The Cost of Risk and the Value of Information in Mine Planning ? Introduction

There are many methods available for the estimation of geologic parameters (Popoff, 1966; Barnes, 1980). In the last decade a new and relatively sophisticated technique using statistical theory has emerged: geostatistical kriging (David, 1977; Journal and Huijbregts, 1978; Rendu, 1978). An interesting property of geostatistical estimation is that when a geologic parameter is estimated for a given volume, not only is the estimate generated but an associated measure of certainty is produced as well. This statistical measure of estimation confidence is called the estimation variance. While the concept of an estimation variance is universally considered to be a good idea, mining engineers and geologists do not currently have the tools to incorporate it into their planning and quantitative analysis. This paper attempts to develop and present some of the necessary tools required to incorporate estimation uncertainty into mine planning. Geologic uncertainty is portrayed as an economic business risk. This risk is objectively characterized, and-the associated cost is quantified. Geologic delineation sampling is viewed in this light as an economic commodity with an associated cost and value. A coal mine planning example is used as a focus in this presentation. The data used is real, though it has been modified to maintain data security and project anonymity.