A NEW DISCOVERY PROCESS APPROACH TO FORECASTING HYDROCARBON DISCOVERIES

The uncertainty inherent in the exploration process requires that expl oration firms try to estimate the results of future exploration in a r egion before making a commitment to explore. This paper discusses a re cent approach derived from an approximation of the mean values of the non-central multivariate hypergeometric distribution. The approximatio n leads naturally to a differential equation model of the exploration process. A Taylor series expansion results in a polynomial in the disc overy number usable as an estimate of the mean value of future discove ry amounts. Further considerations suggest a third order polynomial wh ose coefficients are functions of the underlying geological and behavi oural parameters. Linear regression, on data from three partially expl ored plays, was used to estimate the coefficients, and it produces for ecasting 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 p lays in Western Canada, and an assessment of the forecasting ability o f the model for these plays. The differential equation model is compar ed in terms of accuracy and bias to the exponential decline and the me an historical discovery rate models and found to produce superior fore casts.