Simulation of mineral grades with hard and soft conditioning data: application to a porphyry copper deposit |
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| Authors: | Xavier Emery Lucía N Robles |
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| Institution: | (1) Department of Mining Engineering, University of Chile, Avenida Tupper 2069, Santiago, 837 0451, Chile;(2) Department of Mining, Metals and Materials Engineering, McGill University, 3450 University St., Montreal, Quebec, H3A 2A7, Canada |
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| Abstract: | This work deals with the geostatistical simulation of mineral grades whose distribution exhibits spatial trends within the
ore deposit. It is suggested that these trends can be reproduced by using a stationary random field model and by conditioning
the realizations to data that incorporate the available information on the local grade distribution. These can be hard data
(e.g., assays on samples) or soft data (e.g., rock-type information) that account for expert geological knowledge and supply
the lack of hard data in scarcely sampled areas. Two algorithms are proposed, depending on the kind of soft data under consideration:
interval constraints or local moment constraints. An application to a porphyry copper deposit is presented, in which it is
shown that the incorporation of soft conditioning data associated with the prevailing rock type improves the modeling of the
uncertainty in the actual copper grades. |
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| Keywords: | Geostatistics Conditional simulation Gibbs sampler Soft conditioning data Spatial trends |
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