A Decision Criterion for Drilling Investments

Abstract

American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc. This paper was prepared for the 43rd Annual Fall Meeting of the Society of Petroleum Engineers of AIME, to be held in Houston, Tex., Sept. 29-Oct. 2, 1968. Permission to copy is restricted to an abstract of not more than 300 words. Illustrations may not be copied. The abstract should contain conspicuous acknowledgment of where and by whom the paper is presented. Publication elsewhere after publication in the JOURNAL paper is presented. Publication elsewhere after publication in the JOURNAL OF PETROLEUM TECHNOLOGY or the SOCIETY OF PETROLEUM ENGINEERS JOURNAL is usually granted upon request to the Editor of the appropriate journal provided agreement to give proper credit is made. provided agreement to give proper credit is made. Discussion of this paper is invited. Three copies of any discussion should be sent to the Society of Petroleum Engineers office. Such discussion may be presented at the above meeting and, with the paper, may be considered for publication in one of the two SPE magazines. Abstract This paper discusses utility theory and the corollary notion of expected utility as a decision criterion for drilling investments. The nature and historical background of utility theory are described. It is shown that expected utility is a logical extension of mathematical expectation. Expected utility has the distinct advantage [compared with expected monetary value and other well known measures of investment worth] of quantitatively treating certain preferences and biases of the decision maker. A numerical example is included to illustrate how utility theory can be incorporated into drilling investment evaluations. One problem in implementing utility theory has been the lack of suitable methods of constructing the function [utility curve] which describes the decision maker's preferences for monetary profits and losses. Past research efforts on this problem are summarized. In a recent university research project, a new method of constructing utility curves was developed and is briefly reviewed. This new method appears adequate to permit an attempt to implement utility theory on a trial basis. Suggestions for such a trial are given. Introduction The decision process in which corporate funds are allocated to specific exploratory and development well investment opportunities consists of two sequential steps. Initially, the petroleum explorationist considers the probable geologic conditions that might occur probable geologic conditions that might occur at the proposed location. These conditions are translated to financial profits [or losses], and if the location appears to offer some degree of profit potential, it is submitted to management. This portion of the decision process is usually performed by the professional process is usually performed by the professional staff and might be called the "predictive phase". phase".After the prospect has been presented to the decision maker, he must associate some measure of value to the probable financial outcomes and evaluate how these measures of value relate to the current goals and policies of the firm. This final step involving management personnel might be called the "value phase" of personnel might be called the "value phase" of the decision process. This paper will be concerned with the value phase of exploratory and development well decision processes. The decision maker's reactions to the probable financial outcomes of a prospect are probable financial outcomes of a prospect are influenced by such factors as the firm's current asset position, corporate goals, and his preferences regarding risk. Certainly, these preferences regarding risk. Certainly, these and other factors are considered in every drilling investment decision.

70 years of machine learning in geoscience in review

“…Some selected examples of early applications of Markov chains are found in sedimentology ( Schwarzacher, 1972 ), well-log analysis ( Agterberg, 1966 ), hydrology ( Matalas, 1967 ), and volcanology ( Wickman, 1968 ). Decision tree-based methods found early applications in economic geology and prospectivity mapping ( Newendorp, 1976 ; Reddy & Bonham-Carter, 1991 ).…”