Using growth curves to forecast regional resource recovery: approaches, analytics and consistency tests.

There is growing concern about the depletion of hydrocarbon resources and the risk of near-term peaks in production. These concerns hinge upon contested estimates of the recoverable resources of different regions and the associated forecasts of regional production. Beginning with Hubbert, an influential group of analysts have used growth curves both to estimate recoverable resources and to forecast future production. Despite widespread use, these 'curve-fitting' techniques remain a focus of misunderstanding and dispute. The aim of this paper is to classify and explain these techniques and to identify both their relative suitability in different circumstances and the expected level of confidence in their results. The paper develops a mathematical framework that maps curve-fitting techniques onto the available data for conventional oil and highlights the critical importance of the so-called 'reserve growth'. It then summarizes the historical origins, contemporary application and strengths and weaknesses of each group of curve-fitting techniques and uses illustrative data from a number of oil-producing regions to explore the extent to which these techniques provide consistent estimates of recoverable resources. The paper argues that the applicability of curve-fitting techniques is more limited than adherents claim, the confidence bounds on the results are wider than commonly assumed and the techniques have a tendency to underestimate recoverable resources.