UKERC Energy Data Centre: UKERC Publications

UKERC Home >> EDC Home >> UKERC Publications >> Back to Results >> Hubberts Legacy: a review of curve-fitting methods to estimate ultimately recoverable resources

Hubberts Legacy: a review of curve-fitting methods to estimate ultimately recoverable resources


Citation Sorrell, S. and J. Speirs Hubberts Legacy: a review of curve-fitting methods to estimate ultimately recoverable resources. 2010. https://doi.org/10.1007/s11053-010-9123-z.
Cite this using DataCite
Author(s) Sorrell, S. and J. Speirs
Opus Title Natural Resources Research
Pages 209-230
Volume 19
DOI https://doi.org/10.1007/s11053-010-9123-z
Abstract

A growing number of commentators are forecasting a near-term peak and subsequent terminal decline in the global production of conventional oil as a result of the physical depletion of the resource. These forecasts frequently rely on the estimates of the ultimately recoverable resources (URR) of different regions, obtained through the use ofcurve-fittingto historical trends in discovery or production. Curve-fitting was originally pioneered by M. King Hubbert in the context of an earlier debate about the future of the US oil production. However, despite their widespread use, curve-fitting techniques remain the subject of considerable controversy. This article classifies and explains these techniques and identifies both their relative suitability in different circumstances and the level of confidence that may be placed in their results. This article discusses the interpretation and importance of the URR estimates, indicates the relationship between curve fitting and other methods of estimating the URR and classifies the techniques into three groups. It then investigates each group in turn, indicating their historical origins, contemporary application and major strengths and weaknesses. The article then uses illustrative data from a number of oil-producing regions to assess whether these techniques produce consistent results as well as highlight some of the statistical issues raised and suggesting how they may be addressed. The article concludes that the applicability of curve-fitting techniques is more limited than adherents claim and that the confidence bounds on the results are wider than usually assumed.