo-Au Systems Vertical zonation from Advanced argillic, (pyrophyllite, dickite, quartz Topaz in F-rich systems) or Argillic, (illite-smectite) Phyllic, (sericite) to Potassic, (biotite + K feldspar) to Lateral Zonation from Potassic to Propylitic, (actinolite, chlorite, epidote, albite, calcite)

Seedorff et al., 2005

Advanced Argillic Alteration (vertical zonation)

Topaz Advanced Argillic (in Fe-rich systems, e.g. Porphyry Mo)

Dickite – Advanced Argillic

Phyllic Alteration (vertical zonation)

Phengite Adjacent to potassic or propylitic (deep)

Muscovite - Acidic Adjacent to Adv. argillic (shallow) Short 2200 nm

wavelength

Longer 2200 nm wavelength

Potassic Alteration (lateral zonation)

Mg-rich biotite Proximal

Fe-rich biotite Distal

2245nm

2255nm

Propylitic Alteration (vertical zonation)

Mg Chlorite (overprinting actinolite) High temp, neutral

Fe Chlorite – Low temp, acid

Longer wavelength

Shorter wavelength

Sediment

Rhyolite

Cu-Pb-Zn VMS

Au-As Deposit

Andalusite

Sericite zonation

Wavelength measured

with ASD

Intense alteration

zone, but no metal

Scale 1km

Simplyfied schematic model of how to navigate in alteration systems

3D snapshot

THE END

presentation of smam - spectral mapping of alteration minerals

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