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Geostatistical estimation of orebody geometry: Morphological kriging
Authors:Amilcar Soares
Institution:(1) CVRM, Technical University of Lisbon, IST, Av. Rovisco Pais, 1096 Lisboa Codex, Portugal
Abstract:Most geostatistical approaches to the estimation of orebody geometry fail to make full use of the morphological information available and, as such, provide very simplistic and often unsatisfactory models of the shape and location of the orebody. The purpose of this paper is to describe a method of kriging an indicator variable subject to certain morphological information and then transforming the estimates into a binary map; the technique is termedmorphological kriging. Two case studies are used as examples to show that the method reproduces the morphological characteristics of the orebody, in so far as they can be conveyed by the information contained in the samples, while minimizing the smoothing effect of the estimator.
Keywords:morphological kriging  geometric model  probability map  binary map
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