From The Spatial Sampling Of A Deposit To Mineral Resources Classification
GEOSTATISTICS VALENCIA 2016(2017)
摘要
In the mining industry, estimated mineral resources of a deposit are classified into inferred, indicated, or measured resources, depending upon their level of confidence. From a geostatistical point of view, this depends on the hole spacing and continuity of the mineralization in the deposit or in the different parts of the deposit. This also depends on some nominal volume on which level of confidence is sought. This corresponds typically to an annual expected production volume, not to the next week production block or to the whole deposit (unless it is small). Here we propose a geostatistical classification of mineral resources in two steps. The first step consists in measuring the spatial sampling density of the deposit (or throughout the deposit when this density varies). This is done using a specific volume, which is similar to the inverse of the classical density of sample points in space (this density being a number of samples per volume, its inverse is a volume), but which takes into account the variographic structure of the regionalized variable of interest. This first step allows comparing objectively the spatial sampling density of different deposits or parts of deposit. The second step first converts such a specific volume into a coefficient of variation on the nominal production volume resources. Then a mineral resource category is obtained by thresholding this coefficient of variation. By choosing fixed thresholds for a given commodity and type of deposit, this provides an objective classification of the resources from different deposits or parts of deposits. The proposed method is illustrated on three case studies.
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