Meaningful risk analysis can be a tedious task to perform for many reasons, yet extremely rewarding. Lack of information, uncertainty surrounding risk parameters and their distributions, failure to define proper correlations relating some risk parameters, inappropriate selection of risk analysis criterion and misinterpretation of results are among these reasons. Risking net cash flow (NCF), through traditionally approaches can be a leap of faith. Rather, NCF should be treated with more subjectivity and in-depth understanding of all risk parameters and their interrelationships. Current practice of risk management in the petroleum industry adopts schemes that aim at separating risk into two main categories to understand, simplify, analyze, and evaluate existing contingencies. Commonly, the first category is referred to as subsurface risk that includes resource size, production rate, and access cost. Category two is surface risk that demonstrates total expenditure, facilities delivery, delays, performance, oil/gas prices, etc. Risk analysis of each is normally performed alone. Our study shows that separating risks for an investment with a singular outcome is misleading and extremely dangerous. In this paper, we introduce comprehensive criteria for handling risk associated with oil and gas exploration as well as development of mature reservoirs through EOR and IOR that involves large cash expenditures for; in-fill drilling, waterflooding, gas injection, and thermal and chemical treatment of heavy oil recovery. Basically, one or a combined uncertainty of these elements may create “business risk” that may cause “business impact”. The impact can be positive leading to “business opportunity” or negative leading to “business threat”. Also, instead of risking NCF using risk parameters like gross revenue that consists of hydrocarbon in-place and unit price of oil and gas, and net expenditure (CAPEX and OPEX) by simply defining their risk distributions and parameters, our approach breaks down each risk parameter to sub-parameters, then risk components and finally risk fragments. This produces a break-down model of risk analysis approach by including all parameters with no stage separation that avoids risk of poor assumptions. Hence, risk parameters are simplified by evaluating specific distributions. Case study involving one major Gulf States oil reservoirs is used to demonstrate the approach presented in this paper. Results show great improvement of results as compared to the traditionally used method.

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