Drillhole spacing determination with value of information

Abstract

Different quantities of information are available at various stages of the development of a mining project. Consequential decisions are made given the data available at the time. Geological uncertainty due to sparse data presents economic risk. The collection of additional information reduces geological uncertainty leading to a better technical decision and greater value. Subjectivity in the choice of data collection scheme may lead to sub-optimal outcomes. The value of information (VOI) allows a decision-maker to quantify the future value data could provide before collecting it. Evaluating many future configurations over a range of data spacings identifies the optimal outcome given the value metric. The optimal data spacing represents the balance between the cost of uncertainty and the cost of information. A framework for establishing VOI in a mining context is proposed. A geostatistical “resample and resimulate” approach is adopted: the resampling of simulated realizations provides access to virtually any future data configuration. The difference in value generated with future information and the current information is the VOI. The methodology and techniques developed in this paper are applied to a synthetic example and an operating mine case study. The case study encompasses VOI principles, data spacing, engineering design parameters, and economic factors.