A NEW DISCOVERY PROCESS APPROACH TO FORECASTING HYDROCARBON DISCOVERIES

The uncertainty inherent in the exploration process requires that exploration firms try to estimate the results of future exploration in a region before making a commitment to explore. This paper discusses a recent approach derived from an approximation of the mean values of the non-central multivariate hypergeometric distribution. The approximation leads naturally to a differential equation model of the exploration process. A Taylor series expansion results in a polynomial in the discovery number usable as an estimate of the mean value of future discovery amounts. Further considerations suggest a third order polynomial whose coefficients are functions of the underlying geological and behavioural parameters. Linear regression, on data from three partially explored plays, was used to estimate the coefficients, and it produces forecasting models which perform well compared with two other widely used methods. The paper presents a derivation of the differential equation and the third order polynomial model, examples of its use for three plays in Western Canada, and an assessment of the forecasting ability of the model for these plays. The differential equation model is compared in terms of accuracy and bias to the exponential decline and the mean historical discovery rate models and found to produce superior forecasts.