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Applications of statistical physics to the oil industry: predicting oil recovery using percolation theory

Author

Listed:
  • King, P.R
  • Buldyrev, S.V
  • Dokholyan, N.V
  • Havlin, S
  • Lee, Y
  • Paul, G
  • Stanley, H.E

Abstract

In this paper we apply scaling laws from percolation theory to the problem of estimating the time for a fluid injected into an oil field (for the purposes of recovering the oil) to breakthrough into a production well. The main contribution is to show that percolation theory, when applied to a realistic model, can be used to obtain the same results as calculated in a more conventional way but significantly more quickly. Specifically, we found that a previously proposed scaling form for the breakthrough time distribution when applied to a real oil field is in good agreement with more time consuming simulation results. Consequently these methods can be used in practical engineering circumstances to aid decision making for real field problems.

Suggested Citation

  • King, P.R & Buldyrev, S.V & Dokholyan, N.V & Havlin, S & Lee, Y & Paul, G & Stanley, H.E, 1999. "Applications of statistical physics to the oil industry: predicting oil recovery using percolation theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 60-66.
    • Handle: RePEc:eee:phsmap:v:274:y:1999:i:1:p:60-66
    DOI: 10.1016/S0378-4371(99)00327-1
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    References listed on IDEAS

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    1. N/A, 1996. "Statistical Appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 155(1), pages 110-119, February.
    2. N/A, 1996. "Statistical Appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 157(1), pages 107-116, July.
    3. N/A, 1996. "Statistical Appendix," National Institute Economic Review, National Institute of Economic and Social Research, vol. 156(1), pages 115-124, May.
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    Cited by:

    1. Manwart, C. & Hilfer, R., 2002. "Numerical simulation of creeping fluid flow in reconstruction models of porous media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 706-713.
    2. Ganjeh-Ghazvini, Mostafa & Masihi, Mohsen & Ghaedi, Mojtaba, 2014. "Random walk–percolation-based modeling of two-phase flow in porous media: Breakthrough time and net to gross ratio estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 214-221.
    3. Stanley, H.Eugene & Andrade, José S, 2001. "Physics of the cigarette filter: fluid flow through structures with randomly-placed obstacles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(1), pages 17-30.

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