Forecasting Production in an Oil Reservoir Simulation and Its Challenges

Conference paper

Abstract

A Bayesian approach for uncertainty quantification of oil reservoir parameters in forecasting the production is straightforward in principle. However, the complexity of flow simulators and the nature of the inverse problem at hand present an ongoing practical challenges to addressing uncertainty in all subsurface parameters. In this paper, we focus on two important subsurface parameters, permeability and porosity, and discuss quantifying uncertainty in those parameters.

References

  1. 1.
    Chen, Z., Huan, G., Ma, Y.: Computational methods for multiphase flows in porous media. SIAM, Philadelphia, PA (2006)MATHCrossRefGoogle Scholar
  2. 2.
    Dagan, G.: Flow and transport in porous formations. Springer-Verlag (1989)Google Scholar
  3. 3.
    Douglas, C., Efendiev, Y., Ewing, R., Ginting, V., Lazarov, R.: Dynamic data driven simulations in stochastic environments. Computing 77(4), 321–333 (2006)MathSciNetMATHCrossRefGoogle Scholar
  4. 4.
    Efendiev, Y., Datta-Gupta, A., Ginting, V., Ma, X., Mallick, B.: An efficient two-stage Markov chain Monte Carlo method for dynamic data integration. Water Resources Research 41(W12423) (2005)Google Scholar
  5. 5.
    Ginting, V., Pereira, F., Presho, M., Wo, S.: Application of the two-stage Markov chain Monte Carlo method for characterization of fractured reservoirs using a surrogate flow model. Computational Geosciences 15(4), 691–707 (2011)MathSciNetMATHCrossRefGoogle Scholar
  6. 6.
    Loève, M.: Probability theory. Springer, Berlin (1977)MATHGoogle Scholar
  7. 7.
    Pereira, F., Rahunanthan, A.: Numerical simulation of two-phase flows on a GPU. In: 9th International meeting on High Perfomance Computing for Computational Science (VECPAR ’10). Berkeley, CA (2010)Google Scholar
  8. 8.
    Pereira, F., Rahunanthan, A.: A semi-discrete central scheme for the approximation of two-phase flows in three space dimensions. Mathematics and Computers in Simulation 81(10), 2296–2306 (2011)MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of WyomingLaramieUSA
  2. 2.Department of Mathematics and School of Energy ResourcesUniversity of WyomingLaramieUSA

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