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A general improved methodology to forecasting future oil production: Application to the UK and Norway

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  • Fiévet, L.
  • Forró, Z.
  • Cauwels, P.
  • Sornette, D.

Abstract

We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of the frequency of future oil field discoveries. Compared with the standard methodology that tends to underestimate remaining oil reserves, our method gives a better description of future oil production, as validated by our back-tests starting in 2008. Specifically, we predict remaining reserves extractable until 2030 to be 5.7 ± 0.3 billion barrels for Norway and 3.0 ± 0.3 billion barrels for the UK, which are respectively 45% and 66% above the predictions using an extrapolation of aggregate production.

Suggested Citation

  • Fiévet, L. & Forró, Z. & Cauwels, P. & Sornette, D., 2015. "A general improved methodology to forecasting future oil production: Application to the UK and Norway," Energy, Elsevier, vol. 79(C), pages 288-297.
    • Handle: RePEc:eee:energy:v:79:y:2015:i:c:p:288-297
    DOI: 10.1016/j.energy.2014.11.014
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    References listed on IDEAS

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    1. Z. Forr'o & P. Cauwels & D. Sornette, "undated". "When games meet reality: is Zynga overvalued?," Working Papers ETH-RC-12-003, ETH Zurich, Chair of Systems Design.
    2. Y. Malevergne & V. Pisarenko & D. Sornette, 2005. "Empirical distributions of stock returns: between the stretched exponential and the power law?," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 379-401.
    3. Höök, Mikael & Aleklett, Kjell, 2008. "A decline rate study of Norwegian oil production," Energy Policy, Elsevier, vol. 36(11), pages 4262-4271, November.
    4. Zal'an Forr'o & Peter Cauwels & Didier Sornette, 2012. "When games meet reality: is Zynga overvalued?," Papers 1204.0350, arXiv.org, revised May 2012.
    5. Smith, James L, 1980. "A Probabilistic Model of Oil Discovery," The Review of Economics and Statistics, MIT Press, vol. 62(4), pages 587-594, November.
    6. Brecha, Robert J., 2012. "Logistic curves, extraction costs and effective peak oil," Energy Policy, Elsevier, vol. 51(C), pages 586-597.
    7. Lynch, Michael C., 2002. "Forecasting oil supply: theory and practice," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(2), pages 373-389.
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    Cited by:

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