A Strategy for Implementing Risk Analysis

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Summary This paper proposes five risk analysis models for analyzing drilling prospects. The models range from a simple, two-outcome analysis (Level 1) to a full Monte Carlo simulation risk model (Level 5) that takes into account all geologic and economic uncertainties. The five levels offer an orderly plan for implementing risk analysis techniques in drilling prospect evaluations. Explorationists can enter the progression at any point, and then gradually expand and enlarge the scope of their evaluation model by following the stepwise progression. Introduction "How do I get started using risk analysis?" "We've been using a two-outcome risk evaluation model: dry hole or a discovery. We would now like to expand our risk assessment procedures. What is the next step for us?" "Is there a simple, first step for using Monte Carlo simulation? " Over the past 10 years petroleum exploration risk analysis has become a popular and topical subject in books and journals. As we extend our search for petroleum to the smaller, harder to find traps we have petroleum to the smaller, harder to find traps we have become increasingly aware of the risks of exploration. Uncertainties about future crude prices, inflation rates, supply and demand forecasts, etc. add to our concerns when evaluating exploratory and development well drilling prospects. Despite this increased awareness of risk and uncertainty, the actual use of quantitative risk analysis techniques vanes considerably. Some use sophisticated Monte Carlo simulation techniques. For many, though, quantification of risk consists only of making a statement about the chance of discovery, such as "we have a one-in-four chance of making a well."In this paper, I outline a systematic progression of five different levels, or models, for analyzing drilling prospects. Level 1 is a basic, two-outcome model prospects. Level 1 is a basic, two-outcome model representing one end of the risk model spectrum. Succeeding levels are increasingly comprehensive, extending finally to a full Monte Carlo simulation analysis in Level 5. This final model represents a state-of-the-art risk evaluation that can account for all uncertainties relating to geologic and economic factors. Five levels are proposed because they offer an orderly plan for implementing risk analysis. You can enter the plan for implementing risk analysis. You can enter the progression at the point of your present analysis method, progression at the point of your present analysis method, and then gradually expand and enlarge the scope of the analysis by following the stepwise progression. If you are just getting started you can begin at Level 1. The five models can be used for evaluating any management strategy for a given prospect such as drilling, farm out, electing to take a back-in option or dry hole contribution, etc. The models are also completely general in the sense they can be used for any type of drilling prospect whether gas, oil, offshore, onshore, exploratory well, or development well. Note, however, that because of the nature and magnitude of the uncertainties involved probably only Levels 4 or 5 will be adequate for offshore and frontier exploration prospects. General Model Characteristics All five risk models outlined here have several common features and assumptions. First, the models are based on the premise that the desired decision-making parameter is an expected value profit measure. "Expected valued" here is used in the sense of the fundamental concept of mathematical expectation-the cornerstone of all formalized strategies for decision making under conditions of uncertainty. An expected value profit is a weighted-average profit, where the weighting factors are the probabilities of occurrence of each possible outcome. Calculation consists of multiplying the profit (or loss) associated with each possible outcome by its respective probability of possible outcome by its respective probability of occurrence. These product terms then are summed algebraically to give the expected value profit (or loss) of the decision strategy. This decision-making parameter is usually given as the expected monetary value profit (EMV) of the option. The decision rule is to accept the decision alternative if its EMV is positive and to reject the alternative if its EMV is negative. For ranking purposes, alternatives that maximize positive EMV are selected. Expected value profit is the only criterion available that allows us to profit is the only criterion available that allows us to incorporate quantitative statements of risk (probabilities) into the evaluation process. For this reason the five risk models are structured to yield an EMV as the final decision-making parameter. For a more in-depth review of the expected value concept, see Chap. 3 of Ref. 1. There are two general types of models proposed. The first three models in the progression are discrete-outcome models, which take account of two or more discrete outcomes occurring. JPT P. 1791