Linear kriging methods fail to estimate local grades and local reserves for highly skewed variables due to three reasons: it uses only part of the available data information, it has no physical principles associated with the mathematical proceedings to minimise the problems, and it works with continuous variables while data are discrete because of the limited precision of any equipment. The techniques commonly used up to now to solve the highly skewed variables estimation problems were unsuccessful, unless mathematical rigor is abandoned. Even the method of multiple indicator kriging is not satisfactory. This paper presents a new framework, the fi eld parametric geostatistics (FPG) that transforms noisy variograms into well-behaved variograms and justifi es mathematically empirical procedures commonly used, as trimming or capping arbitrarily very high values. The method, when applied to non-skewed variables, yields similar results to classic kriging. The methodology is illustrated in a case study at a gold deposit in Brazil, and compared to results obtained by usual techniques.
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