Maximum likelihood estimates of the size distribution of North Sea oil fields
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Estimates of the ultimate resource potential of the North Sea petroleum province are derived from a probabilistic model of the discovery phenomenon. The discovery of individual fields are treated as sampling without replacement from a target population (the underlying resource base), and with individual discovery probabilities defined in terms of field size. Dependent on the underlying resource base, the model specifies the likelihood of all possible sequences of discoveries. Conversely, upon observing a particular discovery sequence, it is possible to identify the underlying resource base that maximizes the likelihood of this event. The present paper examines the sensitivity of such resource estimates to the postulated form of the size distribution of fields, and to the presumed degree of randomness inherent in the discovery process.
Key wordsResource potential maximum likelihood field size
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- Adelman, M. A. and Jacoby, H. D., 1979, Alternative methods of oil supply forecasting,in (R. Pindyck, ed.), Advances in the economics of energy and resources, vol. 2: JAI Press, Inc., Greenwich, Conn., p. 1–38.Google Scholar
- Arps, J. J. and Roberts, T. G., 1958, Economics of drilling for cretaceous oil on east flank of Denver-Julesburg basin: Bull. Amer. Ass. Pet. Geol., v. 42, p. 2549–2566.Google Scholar
- Barouch, E., and Kaufman, G. M., 1976, Probabilistic modeling of oil and gas discovery,in (F. Roberts, ed.): Energy, mathematics, and models, Society for Industrial and Applied Mathematics, Philadelphia, p. 133–150.Google Scholar
- Cozzolino, J. M., 1972, Sequential search for an unknown number of objects of nonuniform size: Oper. Res., v. 20, p. 293–308.Google Scholar
- Eckbo, P. L., Jacoby, H. D., and Smith, J. L., 1978, Oil supply forecasting: A disaggregated process approach: Bell J. Econ., v. 9, p. 218–235.Google Scholar
- Kaufman, G. M., 1975, Models and methods for estimating undiscovered oil and gas—What they do and do not do,in (M. Grenon, ed.), First IIASA conference on energy resources: International Institute for Applied Systems Analysis, Laxenburg, Austria, p. 237–249.Google Scholar
- Kaufman, G. M., Balcer, Y., and Kruyt, D., 1975, A probabilistic model of oil and gas discovery,in (J. D. Haun, ed.), Methods of estimating the volume of undiscovered oil and gas resources, (Studies in Geology No. 1) American Association of Petroleum Geologists, Tulsa, Oklahoma, p. 113–142.Google Scholar
- Kaufman, G. M., and Wang, J. M., 1980, Model mis-specification and the Princeton study of volume and area of oil fields and their impact on the order of discovery, M.I.T. Energy Laboratory Working Paper No. MIT-EL 80-003WP.Google Scholar
- O'Carroll, F. M., and Smith, J. L., 1980, Probabilistic methods for estimating undiscovered petroleum resources,in (J. Moroney, ed.), Advances in the economics of energy and resources, v. 3: JAI Press, Inc., Greenwich, Conn., p. 31–63.Google Scholar
- Smith, J. L., 1980, A probabilistic model of oil discovery: Rev. Econ. Stat., v. 62, p. 587–594.Google Scholar