A consistent probabilistic definition of reserves
Uncertainty begs for a probabilistic treatment, and almost no business is filled with more uncertainty than that of the petroleum technologist in quest of oil and gas volume estimates. As in most uncertain endeavors, no single number captures the range that describes the lack of knowledge. Fortunately, the petroleum business has a mathematical ally, the central limit theorem. When one multiplies variables (reservoir thickness, reservoir length, reservoir width, porosity, saturation, percent of hydrocarbon in place that can be produced with present technology and prices) one very quickly approaches the log-normal distribution. One can make the estimates of proved, probable, and possible reservoirs all consistent if one makes sure that each lies on the same log-normal probability distribution. Still other improvements can be made if one takes these distributions for wells (or the basic unit on which they estimate reserves) and adds the entire distribution to get reservoir, field, or company reserves. Simply adding proved reserves has never been a mathematically legal operation and ought to cease as quickly as possible. By striving for a distribution answer, one can supply the kinds of numbers from ``very safe`` to ``this is a dream`` that will satisfy the various constituencies requiring volume information--governments, management, explorationists, bankers, and others. Still better, when estimates have probabilistic definitions, it is also possible to generate performance measures that hold the estimators to their promises.
- Sponsoring Organization:
- USDOE
- OSTI ID:
- 194733
- Journal Information:
- SPE Reservoir Engineering, Vol. 11, Issue 1; Other Information: DN: Paper presented at the 1993 SPE Hydrocarbon Economics and Evaluation Symposium, Dallas, TX, March 29--30; PBD: Feb 1996
- Country of Publication:
- United States
- Language:
- English
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