Abstract

The plurigaussian model is increasingly used for simulating geo-domains and quantifying geological uncertainty in the subsurface. However, because they rely on the truncation of only two Gaussian random fields, the current implementations of this model are often restricted in the number of geo-domains that can be simulated and in their contact relationships. A solution to overcome these restrictions is to increase the number of underlying Gaussian random fields. Such an approach yields a very flexible model, able to reproduce the contact relationships between geo-domains in agreement with their chronology (i.e., such that younger geo-domains cross-cut the older ones), as well as the geo-domain proportions and spatial correlation structure. The proposed approach is applied to a dataset from the Rio Blanco copper deposit in the Chilean Central Andes, in which it is of interest to simulate the layout of seven rock units (andesite, granitoid, tourmaline breccia, monolithic breccia, magmatic breccia, porphyry and pipe). The results are used to map the probabilities of occurrence of the rock units and to identify the sectors where the interpreted rock model is uncertain.

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