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Assessment of the Impact of Non-Additivity in the Estimation of Iron Ore Attributes - with narration
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Transcript of Assessment of the Impact of Non-Additivity in the Estimation of Iron Ore Attributes - with narration
Assessment of the Impact of Non-Additivity in the Estimation of Iron Ore
Attributes
Iron Ore 2013, 12th – 14th August 2013
Alastair Cornah
Outline
Planning, development and execution
Value add
Heterogeneous in situ chemical and physical attributes
Homogeneous product chemical and physical attributes
Product marketingDeposit level sequencing and blending
Life of mine planning and sequencing
Production planning and sequencingMining and processingStockpiling and blending
Data collection, but incomplete knowledge
Sparse drillholes
Infill drilling
Blast holes / grade control drilling
Local block models
Global models, local block models
Grade control models
Spatial estimation models
Mean in situ grades
Mean product yields
Mean product grades
Mean in situ grades
Mean product yields
Mean product grades
Destination 2
Destination 1
In situ grades
Product yields
Product grades
variable
Res
ponse
Linear average of data
understates responseR
esponse
variable
Linear average of data
overstates response
Rock Response Properties
Primary Rock Properties
Energy or Process
Primary – Response Framework, modified from Coward et al., 2009.
In situ geochemical grades
Bulk and particle density
Mineral abundances
Material type abundances
Texture
Primary Response
Davis Tube concentrate recovery and grades
Porosity
Dry crush and screen / beneficiation product yields and grades
Material handling, degradation metrics
Sinter performance metrics (TI, RDI, RI)
Compare between:1. The average of the ratios; and2. The ratio of the averages
Additive variables are shown in blue, non additive variables are shown in red using the following notation:
Direct (illegitimate) approach
Samples or nodes Averaged samples or nodes
Indirect (legitimate) approach
Global estimation approach % Fe units recovered to concentrate
% Fe units lost to tails
Direct (illegitimate non-additive procedure)
76.36 23.64
Indirect (legitimate additive procedure)
76.60 23.40
Direct (illegitimate non-additive procedure)
Realisation 5 / 25
Direct (illegitimate non-additive procedure)
Realisation 10 / 25
Direct (illegitimate non-additive procedure)
Realisation 15 / 25
Direct (illegitimate non-additive procedure)
Realisation 20 / 25
Indirect (legitimate
additive procedure)
Realisation 5 / 25
Indirect (legitimate
additive procedure)
Realisation 10 / 25
Indirect (legitimate
additive procedure)
Realisation 15 / 25
Indirect (legitimate
additive procedure)
Realisation 20 / 25
VARIABLE Mean (biased - unbiased)
Realisation 1 -0.2
Realisation 2 -0.2
Realisation 3 -0.21
Realisation 4 -0.23
Realisation 5 -0.35
Realisation 6 -0.29
Realisation 7 -0.28
Realisation 8 -0.24
Realisation 9 -0.34
Realisation 10 -0.23
Realisation 11 -0.17
Realisation 12 -0.67
Realisation 13 -0.24
Realisation 14 -0.11
Realisation 15 -0.4
Realisation 16 -0.65
Realisation 17 -0.33
Realisation 18 -0.43
Realisation 19 -0.12
Realisation 20 -0.19
Realisation 21 -0.86
Realisation 22 -0.57
Realisation 23 -0.04
Realisation 24 -0.39
Realisation 25 -0.1
Residuals, %
(biased – unbiased)
Conclusions and Recommendations
Key References:
Carrasco P., Chiles J.P. and Seguret S., 2008. Additivity, Metallurgical Recovery and Grade. In Geostats 2008: VIII International Geostatistics Congress (eds: J. Ortiz and X. Emery), Santiago, pp.465-476. Springer.
Coward, S., Vann J., Dunham S., and Stewart M., 2009, The Primary-Response Framework for Geometallurgical Variables. In Proceedings Seventh International Mining Geology Conference, pp.109-113. The Australasian Institute of Mining and Metallurgy: Melbourne.
Correspondence: [email protected]