The Use of Computerized Statistical Data in Risk-Appraised Economic Analysis of Oil and Gas Prospects

Abstract

Summary Historical statistics provide a unique tool for quantifying acceptable ranges of success probability for use in expected monetary value (EMV) risk analysis. By storing statistical information on computer files, the analyst can quickly compare a given prospect with the historical performance in the surrounding area, examine the difference between performance in the surrounding area, examine the difference between technical and commercial success, perform sensitivity and threshold analyses, and compare perceived risk levels with the statistical norm. Introduction With the current uncertainty in the oil and gas industry regarding price and cost forecasting and regulatory changes, the need to effectively evaluate not only the economic rewards but also the perceived risk levels of exploration ventures is critical to effective decision making. At a time when many companies are introducing austerity measures, cost savings and productivity of technical staff are under increasing scrutiny. Readily available statistical data can be used to address both issues by aiding the engineer and geologist to simplify and thereby speed up the process of risk-factor determination and lend support to the reasonableness of the determination. As noted by Campbell and Hubbard, productivity improvement through streamlining the evaluation process is a major cost-saving factor. The willingness to take risks depends upon both the odds and the stakes. In the oil and gas industry, the stakes are usually well defined as an anticipated volume of hydrocarbons that is based on geological mapping and relatively well-known drilling and extraction costs. Forecasts of future costs and product prices normally are fixed as part of corporate policy. The problem then becomes how to quantify the odds and what to do with them once they are quantified. Two basic approaches may be taken in prospect analysis. The deterministic approach derives a single answer. The probabilistic approach, as represented by the Monte Carlo simulation, analyzes the effect of input-parameter uncertainty by combining ranges and distributions and computing an outcome probability value and distribution. In densely drilled areas, the ranges of uncertainty are narrow and the results of the Monte Carlo simulation and those derived from deterministic methods should approach coincidence. For an undrilled prospect, both methods require the application of a risk factor that represents the probability that oil or gas will be present in the quantities that have been modeled. It is a misconception to equate simulation with risk analysis because the simulation computes occurrence probabilities for given volumes, while the success probability can be thought of as the probability of whether that volume contains hydrocarbons. There are many types of uncertainty, many methods for attempting to evaluate uncertainty, and many different expressions of the result. This paper concentrates on risk analysis in its simplest form-a simple two-outcome deterministic model-and examines how historical drilling statistics can be manipulated to provide benchmarks that will assist the analyst in the determination of acceptable ranges for success probability. Also discussed are the different ways of mathematically handling a derived success ratio, including a comparison of results from commonly used methods in the industry. In most established onshore U.S. basins that have an extensive history of drilling and production, the deterministic approach can be used with reasonable accuracy. Although it is usually advisable to run several cases (perform sensitivity analysis), a deterministic approach does have the advantage because it arrives at a single answer that is compatible with the normal process of decision making. The probabilistic approach defines an outcome distribution that is more difficult to grasp and interpret. Analysis Techniques The procedures used by individuals and companies evaluating oil and gas exploration and development opportunities vary considerably. For the purpose of discussion, I have listed areas of analysis carried out in my company for assessing the merits of an exploration opportunity.Relevant data are assimilated from both the originator of the exploration opportunity and the public domain. This information includes as a minimum the offering terms, the well prognosis, an authorization for expenditure, and supporting prognosis, an authorization for expenditure, and supporting information on marketing any oil and gas discovery.Regional statistical information based on data either supplied by the prospect originator or from the public domain will be assimilated. JPT P. 583