sampling issues: getting the right sample · • receptor soil, sediment, water, plants, animal...
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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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10
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0.010.1110100
Sieve Size (mm)
Pe
rce
nt
Fin
er
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