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Post-breakthrough scaling in reservoir field simulation

Author

Listed:
  • Oliveira, C.L.N.
  • Araújo, A.D.
  • Lucena, L.S.
  • Almeida, M.P.
  • Andrade, J.S.

Abstract

We study the oil displacement and production behavior in an isothermal thin layered reservoir model subjected to water flooding. We use the CMG’s (Computer Modelling Group) numerical simulators to solve mass balance equations. The influences of the viscosity ratio (m≡μoil/μwater) and the inter-well (injector-producer) distance r on the oil production rate C(t) and the breakthrough time tbr are investigated. Two types of reservoir configuration are used, namely one with random porosities and another with a percolation cluster structure. We observe that the breakthrough time follows a power-law of m and r, tbr∝rαmβ, with α=1.8 and β=−0.25 for the random porosity type, and α=1.0 and β=−0.2 for the percolation cluster type. Moreover, our results indicate that the oil production rate is a power law of time. In the percolation cluster type of reservoir, we observe that P(t)∝tγ, with γ=−1.81, where P(t) is the time derivative of C(t). The curves related to different values of m and r may be collapsed suggesting a universal behavior for the oil production rate.

Suggested Citation

  • Oliveira, C.L.N. & Araújo, A.D. & Lucena, L.S. & Almeida, M.P. & Andrade, J.S., 2012. "Post-breakthrough scaling in reservoir field simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3219-3226.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:11:p:3219-3226
    DOI: 10.1016/j.physa.2012.01.017
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    Cited by:

    1. 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.
    2. Wu, Bin & Liu, Zhi-Feng & Wang, Xiao-Hong, 2013. "Statistical behaviors for renormalization of correlated permeability field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(15), pages 3115-3121.
    3. Tavagh-Mohammadi, Behnam & Masihi, Mohsen & Ganjeh-Ghazvini, Mostafa, 2016. "Point-to-point connectivity prediction in porous media using percolation theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 304-313.

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