Hurricane sample replacement using the inverse distance weighted method

The article discusses the method of hurricane sample replacement taking into account the spatial relationship of other routine samples. This sample is presented as the result of selecting sampling parameters with the mineral content above average values determined using the proposed methodology. The approach is based on geostatistical findings regarding the spatial dependence of sampled subsurface areas within a single geological block. The feature of the proposed methodology is the calculation of the studied indicator taking into account all samples for the evaluated block including the hurricane one. The approach is based on the method for determining weighting coefficients from the inverse distance weighted method. The method has been tested using the exploration data from a placer gold deposit. All key parameters of the proposed method, such as the radius and number of additional points created, as well as the power coefficient of the weighting function are analyzed. Several indicators are identified that will influence the results of mineral reserves calculations taking into account a hurricane sample and when it is replaced by the values calculated using the proposed methodology. The article analyses a situation in which the study object is selected incorrectly. It is demonstrated how the replacement of an outlier value can affect the assessment results for a given geological block. Examples of replacing similar samples are provided along with the assessment of the impact on the change in estimated reserves for a placer gold deposit. A conclusion is drawn regarding the error in determining the hurricane sample with the comparison of the impact on the exploration results and geological block assessment. The article is based on the study of a geological block tested by vertical boreholes, in which the gold content was determined. The results were obtained by modeling the process of determining the values to be used to replace the selected sample. The conducted analysis shows the effect of volume changes for various parameter variants of the proposed method. The article is illustrated with grade-interpolated plots and graphs showing curves for various parameters of calculated indicators.

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