A Case Study on the Use of Geostatistical Simulation to Support Drill Hole Spacing Decisions

2019

Felipe Cabral Pinto, Centre for Computational Geostatistics, University of Alberta; Clayton V. Deutsch, University of Alberta

At all stages of a mineral project, decisions need to be made that are based on the data available. Improved decisions often call for a better understanding of the local geology and distribution of rock properties.  An important issue is to assess the correct amount of data necessary to support a decision. Of the data typically available, the information gathered from drilling is the most direct approach to understanding the mineral deposit.  The uncertainty away from the drill holes depends on the nature of geological variability, the data spacing and the scale being considered.  A geostatistical simulation approach can be used to quantify uncertainty and help understand these dependencies.  This paper presents a case study of drill hole spacing versus uncertainty that includes geological and multivariate grade modelling.
Mots Clés: Geostatistics, Drill Hole Spacing, Uncertainty Modeling, Resources Classification, Geostatistical Simulation
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