FANG, J. H., Department of Geology, Univ. of Alabama, Tuscaloosa, AL; C. CHEN, Department of Computer Science, Univ. of Alabama, Tuscaloosa, AL; and Y. HSU, Chinese Petroleum Corp., Taiwan, ROC

ABSTRACT: Field-Size Assessment: Comparison of Old (Bayesian Theorem) and New (Fuzzy Set) Approaches

Prediction of future discoveries of hydrocarbons are of great importance in planning and policy-making in the petroleum industry. Exploration trends are the combined result of two independent factors--success (or discovery) rate and field size. Experience has shown that the field size plays a greater role in defining the shape of the discovery trend than does the success rate.

In this paper, we address field-size assessment of a prospect by comparing the traditional approach of employing the concept of subjective probability based on Bayesian theory and a novel possibility approach grounded in fuzzy set theory.

In the Bayesian method, a priori probability estimate is made from the data already available, coupled with the geologist's subjective judgment. This estimate is then updated using additional information to yield a posteri estimate. We will show how this is done with a real example (although the location is not revealed for proprietary reasons).

Then, we introduce the concept of possibility theory vis-a-vis probability theory. The fundamental difference between the two approaches is that the uncertainty arising in the field-size assessment comes from incomplete information, rather than due to randomness of data.

We will illustrate the workings of both approaches with a case study and demonstrate the superiority of the latter method employing fuzzy set theory.

AAPG Search and Discovery Article #90987©1993 AAPG Annual Convention, New Orleans, Louisiana, April 25-28, 1993.