Sampling Issues:

Getting the right sample

Dr. Rob Bowell – SRK Consulting (UK)

Introduction

Geochemical and mineralogical

testwork requires validated, well

located samples that are

representative

Essential components in

characterization of mine waste

Starts with getting a good

sample!

What is a good sample?

What to sample?

Depends on focus:

• Source

Waste rock, core, tailings, heap leach, pit walls, pit lake, tailings pond

• Pathway

Groundwater, surface water

• Receptor

Soil, sediment, water, plants, animal tissue/fluid

5/19/2014 3

Gaps in Predictive Knowledge

Sampling approach • Representation

• Heterogeneity

• Number of samples

Verification of data

Assessment of non-standard protocols

Application of field tests

Kinetic tests

Assessment of ecotoxicology

Approaches to Sampling

Spatial • Visual assessment

Numerical • Samples collected randomly

proportional to predicted waste production

Geological • Determine rock and alteration

types to determine

Statistical • Account for heterogeneity in

sampling set by determining number of samples required

• Apply Gy theorem to variation in sample parameters

Sampling: Two key issues for ARDML

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0.010.1110100

Sieve Size (mm)

Pe

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0-10 10-20 20-30 30-40 40-50

Representation

• Provide representative sampling

of system being assessed

• Complicated by heterogeneity

Heterogeneity approach

• Accept heterogeneity and complicate

QA-QC programs & sampling

• Eliminate through homogenization

Size fraction

• Silt fraction controls majority

of water movement

in most waste types.

Important to ensure

sample represents size fractions

Material Type Delineation

and Sample Selection

• Review of drill core logs and delineation of primary material types.

• Material defined by:

o Lithology e.g. quartz monzonite, breccia, andesite, limestone

o Alteration e.g. argillic, potassic, silica

o Oxidation - oxide, transitional (minor limited mainly to ore),

sulfide

o Metal grade – ore, marginal or low grade, mineralized waste,

non-mineralized waste, overburden

Use of Mine Site Information

Site knowledge

Geological – mining model of

site

Incorporate –

• Spatial distribution

• Material characteristics

• Geology

• Relationship to phases of

mining

Core Sample Collection

• Leapfrog 3D geological modeling software used to query mine model.

• Sample intervals representative of waste within pit shell.

• Includes samples within shell drawn 200 feet outside the proposed pit.

Example of Sample Matrix –

by material type Material Type Number of Samples

Andesite 4

Diabase 2

Sulfide waste 72

Transitional waste 13

Sulfide ore 26

Transitional ore 14

Oxide ore 1

Tailings 12

Historic tailings 2

TOTAL 146

Example using site specific

rock classification

Important: rock type and spatial

representativity

Compare samples to rock

geochemistry from exploration

Best Approach – a combination

Avg sulfur grade % % of deposit

Albite 0.02 0.14%

Actinolite Skarn 0.37 0.55%

Amphibolite 1.06 1.02%

Banded Iron Formation 5.17 0.05%

Biotite phlogopite 0.14 0.46%

CPX Actinolite Skarn 0.95 7.36%

CPX-skarn 1.19 16.66%

Diorite 3.52 0.13%

Dyke 0.43 0.15%

Granite 0.24 3.84%

Greenstone 0.16 0.22%

Marble 0.85 2.53%

Magnetite-skarn 0.55 16.48%

Quartz Phyllite 0.93 0.13%

Quartz 2.32 0.16%

Skarn 0.45 31.91%

Serpentinite skarn 0.65 8.29%

Tremolite skarn 0.22 1.53%

AVERAGE 0.62%

Field Assessment

Field mapping

Mineralogy

• Estimate sulfide/carbonate

minerals present

Field tests- the paste method

• Assessment of reactivity

• Useful screening method

Field analysis

Use data for screening & direct

laboratory work

Benefit of Field Assessment

• Rapid results

• Material characteristics to

explain chemical

heterogeneity in similar

materials

• Expand to undertake field

trails on “pilot scale waste

dumps”

• Test historic waste materials

versus freshly mined

materials

• Analysis in the field

• No delay due to laboratory analysis

• Rapid turnaround of results to aid sampling

• Cost effective

• Measure parameters of environmental

concern

• Sulfur – indication of acid generation

• Ca+Mg – indication of acid buffering

(calcite-dolomite and Mg-rich silicates)

• Metals (Cu, Cr, Fe, Mn, Pb, Zn, Cd, Hg….)

• Metalloids (As, Sb, Mo, Se……..)

Portable XRF in Environmental

Geochemistry

• Relate geochemistry to site conditions

• Use lithology but often lithologies can have

large differences due to alteration

• Obtain geochemical indices of high/low S

or metals – distinguish end points

for each lithology

Take Away Statement

Sample Selection

• Environmental risk – liability due to

unprocessed ore or reactive waste

• But can we relate potential for metal

release or acid generation to total metal

content?

Rapid Risk

Assessment

• Environmental risk – assess toxicity in terms of total metals such as in EU

contaminated land guidelines

• Assess metals in terms of Geochemical Abundance ie GAI >3 anomaly

• Total metal chemistry as an initial guide to metal toxicity

Toxicity evaluation

Ag Bi Cu Hg Mo Pb S Sb Se Zn

ppm ppm ppm ppm ppm ppm % ppm ppm ppm

AECA 0.07 0.2 60 0.085 1.2 14 0.04 0.2 0.1 70

GAI=0 0.105 0.3 90 0.1275 1.8 21 0.0525 0.3 0.075 105

GAI=1 0.21 0.6 180 0.255 3.6 42 0.105 0.6 0.15 210

GAI=2 0.42 1.2 360 0.51 7.2 84 0.21 1.2 0.3 420

GAI=3 0.84 2.4 720 1.02 14.4 168 0.42 2.4 0.6 840

GAI=4 1.68 4.8 1440 2.04 28.8 336 0.84 4.8 1.2 1680

GAI=5 3.36 9.6 2880 4.08 57.6 672 1.68 9.6 2.4 3360

Lithology GAI=6 6.72 19.2 5760 8.16 115.2 1344 3.36 19.2 4.8 6720

QMBS Avg 5.26 9.16 1101.15 3.10 20.00 2963.13 2.47 7.86 1.12 2697

SDev 4.06 7.66 1398.35 7.70 17.63 3787.40 1.55 13.25 0.94 2913

MV Avg 0.92 1.09 178.46 0.12 4.67 203.86 0.55 1.25 0.50 888

SDev 1.35 1.24 202.24 0.27 5.26 410.97 1.01 2.19 0.00 1313

QMS_Sul (Sil/Cly/Chl/Ser) 2.39 7.09 1110.00 0.24 29.60 187.00 5.00 6.70 2.00 4120

MBS_Sul (Sil/Chl(Ser)) 1.83 6.56 1110.00 0.21 34.40 179.00 5.00 6.67 2.00 3540

Overburden Avg 2.94 2.69 414.00 0.62 6.39 909.00 0.43 5.18 0.50 1360

SDev 3.27 2.24 408.71 0.66 5.96 963.08 0.11 4.94 0.00 495

Metal distribution across site:

Tsumeb, Namibia

Copper distribution

across Tsumeb district

TSF

Smelter

Tschudi

Tsumeb West

• Representative sample

• Representative analysis

• Issues with penetration into the sample?

• Surface analysis- representative analysis?

• Mineralogy effects?

Major Issues

• Cwmstywth mine,

mined from 1845 to 1928

• More than 4 Mt of mine waste

and tailings deposited

adjacent to Yswth river

• High levels of acid generation on site

from weathering of pyrite

and marcasite

• Some buffering from calcite

and dolomite

• Reported impacts of zinc, cadmium

and acidic pH in receiving water

Case Study: Cwmstywth mine,

Central Wales

• Base metal mineralization associated with faults in Ordovician rocks

• 400 to 350 Ma, Caledonian orogeny

• Mineralogy is galena, sphalerite, chalcopyrite, arsenopyrite, with some pyrite

and marcasite within a quartz, barite and carbonate

• Geological oxidation in Tertiary to Recent, over 40 secondary minerals

Central Wales Orefield

• Mined between 1600 and 1955 for Ag, Pb and Cu

• Predominantly underground

• Liability due to unprocessed ore, discharged

tailings or reactive mine waste, groundwater

rebound in underground mines

History of Central Wales Orefield

Hydrogeochemistry

• Measures of potential

reactivity is paste pH

and paste EC

• Correlation in acidic pH

to leachable solids (EC)

• Potential to correlate

to XRF would allow

easier definition

of reactive mine waste

and define metals

of concern

and magnitude

Material Reactivity Geochemistry

Calibration of XRF instruments

Sample CY1-5

Sample CY1-7

Sample CY1-10

Sample CY1-11

XRF Results Comparison

to Acid Generation Assessment

Comparison to leaching tests, Zinc

Risk Assessment Maps

Leachable Zinc from mine waste,

Contact test/ICP

Total Zinc in mine waste, XRF

Risk Assessment Maps

Total Arsenic in mine waste, XRF

Abuse of portable XRF

in Environmental Studies

26.2% Pb

32% Pb

2.6% Pb

56% Pb

1.9% Pb

1 m

Abuse comes from:

• Utilising the internal calibration of the XRF unit and assuming these recorded

values as reportable – overcome by external calibration

• Matrix effects – overcome by destructive method to homogenize sample

• Bias in In-Situ analysis due to matrix effects- overcome by preparation of

samples

• Mine Waste Studies

o Characterize mine waste geochemistry

o Define impacts to the environment

o Seek to define risk of impacts

o Define toxicity

• Conventional studies require careful selection

of representative samples for laboratory testing

• Portable XRF has potential to be integral

in achieving these goals BUT:

• Require good control over calibration

• Require good mineralogical understanding of material

• Avoid spurious results as a consequence

of selective analysis of In-situ material –

homogenize samples better than many in-situ results

Recommendations

• Good sampling is essential

in an ARDML study

• Requires knowledge of geology

and history of the site, mineralogy

and mining methods

• Needs to be representative

• Different sample medium to collect –

depends on focus of study

• Environmental Geochemistry Studies

benefit from Portable XRF

Summary