Author(s): |
Rodrigo Riquelme, GeoInnova Consultants (CL)
Alejandro Cáceres, GeoInnova Consultants (CL)
Xavier Emery, University of Chile (CL)
Susana Zapata, GeoInnova Consultants (CL)
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Abstract: |
This paper deals with the joint estimation of a set of coregionalized variables, based on a transformation of the variables into minimum/maximum autocorrelation factors, assumed mutually independent, followed by multigaussian kriging in order to separately estimate the local distributions of these factors. The proposed approach is applied to two case studies and the results are compared with the estimations by kriging and cokriging. The first case study deals with the estimation of the total and soluble copper grades in a Chilean deposit, while the second case study corresponds to a lateritic nickel deposit in which six variables (Al2O3, Cr, Fe, MgO, Ni, SiO2) are of interest. The estimation based on minimum/maximum autocorrelation factors shows a significant improvement in the reproduction of the relationships between the variables, in particular concerning the order relationship between total and soluble copper grades, while it considerably reduces CPU time with respect to the co-simulation of the variables.
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