Optimal Dynamic Production Policy: The Case of a Large Oil Field in Saudi Arabia

Abstract

We model the optimal dynamic oil production decisions for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from a number of sources to estimate the cost and revenue functions used in the dynamic programming model. We also pay particular attention to the dynamic aspects of oil production. We use a nonparametric smoothing technique – tensor splines – to approximate the value function. The optimal solution depends on assumptions about various exogenous variables such as the discount rate and the timing of breakthroughs in the use of alternative energy, which we take to be solar energy. We account for uncertainty about the forecasts by examining the solutions under a number of scenarios. Our model is based on the hypothesis that oil production is chosen to maximize the discounted value of profits. Saudi oil policy reflects many political and strategic motives. Our analysis enables one to quantify the cost of pursuing these non-economic objectives.

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Part of Energy Forum study on "Political, Economic, Social, Cultural, and Religious Trends in the Middle East and the Gulf and Their Impact on Energy Supply, Security, and Pricing"
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optimal oil production, dynamic programming, value function approximation, tensor splines
Citation

Gao, Weiyu, Hartley, Peter R. and Sickles, Robin C.. "Optimal Dynamic Production Policy: The Case of a Large Oil Field in Saudi Arabia." (2004) James A. Baker III Institute for Public Policy: http://www.bakerinstitute.org/research/optimal-dynamic-production-policy-the-case-of-a-large-oil-field-in-saudi-arabia/.

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