understanding ore heterogeneity: in-situ and in broken ore
DESCRIPTION
Understanding Ore Heterogeneity: In-situ and in Broken Ore. Dr Geoff Lyman Materials Sampling & Consulting Southport, Queensland. Overview. What is heterogeneity? How do we quantify heterogeneity? How does it impact exploration? How does it impact mining and beneficiation? - PowerPoint PPT PresentationTRANSCRIPT
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Understanding Ore Heterogeneity:
In-situ and in Broken Ore Dr Geoff Lyman
Materials Sampling & ConsultingSouthport, Queensland
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Overview
• What is heterogeneity?• How do we quantify heterogeneity?• How does it impact exploration?• How does it impact mining and
beneficiation?• How does it impact analytical procedures?
• How to control the impact• Tools to evaluate heterogeneity
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Heterogeneity
• Heterogeneity must be defined with respect to a particular analyte – a mineral phase or an elemental concentration
• In a broken ore:– particles vary in size, composition and density– it is the extent of variation in composition from
one particle to the next that controls the extent of heterogeneity
– we call this type of heterogeneity intrinsic heterogeneity
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Intrinsic Heterogeneity
Size 1 Size 2 Size 3
Size 4 Size 5 Size 6The extent of liberation of the target phase increases as particle size
decreasesand so does the heterogeneity
pure ‘other’
pure ‘targe
t’
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Intrinsic Heterogeneity
• Quantification of particulate heterogeneity– In statistics, we measure variability using the
variance of a probability distribution
2var x p x x x dx x x
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Intrinsic Heterogeneity
• Quantification of particulate heterogeneity– within a size fraction, we measure intrinsic
heterogeneity much the same way, except we include particle density
1 2
0
L
L
a aIH y a aa
2
1
CN
j Lj j
Lj
a aIH y
a
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Intrinsic Heterogeneity
• Quantification of particulate heterogeneity– For a sample as a whole, the intrinsic
heterogeneity is characterised uniquely by a ‘sampling constant’,
– The sampling constant has units of mass (grams)
SK
12
1 1
S
S C
N
S i i iiN N
ij Li i ij ij
Li j
K x v IH
a ax v y
a
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varS S
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Intrinsic Heterogeneity
• Quantification of particulate heterogeneity
1
2
1
S C
ij Lij ij
Li
N N
Si j
iKa
va
yxa
mass fraction in the size fraction
average volume of a particle in
the size fraction
IH of the material in the size fraction
The particle size effect is very important: it is usually the top 2 or 3 size fractions that control the value of the sampling constant
Potential problem: dilution of ore by waste
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Intrinsic Heterogeneity
• Quantification of particulate heterogeneity– The value of the sampling constant will vary
from one analyte to the next– mineral phases present in low concentration
generally have larger sampling constants• nuggetty gold is a clear example of this
– the mineral phase with the highest sampling constant will usually control sampling protocol design, unless degraded precision for that phase can be tolerated
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Intrinsic Heterogeneity
• Gy’s Simplified Formula– The simplified formula
is
• the critical factor is the determination of the liberation factor l.
• The plot at the right shows that this can be a complex issue and that simplifications can misleading
395SK cfg d
data of Pedro Carrasco (Codelco)
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Heterogeneity
• Sampling a process stream or ROM ore– When we sample a process stream or use an
on-line analyser on the stream, we see deviations from the average grade for the analyte
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Distributional Heterogeneity
• Sampling a process stream or ROM ore– The type of heterogeneity exhibited is called
distributional heterogeneity as it is a variation in time or position along the conveyor belt
– To statistically characterise the variation, we use a variogram or a covariance function
– With the variogram, we can calculate how often we need to sample the process stream in order to control the sampling variance due to distributional heterogeneity
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Distributional Heterogeneity• Sampling a process stream or ROM ore– The shorter the variogram range, the shorter
the time between increments to control the variance
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Heterogeneity
• Sampling a process stream or ROM ore– When sampling a particulate stream, the total
variance is the sum of the distributional heterogeneity variance and all intrinsic heterogeneity variances from the primary sample right down to the selection of the analytical aliquot plus the analysis variance
1 2
var var var var var var LaliquotS DH IH IH IH analysisa
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In-situ Heterogeneity
• In-situ Heterogeneity (in the ore body)– The total picture of variability is captured in the
variogram and variability is a combination of distributional heterogeneity and intrinsic heterogeneity
Sill
Nugget
Range
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In-situ Heterogeneity
• The nugget variance has two parts– The variance of sample preparation and
analysis when the core is split and crushed for assaying• if the preparation protocol is inappropriate, this
variance can be high and dominate the nugget variance
– The ‘geological’ component of nugget variance• this variance can be conceptualised as the variance
between assays of the 2 splits of the core, after subtraction of the preparation and analysis variance
• this variance depends on the texture of the ore and the size of the core sample
Nugget
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In-situ Heterogeneity
• The sill – nugget variance– This difference is the spatially regionalised
variance – It is relevant to how densely the ore body
should be sampled to define block grades with an acceptable block estimation variance
– If the nugget variance is high, it makes capture of the regionalisation difficult and makes estimation of the variogram shape and range difficult
Sill - Nugget {
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In-situ Heterogeneity
• To quantify in-situ heterogeneity, we can consider the following:– choose a standard block size– define an acceptable relative variance for the
block estimation variance,– choose a standard sample size (core diameter
and length)
– determine the total mass of standard samples per block that provides the target relative estimation variance
2 2 x
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Exploration Impact
• In exploration, there are two objectives:– define the ore body structure/continuity– provide preliminary data for variography which
leads to estimates of the value of the resource• For an critical analyte showing a high nugget
value (for any reason), both objectives are compromised– There is motivation to establish a geological
nugget variance in each domain and reduce it to a reasonable value by choice of sample and core size
– Similarly, sample prep protocol can be optimised
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Mining and Beneficiation Impact
• Failure to solve heterogeneity issues at exploration will lead to poor planning of infill drilling for the resource model and degrade the block model – this will affect the mine plan and definitions of ore
and waste– the design of the beneficiation plant and pre-plant
ore blending facilities may be adversely affected– project risk increases in a manner that may be
difficult to quantify
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Impact on Analytical Procedures
• If the heterogeneity of the ore from each domain is well-understood, optimal sample prep protocols can be devised for each domain– sample prep variance can be minimised– the variance due to the intrinsic heterogeneity
of the analytical aliquot in conjunction with the analysis variance can be minimised
– optimal analytical procedures result• optimal aliquot mass• optimal analytical method
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Controlling Heterogeneity
• For each domain– The intrinsic heterogeneity of the
ore is estimated at a series of material top sizes
– The impact of dilution of ore by waste is assessed
– The sample mass retained at each stage of sample preparation is determined to control the total preparation variance
– This work will support exploration as well
2 21 DH IH1SK
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22 IH
23 IH
24 IH
5SK25 IH
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Tools for Heterogeneity Evaluation
• Until recently, heterogeneity evaluation had to be done by analysis of many replicates– this is expensive and needs to be corrected for
preparation and analytical variance to get the correct value of at a given state of comminution
• It is now possible to use the Qemscan to determine heterogeneity for particle top sizes less than about 5 mm– three or four points on the curve of vs
can be determined first followed by other tests at larger sizes as necessary
SK
3SK d d
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Tools for Heterogeneity Evaluation
• For low concentrations of analyte:– Qemscan ‘bright phase’ searches can be run– Preconcentration of heavy mineral phases can
be used as well• All the work should be guided by the
mineralogists and geologists
Mineralogy, Texture, Heterogeneity
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Summary
• Intrinsic heterogeneity impacts all sampling
• Distributional heterogeneity impacts exploration work and sampling from process streams
• A full set of tools exists to evaluate heterogeneity in a quantitative manner– these are assisted by a careful evaluation of
ore textures and domains• Control of data accuracy reduces project
risk