Budget Allocation and the Stopping Problem in Mineral Exploration

Abstract

Most greenfields mineral exploration projects involve a process of testing targets that have been selected on the basis of geoscientific data. Although this data can be used to rank targets, questions still arise as to how many targets should be tested before the area is dropped. This paper addresses this question with a probabilistic model of the exploration process and illustrates the method with a geophysical example. The model is governed by the target and background distributions of the variable used to rank targets, various economic parameters and two geologically determined probabilities. It generates Expected Value, Probability of Success and Return on Investment (ROI) for a range of possible project budgets showing where each is maximized. It is argued that a lower and upper limit for the number of tests to be undertaken can be defined in terms of this model. The lower limit, called the Equal Opportunity Truncation point, occurs where the ROI is maximized and is relevant when other equally attractive prospects are available. The upper limit, called the Economic Truncation point, occurs when the Expected Value is maximized. The kimberlite exploration case study illustrates a new method of estimating the target distribution using magnetic modelling and shows how the probabilistic model could have been used to budget this exploration project.