GEOLOGY GEOTECH MINING PROCESSING VALUATION/RISK TECHNOLOGIES ENVIRONMENT TRAINING

Sampling Case Studies

Presented by Mark NoppeAt IQPC Mine Site Sampling, Brisbane

14-15 May 2013

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Content

Importance of sampling

Sampling errors

Channel sampling

Riffle sampling

Coal sampling

Pulp sampling

QA/QC data

Bulk density

Databases

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Xstract disclaimer

© 2013 Xstract Mining Consultants Pty Ltd. All rights reserved.

This presentation has been prepared by Xstract Mining Consultants Pty Ltd (“Xstract”)(ABN 62 129 791 279). It is being made available for information purposes only. The information in this presentation is of a general nature only, and represents Xstract’s preliminary views. Xstract makes no representation or warranty as to the accuracy, reasonableness or completeness of any statement or projection in this presentation. The information contained in this presentation is confidential and must not be disclosed to any other person  without the prior consent of Xstract.

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Importance of sampling

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Where sampling errors occur

C la ss ifica tion of E rro rs (a fte r Bo ng a rco n)

L o ca lisa tio n E rro r

D e lim ita tion a ndE x tra c tio n E rror

G rou p in g a ndS e g re g atio n E rror

M a te ria lisa tio n E rro r Fundamental Sam plingError

S a m ple C o lle c tionE rro r

A n a lytica l E rro r

S a m p ling E rror

M o d e llingE rro r

K rig in g E rro r

G e o s ta tis tica lE s tim a tio n E rro r

G e o log ica lIn te rpre ta tio n E rror

E s tim a tion E rro rs

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Sampling error

• Going from the bottom up, all the errors are accumulated in a Sampling Error

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Analytical error

• The Analytical Error arises from the technique or instrument used to analyse the sample

• Do you think this error is large or small?

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Sample collection error

• The Sample Collection Error is the sum of all the errors below it

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Localisation error

• The Localisation Error is the error that arises from poorly locating the sampling points

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Materialisation error

• The Materialisation Error is the sum of the Delimitation and Extraction Error (DE and EE) and the Grouping and Segregation Error (GSE)

• DE and EE both relate to obtaining the sample

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Channel sampling: Zambia copper, Brazil gold

Samplers selectively sampling ore zone

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Mali gold – overwhelmed riffl e sampling

Riffle splitter versus automatic RC chip sampling

Good example of useIncorrect use of splitter

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Riffl es and cones

Three-tiered riffle splitter

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Cone sampler

Cone splitter

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Coal examples

• Loss of fines during drilling and/or sampling

• Poor recovery, effects typically bright (good quality coal bands)

• Coal and/or coking yield assessment

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Coal examples

• Indonesia – parting not sampled, coal qualities overstated

Coal seams

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Coal examples

• Shift sampling – shift sample tampering

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Segregation error – pulp sampling

• Gold mine – gold pulp sampling bias

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QA/QC data analysis

• Alumina XRF – trends in data overlooked

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QA/QC data analysis

• DRC – no correlation between duplicates

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Bulk density sampling

• Grab samples for grade control – used in model too, not “air dried”, no moisture adjustment, poor use of grab sample, no correction for “vugghy” samples

• Moisture content?

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Bulk density sampling

• Belt sampling – seasonal moisture issues

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Database errors

• % or ppm, particularly for cobalt from mixed database sources

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Thank you for your attention

For any follow up questions or enquires please contact:

Mark NoppeManaging Director & Principal ConsultantXstract Mining Consultants Pty Ltd

+61 7 3221 2366mnoppe@xstractgroup.com

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