Abstract
The resource classification system helps protect producers and consumers from ambiguous reporting of mineral resources. Classification systems have been introduced in many countries, but they are often general, so they are not easy to apply in the field. Geostatistical approaches are often inaccurate on data with high nugget values. The system requires sophisticated knowledge and takes time to understand, while field practitioners are eager to immediately get mineral resource classification results. This study aims to introduce the average distance from the borehole as a mineral resource classification parameter. In this study, modeling and grade estimation uses a block model with nearest-neighbor polygon and inverse distance weighing techniques as grade estimation techniques. The highest weight in the NNP estimation technique is the closest sample, while the IDW weight depends on the distance; therefore the NNP and IDW techniques use distance considerations only. Based on the histogram of the average distance, the populations in the graph show the classification as inferred resources, indicated resources, and measured resources. The application of the average distance technique for the classification of laterite nickel resources uses the block model.
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