Application of Real Options to Valuation and Decision-making in the Petroleum E&P Industry

This study establishes a risk-neutral binomial lattice method to apply real options theory to valuation and decisionmaking in the petroleum exploration and production (E&P) industry under uncertain oil prices. The research is applied to the switching time from primary to water flooding oil recovery. First, West Texas Intermediate (WTI) oil price evolution in the past 25 years, from January 2, 1986 to May 28, 2010, is studied and modeled with geometric Brownian motion (GBM) and one-factor mean reversion price models. Second, production profile for primary and water flooding oil recovery for a synthetic onshore oil reservoir is generated using UTCHEM simulator. Third, the binomial lattice real options evaluation (ROE) method is established to value the project with flexibility in switching time from primary to water flooding oil recovery. Seven results and conclusions are reached: 1) for GBM price model, the assumptions of constant drift rate and volatility do not hold for WTI oil prices; 2) one-factor mean reversion model is better to fit WTI oil prices than GBM model; 3) the evolution of WTI oil prices in the past 25 years was according to three price regimes and since 2003, the world economy has increased its tolerance to higher oil prices and to higher price fluctuation from its long run price; 4) the established ROE method can be used to identify the best time to switch from primary to water flooding oil recovery; 5) with one-factor mean reversion oil price model and the most updated cost data, the ROE method finds that water flooding switching time is earlier than that from traditional net present value optimizing method; 6) the ROE results reveal that most of time water flooding should start when oil prices are high; and 7) water flooding switching time is sensitive to oil price models and to the investment and operating costs. The established ROE framework enhances the valuation and decision-making for petroleum E&P industry including when to switch from one enhanced oil recovery method to another and when to switch from conventional to unconventional hydrocarbon production. Introduction The petroleum industry is characterized by large investment and asset base. In addition to high level of technical complexity in exploration and production, it is very vulnerable to the fluctuation in oil and gas prices. The value of a petroleum company relies on its oil and gas reserves and the evaluation of producing an oil and gas reserve depends on many certain and uncertain factors. Taking only oil production into consideration, after an oil field is discovered and developed, there are three major stages in the production of the oil field, i.e., primary, secondary, and tertiary production. How should a petroleum company arrange the oil production according to specific reservoir conditions and the changing oil prices so that the total value which the company receives from producing the natural resource can be maximized? Traditionally, net present value (NPV) is used to value the project with the deterministic oil prices. However, this method cannot capture the uncertainty of oil prices and value of flexibility in decision making, such as the flexibility to decide when to switch from one oil production option to another, contingent on uncertain factors such as oil prices. The real options approach, built on the theory for pricing financial options, addresses this challenge more successfully than conventional techniques such as the NPV method. The real options method takes uncertainty in oil prices, oil production rate change, and managers’ flexibility in decision making into consideration and discovers the best time for switching from one production option to another. Thus the maximum value of producing the oil reservoir is obtained. With a synthetic petroleum company and a synthetic oil exploration and production (E&P) project, this research establishes a binomial lattice real options evaluation method for the petroleum E&P industry to perform project evaluations under uncertainty. With the unique industry needs oriented, this research builds binomial lattices for two stochastic oil price models, i. e. , the geometric Brownian motion (GBM) and one-factor mean reversion models, generates oil production profile with different water flooding switching times through reservoir simulations, and creates binomial lattice cash flow models. The research integrates the established real options evaluation framework with the binomial lattices of stochastic oil price models, oil production profile, and binomial lattice cash flow to achieve the evaluation functions. This real options evaluation method is then applied to identify the best switching time at changing oil prices with the flexibility of switching from primary to water flooding oil recovery, and to capture the maximum value of the project for producing the synthetic oil reservoir. The results from the real options evaluation method are compared with those from the traditional NPV evaluation method. The research and results for this study are presented through five sections. 1). The historical West Texas Intermediate (WTI) oil prices are analyzed, the parameters for the geometric Brownian motion (GBM) and one-factor mean