Compositing and regularization of drillhole data for geostatistical resource estimation

The Southern African Institute of Mining and Metallurgy
L. W. Palmer
Organization:
The Southern African Institute of Mining and Metallurgy
Pages:
7
File Size:
1120 KB
Publication Date:
Jul 10, 2024

Abstract

Compositing or regularization of drillhole data is common practice in mineral resource estimation and is deemed a necessary step in producing unbiased estimates of mineral resources and reserves. Commonly, data are collected over irregular distances due to the varying relative thicknesses of lithologies drilled or sampling/assaying strategies. This necessitates data transformation to regular lengths of equal size to ensure that all data have the same sample support. However, there have been few detailed publications on the effect of this process on the composited data that are subsequently taken forward for the estimation process. In this paper, three currently available compositing methods are reviewed and the effects of inappropriate compositing methodologies presented. It is shown through a case study that compositing samples to different lengths leads to changes in the average and variance of the grades in the drillcores in the dataset, which will impact the final estimated value. These differences are exacerbated by breaks or gaps in data where, for a variety of reasons, there has been no data collection or data have been lost. The importance of appropriately treating blank and zero data is also presented. Globally, these differences might be minimal, but locally may be substantial, affecting the efficiency of the estimation and subsequent use of the results in, for example, mine planning and reconciliation. Further detailed investigation of compositing practices is required if the full implications of compositing are to be understood and any induced bias effectively defined.
Citation

APA: L. W. Palmer  (2024)  Compositing and regularization of drillhole data for geostatistical resource estimation

MLA: L. W. Palmer Compositing and regularization of drillhole data for geostatistical resource estimation. The Southern African Institute of Mining and Metallurgy, 2024.

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