Computational Geoscience Using Excel

Featuring OSNACA and the Lithogeochem Calculator as Examples

April 2017 www.csaglobal.com

Dr Carl Brauhart

Principal Consultant

OSNACA SponsorsSipa Resources

Limited

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Computational Geoscience:

A Field Geologist’s Approach

OSNACAOre Samples Normalised to Average

Crustal Abundance

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Why OSNACA?

A multitude of multi-element ore signatures have been recognised and described qualitatively

e.g., Au-As-Sb-W Orogenic GoldAu-Bi-Te-W Another type of Orogenic GoldCu-Au-Mo-Bi-Te-Ag Porphyry CopperCu-Au-Fe-U-La Iron Oxide Copper GoldZn-Pb-Ag-Cd MVTZn-Pb-Ag-Cd-As-Tl SEDEX

How can differences (and similarities) be quantified?

OSNACA Transform

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1. Censor Data: Replace all data below average crustal abundance (ACA) with ACA

2. Normalise Data to ACA

(cannot get value < 1)

3. Log Data (with care) (cannot get value < 0)

4. Scale Data

F

A

A’

B

B’

C

C’

D

D’

E E’ & F’

Log (Element 1)

Log

(Ele

me

nt

2)

ACA

Log data with care

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Step 1 in Excel

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Censor Data to ACA

Steps 2 & 3 in Excel

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Steps 2 & 3 in Excel

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Steps 2 & 3 in Excel

Log data with care

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Step 4 in Excel

Vector Length Squared

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Step 4 in Excel

Multiply each term from Fe to U by CONSTANT

OSNACA Transform

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1. Censor Data: Replace all data below average crustal abundance (ACA) with ACA

2. Normalise Data to ACA(cannot get value < 1)

3. Log Data (with care) (cannot get value < 0)

4. Scale Data

F

A

A’

B

B’

C

C’

D

D’

E E’ & F’

Log (Element 1)

Log

(Ele

me

nt

2)

ACA

This framework is Magmato-Hydrothermal Space

MH-Space (3D)

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MVT

SHMS

VHMS

Sed Cu

IOCG

Orog

Au

Epithermal Carlin

Au

Zn

Au

Cu-AuCu-Au

Porphyry

Cu

Por.

Mo

Sn-W

Skarn

a

b

c

d

e

From Excel to Leapfrog

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Ni-Cu

MVT

SHMS

Epithermal

Sed Cu

IOCG

Orog

Au

Carlin Au

Ultramafic(Ni)

Sedimentary Igneous

Granite

(Mo, W, Sn)

Por.

MoSn-W

a

b

c

d

e

MH-Space (3D)

Main Hydrothermal Plane

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Exploring within a Class 80 VHMS Samples

VHMS Subgroups

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B

AC

D

E

a

Zn

Cu-Au Group E

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Exploring within a Deposit Prairie Downs

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Deposit Scale: Prairie Downs

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High Te-Bi-Sn

High Zn

High Pb

High Sb

Re Cu Ag Zn Cd In Tl Pb As Sb Bi Te Mo W Sn La U Re Cu Ag Zn Cd In Tl Pb As Sb Bi Te Mo W Sn La U

Re Cu Ag Zn Cd In Tl Pb As Sb Bi Te Mo W Sn La U Re Cu Ag Zn Cd In Tl Pb As Sb Bi Te Mo W Sn La U

Prairie Downs - Long Section

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Geometallurgy

Exploration Implications

LithogeochemCalculator

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Th Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V ScTh Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V ScTh Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V Scwww.csaglobal.com

Why LithogeochemCalculator?

Subtly different immobile element signatures can be difficult to discriminate, both on X-Y plots, and on Primitive Mantle Normalised Trace Element diagrams

Quantifying Shapes

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Th/Nb

Th/Yb

Gd/Yb

Er/YbGd/Dy Dy/Er

Th Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V Sc

Ho

rnb

len

de

Mag

net

ite

Pla

gio

clas

e

Ap

atit

e

Mag

net

ite

Use incompatible element ratios to discriminate between magma seriesUse compatible elements to discriminate within a magma series

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1. Data

Only 11 elements required

2. Ratios

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13 simple ratios to calculate

3. Similarity Matrix

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3. Similarity Matrix

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A

Zr

ThB

Compared to large red diamond symbol

A = 2 x

B= ½

Both are different to large red diamond by a factor of 2

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3. Similarity Matrix

Hottest Colour (Purple):

Lowest Number

Most Similar

Devlin Creek Project

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Cu-Zn-Ag-Au VHMS deposits hosted in Permian Rookwood Volcanics

Locally, basalt dominant package

Data are from one such area where basalt dominates stratigraphy and it is very difficult to discriminate any different units

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Result: Averaged Profiles

Th Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V Sc

Mid Th

www.csaglobal.comTh Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V Sc

Result: Averaged Profiles

FERTILE

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Th Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V Sc

Result: Averaged Profiles

Low Th

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Result

Th Nb Ta La Ce Pr Nd Zr Hf P Sm Eu Ti Gd Tb Dy Y Ho Er Tm Yb Lu V Sc

3 Extreme Low Th1Felsic

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Is It Any Use?

Good separation of FERTILE samples in south and east of sampled area.

Good local separation of Mid-Th from Low-Th samples

Extreme depleted all together in one hole

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And Now For Something Completely Different

Created with the help of Tony Standish

Inspired by a Legend of Modern Thinking

Four Quadrants of Exploration

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Known Knowns Unknown Knowns

Known Unknowns

Unknown Unknowns

False

Assumptions

Completely

Unknown

Scientific

Method

Infinite

Resource

Data Storage

Data Management

Discipline & Organisation

OR

?

Eg

o

Ego

Wisdom

Knowledge

Information

Data

OSNACA SponsorsSipa Resources

Limited