Modeling Dependencies Between Geologic Risks in Multiple Targets

Abstract

Summary A single-target prospect can be characterized probabilistically by two elements: the risk or probability of success and the distribution of reserves given success. But there is no obvious way of combining the results of multiple targets into a single representative assessment. This paper presents a simple approach for aggregating multiple targets for the purpose of prospect ranking. Reserves given success are assumed independent, and the novelty lies in the modeling of dependencies between geologic risk factors. Although interdependence can be represented by conditional probabilities, the selection of these values is a problem for most explorationists. In this paper, a more practical method is proposed. A matrix is completed for multiple targets, specifying which geologic factors are common and which are independent. An outcome tree with dependent targets is created, and the probability distribution of aggregate reserves is determined either analytically or by Monte Carlo simulation. A case study with six targets illustrates the method. Dependencies reduce the probability of at least one success from 92% to 65% and the number of possible outcomes from 64 to 25. This allows a useful grouping by development cases. The method can be used for stacked reservoirs or portfolio analysis.