Abstract
Multivariate conditional simulation is used to assess the multivariate grade risk in mineral deposits. With the presence of several spatially correlated attributes, it is important to ensure that their joint simulation is carried out properly and that the observed spatial correlation is reproduced in the realizations. The method of minimum/maximum autocorrelation factors (MAF) is a well established and practical technique that can be used for this purpose. MAF offers tremendous advantages over standard full cosimulation, principal component analysis, and stepwise techniques. In what follows, a detailed review of the MAF technique, its applications, and examples are provided to guide the practitioner on its use.
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Rondon, O. Teaching Aid: Minimum/Maximum Autocorrelation Factors for Joint Simulation of Attributes. Math Geosci 44, 469–504 (2012). https://doi.org/10.1007/s11004-011-9329-6
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DOI: https://doi.org/10.1007/s11004-011-9329-6