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NNRManaging Risk in the E&P Industry through Integrated Portfolio Management
Meftun Erdogan1, Brett Mudford2, John Davidson1, Chuck T.Davis1
Overview
Traditional methods of project evaluation and capital allocation in petroleum exploration and production often result in over-estimation of value, under-estimation of risk and most importantly, the mis-allocation of capital. An Integrated Portfolio Management approach combining economic evaluation, portfolio modeling and portfolio optimization offers significant improvements towards mitigating these challenges. Effective economic analysis and the output of valid data for portfolio analysis and optimization requires an integrated portfolio management approach that relies on capturing all elements of risk and uncertainty in a consistent manner and adopting a standard process for economic evaluations. To be effective, risk/uncertainty assessment and standard processes must be applied throughout the project life cycle and across disparate business lines. Maximum effectiveness of the Integrated Portfolio Management approach is achieved only when all relevant portfolio data is accessible from one centralized location with all granularities for which data integrity can be easily managed and maintained. This environment enables the corporate decision makers to analyze different investment/divestment strategies under variable market conditions, quantify the impact of the strategies on the corporate portfolio and assess the interaction of each of the competing opportunities (or opportunity set) as they contribute to the delivery of the overall corporate business objectives. Accomplishing this task while accommodating practical business constraints, while maximizing financial returns, and while measuring and controlling risk is the true value of Integrated Portfolio Management approach.
Methods
In this study, an upstream oil and gas portfolio, consisting of 14 exploration, 6 exploitation and 6 development projects is analyzed using an Integrated Portfolio Management approach. The objective is to emphasize major components of such a system and to deliver more holistic picture to decision makers, enabling them to identify most effective choices in uncertain situations. This is achieved by determining the boundaries of entire solution envelope; efficient frontier, inefficient frontier and constrained frontier using portfolio optimization.
Economic evaluations are performed using stochastic simulation techniques for projects. Input probability distributions are introduced for geological, technical and economical parameters and dependencies between input parameters are also taken into account. For the projects, in-place reserve is defined by combining different geological risk factors with range of reservoir parameters such as net pay, recovery factor and area. The geoscientific information is integrated with array of engineering data to build dynamic scenarios including commodity prices, forecasted inflation, and additional economic parameters. Distributions of possible outputs are generated for each project through stochastic simulation in the economics model. The results of stochastic modeling serve as input to in-depth portfolio analysis and optimization.
The methodology behind the portfolio optimization is based on the Modern Portfolio Theory of Harry Markowitz. Mean-variance efficient portfolios were the essential for Modern Portfolio Theory. A portfolio is defined as mean-variance efficient if it has the highest expected return for a given variance, or if it has the smallest variance for a given expected return. But, in this study, due to the uniqueness of the E&P industry, risk measure is selected as downside exposure or loss since upstream projects typically have more skewed or log-normal value distributions with high probabilities of achieving low-value outcomes, and small probabilities of high-value results. (See Orman and Duggan (1) for an in-depth explanation of the differences in the E&P industry.) Semi standard deviation is selected as representative statistics for risk measure. Net Present Value is preferred for measuring return when framing portfolio optimization problem since is more aligned with E&P investment decision making goals and better captures the differences in project lengths. A sophisticated general purpose optimizer is used to solve for optimum portfolios. (See April et al. (2) details of optimization methodology)
1 Halliburton,
2 Constellation Power Source
Results;
The results of two different capital allocation scenarios are reported below.
In Case 1, a portfolio was created using traditional profitability index ranking (Net Present Value/Discounted Investment P/I). In this case, 28 projects are ranked by P/I ratio and are funded until available capital is exhausted. By leveraging this approach to capital allocation, risk is not considered either at project or portfolio level. Mean capital efficiency is the primary focus.
In Case 2, all possible combinations of 28 projects in a portfolio were analyzed using portfolio optimization. The analysis determined the boundaries of entire solution envelope; efficient frontier, inefficient frontier, and constraint frontier with corresponding risk and return values. The impacts of constraints in the optimized solution are quantified and the results compared to the traditional capital allocation ranking within the solution envelope.
Conclusions;
In the study, an oil and gas portfolio is analyzed using an Integrated Portfolio Management approach. Major components of this methodology are economic evaluations, portfolio analysis and portfolio optimization. Compare to traditional methods of project evaluation and capital allocation, the Integrated Portfolio Management methodology coupled with portfolio optimization delivers better results by capturing all elements of risk and uncertainty in a consistent manner and adopting a standard process for economic evaluations throughout the project life cycle and across the entire business. Decision makers that leverage the Integrated Portfolio Management approach are able to easily test the feasibility of different strategies and compare portfolio optimization results against traditional methods. By defining all feasible portfolios and establishing solution envelopes, more effective business decisions can be reached in uncertain situations.
References;
1. Orman, M., Duggan, T.E., Applying Modern Portfolio Theory to Upstream Investment Decision-Making, paper SPE49095 presented SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, 27-30 September, 1998.
2. April,J., Glover,F., Kelly,J., Laguna,M., Erdogan,M., Mudford, B., Stegemeier,D. Advanced Optimization Methodology in the Oil and Gas Industry: The Theory of Scatter Search Techniques with Simple Examples, SPE Paper 82009, Paper and Proceedings of 2003 SPE Hydrocarbon Economics and Evaluation Symposium: Dallas, Texas; 2003.
3. Erdogan, M., Mudford B., Davis, C.T., Stegemeirer , D., Going Beyond the Efficient Frontier Analysis Using an Integrated Portfolio Management Approach, SPE Paper 94565, SPE Hydrocarbon Economics and Evaluation Symposium, Dallas, April3-5 2005,
4. Davidson,J.W., Erdogan,M., Dowty,T.,Diapolo,E.J., Garrison,C. Project Portfolio Management A
Low Cost, High Return Business Solution, SPE Paper 77665, Paper and Proceedings of 2002 SPE Anuual Technical Conference: San Antonio, Texas, 2002
5. Wood, David, Portfolio Optimization Benefits from Integrating Analysis of Risk, Strategy, and Valuation, Oil and Gas Journal, July 8, 2002.
6. Erdogan, M, Mudford, B, Chenoweth, G, Holeywell, R, Jakubson, J, Optimization of Decision Tree and Simulation Portfolios: A Comparison, SPE paper 68575, Paper and Proceedings of 2001 SPE Hydrocarbon Economics and Evaluation Symposium: Dallas, Texas; 2001.
7. Walls, M. R., Corporate Risk Taking In the E&P industry, Oil and Gas Journal, Executive Report, Vol 2, No 2
(1999), pg 42.
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