The theory of disjunctive kriging and its application in grade estimate

Linear estimation methods such as ordinary and simple kriging commonly fail to provide unbiased estimates of recovered ore tonnage and metal content which means that a mining project can be exposed to undue risk. Nonlinear estimation, such as the Gaussian disjunctive kriging (DK) technique provide a mean of calculating unbiased estimates of ore and metal content over any cut-off range and mining unit size combination. The disadvantage of this method is the requirement of an assumption of strict stationarity. It supposes that we have known all bivariate distributions of regional variables (Z_alpha, Z _beta) and (Z₀, Z_beta) in which the values of Z_alpha, Z_beta is known and the value of Z₀ is to be estimated. The paper contents of Gaussian anamorphosis, varigram and structure analysis and Hermite polynomials. The application of these estimation methods to a deposit is described. The study carries out DK and ordinary kriging (OK) for a suit of 3D drill data of a multi-metal deposit, containing 63 drills and 2 kinds of metal, from which we can see DK is more perfect and easier. A discussion of the results from a practical point of view is also given