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The impact of stochastic extraction cost on the value of an exhaustible resource: An application to the Alberta oil sands

Author

Listed:
  • Abdullah Almansour

    (Department of Finance and Economics, King Fahd University of Petroleum and Minerals)

  • Margaret Insley

    (Department of Economics, University of Waterloo)

Abstract

The optimal management of a non-renewable resource extraction project is studied when input and output prices follow correlated stochastic processes. The decision problem is specified by two Bellman equations describing the project when it is currently operating or mothballed. Solutions are determined numerically using the Least Squares Monte Carlo methodology. The analysis is applied to an oil sands project which uses natural gas during extracting and upgrading. The paper takes into account the co-movement between crude oil and natural gas prices and proposes two price models: one incorporates a long-run link between the two while the other has no such link. Incorporating a long-run relationship between oil and natural gas prices has a significant effect on the value of the project and its optimal operation and reduces the sensitivity of the project to the natural gas price process.

Suggested Citation

  • Abdullah Almansour & Margaret Insley, 2013. "The impact of stochastic extraction cost on the value of an exhaustible resource: An application to the Alberta oil sands," Working Papers 1303, University of Waterloo, Department of Economics, revised Jun 2013.
    • Handle: RePEc:wat:wpaper:1303
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    References listed on IDEAS

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    Cited by:

    1. Margaret Insley, 2013. "On the timing of non-renewable resource extraction with regime switching prices: an optimal stochastic control approach," Working Papers 1302, University of Waterloo, Department of Economics, revised Aug 2013.
    2. Galay, Gregory & Winter, Jennifer, 2025. "No end in sight: End-of-life management of oil wells in Alberta," Resource and Energy Economics, Elsevier, vol. 82(C).
    3. Davis, Rebecca J. & Sims, Charles, 2016. "To Frack or Not to Frack: Option Value Analysis on the U.S. Natural Gas Market," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235642, Agricultural and Applied Economics Association.
    4. Giorgio Ferrari & Shuzhen Yang, 2016. "On an Optimal Extraction Problem with Regime Switching," Papers 1602.06765, arXiv.org, revised Dec 2017.
    5. Kobari, L. & Jaimungal, S. & Lawryshyn, Y., 2014. "A real options model to evaluate the effect of environmental policies on the oil sands rate of expansion," Energy Economics, Elsevier, vol. 45(C), pages 155-165.
    6. Jacob LaRiviere & David Kling & James N Sanchirico & Charles Sims & Michael Springborn, 2018. "The Treatment of Uncertainty and Learning in the Economics of Natural Resource and Environmental Management," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 92-112.

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    More about this item

    JEL classification:

    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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