Use of Quantitative Risk Analysis for Uncertainty Quantification on Drilling Operations-Review and Lessons Learned

Author:

Cunha Jose C.S.1,Demirdal Barkim,Gui Ping

Affiliation:

1. U. of Alberta

Abstract

Abstract This paper presents comments and some background on the use of risk analysis methods in the oil and gas industry. Particularly attention is given to applications developed specifically for drilling operations. A literature review emphasizing articles written specifically for risk analysis applications on oil & gas well drilling operation is presented. Recommendations for procedures related to risk analysis methods implementation as well as an example of application and its results are presented. A Monte Carlo simulation was run to predict a cumulative distribution function for a well drilling AFE (Authorization For Expenditure.) The simulation procedure as well as the resultant function is presented. Introduction Back in 1975, an article about "the use of new quantitative evaluation methods" was published[1]. The title of the article, "Risk Analysis - Is it Really Worth the Effort?", somehow reflected the frustration of the author, one of the pioneers on the subject2, with the fact that, by then, many would feel that decision making is a managerial process that could not be quantified by statisticians dealing with complex and hard-to-grasp concepts. After thirty years it would probably be safe to assert that the use of quantitative risk analysis methods for investment decisions is widely adopted by oil companies. Also, certain petroleum engineering technical areas, like reservoir engineering, benefit of the use of risk analysis on the planning and development of oil fields and on reservoir management. Conversely, other technical areas that decidedly would benefit from the use of the same tools do not make use of it on a consistent way. In this paper specific risk analysis applications for drilling engineering processes will be analyzed. A literature review on some important applications as well as an example of application is presented. Some suggestions on how to implement risk analysis methods for drilling are discussed. Literature Review Risk analysis is a very powerful tool for certain engineering processes where decision under uncertainty is involved. Specifically for oil well operations, a number of articles have been presented illustrating how risk analysis methods can be used to maximize the possibility of adopting, for a certain operation, the correct decision. For drilling operations, even though not extensively used, a variety of applications have been developed. In this section a review of those important applications is presented. Newendorp and Root[2] conducted a pioneer study on the possibility of using risk analysis methods while deciding on drilling investments, which involves a dedication of significant amount of capital under highly uncertain conditions. Authors suggested that, instead of reaching decisions qualitatively under the influence of subjective observations in a personal and intuitive process, a decision theory technique could be used making possible to asses and estimate the risks associated with drilling investments, quantitatively. Since risks associated in drilling investments contain uncertainties due to geological and engineering factors that affect profitability of investment, it is wiser to estimate range and distribution of possible outcomes of a drilling investment to investigate the profitability of a prospect. Authors stated that the method would minimize subjective decisions and conclusions for a drilling investment project. With the use of the method, effects of unlimited number of variables on drilling prospects can be analyzed, sensitivity analysis can be conducted and variables highly affecting the profitability could be isolated and better analyzed. The proposed method is much more sophisticated, objective and precise for assessment of drilling prospects than the type of qualitative analysis commonly used by the time of publication of the article.

Publisher

SPE

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