The Value of Information in Mineral Exploration Within a Multi-Gaussian Framework

Abstract

In mineral resource evaluation a careful analysis and assessment of the geology, assay data and structural data is required. One important question is where to position the exploration boreholes, another is what method to use when analyzing the grade in the collected material. Here, a challenge of this type is whether one should analyze the collected core samples with accurate and expensive lab equipment or a simpler hand-held meter. A dataset of about 2000 oxide observations is available, along with relevant explanatory variables, from a deposit in Norway. A Gaussian geostatistical model is used to predict the grade parameter on block support. To improve the predictions, several new boreholes are planned, giving 265 additional samples. The associated uncertainty reduction is evaluated, and a resource evaluation is performed with and without the planned data. Then the value of information of the planned data is computed, using assumed costs, recovery rates and revenues. The data acquired with the hand-held meter has almost the same value as the more expensive acquisition strategy, given that the already established correlation between the two datasets is valid.