Skip to main content
Log in

Numerical studies of a class of linear solvers for fine-scale petroleum reservoir simulation

  • Published:
Computing and Visualization in Science

Abstract

Numerical simulation based on fine-scale reservoir models helps petroleum engineers in understanding fluid flow in porous media and achieving higher recovery ratio. Fine-scale models give rise to large-scale linear systems, and thus require effective solvers for solving these linear systems to finish simulation in reasonable turn-around time. In this paper, we study convergence, robustness, and efficiency of a class of multi-stage preconditioners accelerated by Krylov subspace methods for solving Jacobian systems from a fully implicit discretization. We compare components of these preconditioners, including decoupling and sub-problem solvers, for fine-scale reservoir simulation. Several benchmark and real-world problems, including a ten-million-cell reservoir problem, were simulated on a desktop computer. Numerical tests show that the combination of the alternating block factorization method and multi-stage subspace correction preconditioner gives a robust and memory-efficient solver for fine-scale reservoir simulation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Al-Shaalan, T.M., Klie, H.M., Dogru, A.H., Wheeler, M.F., et al.: Studies of robust two stage preconditioners for the solution of fully implicit multiphase flow problems. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (2009)

  2. Appleyard, J., Cheshire, I., Pollard, R.: Special techniques for fully implicit simulators. In: Preceeding, European Symposium on Enhanced Oil Recovery, Bournemouth, England, pp. 395–408 (1981)

  3. Appleyard, J., et al.: Nested factorization. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (1983)

  4. Baker, A.H., Jessup, E.R., Kolev, T.V.: A simple strategy for varying the restart parameter in GMRES (m). J. Comput. Appl. Math. 230(2), 751–761 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  5. Bank, R.E., Chan, T.F., Coughran Jr., W.M., Smith, R.K.: The Alternate-Block-Factorization procedure for systems of partial differential equations. BIT Numer. Math. 29(4), 938–954 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  6. Behie, A., et al.: Comparison of nested factorization, constrained pressure residual, and incomplete factorization preconditionings. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers. (1985)

  7. Behie, A., Vinsome, P., et al.: Block iterative methods for fully implicit reservoir simulation. Soc. Pet. Eng. J. 22(05), 658–668 (1982)

    Article  Google Scholar 

  8. Behie, G.A., Forsyth Jr., P.: Incomplete factorization methods for fully implicit simulation of enhanced oil recovery. SIAM J. Sci. Stat. Comput. 5(3), 543–561 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  9. Cao, H., Tchelepi, H.A., Wallis, J.R., Yardumian, H.E. et al.: Parallel scalable unstructured CPR-type linear solver for reservoir simulation. In: SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers (2005)

  10. Chen, Z., Huan, G., Ma, Y.: Computational Methods for Multiphase Flows in Porous Media, vol. 2. SIAM, Philadelphia (2006)

    Book  MATH  Google Scholar 

  11. Christie, M., Blunt, M., et al.: Tenth SPE comparative solution project: a comparison of upscaling techniques. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (2001)

  12. Dogru, A.H., Fung, L.S., Al-Shaalan, T.M., Middya, U., Pita, J.A. et al.: From mega cell to giga cell reservoir simulation. In: SPE Annual Technical Conference and Exhibition. Society of Petroleum Engineers (2008)

  13. Dogru, A.H., Fung, L.S.K., Middya, U., Al-Shaalan, T.M., Byer, T., Hoy, H., Hahn, W.A., Al-Zamel, N., Pita, J.A., Hemanthkumar, K., et al.: New frontiers in large scale reservoir simulation. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (2011)

  14. Eberhard, J., Attinger, S., Wittum, G.: Coarse graining for upscaling of flow in heterogeneous porous media. Multiscale Model. Simul. 2(2), 269–301 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  15. Eberhard, J., Wittum, G.: A coarsening multigrid method for flow in heterogeneous porous media. In: Multiscale Methods in Science and Engineering. Springer, pp. 111–132 (2005)

  16. Graham, I., Hagger, M.: Unstructured additive Schwarz-conjugate gradient method for elliptic problems with highly discontinuous coefficients. SIAM J. Sci. Comput. 20(6), 2041–2066 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  17. Hu, X., Liu, W., Qi, G., Xu, J., Yan, Y., Zhang, C.-S., Zhang, S.: A fast auxiliary space preconditioners for numerical reservoir simulations. In: SPE Reservoir Characterization and Simulation Conference (2011)

  18. Hu, X., Xu, J., Zhang, C.-S.: Application of auxiliary space preconditioning in field-scale reservoir simulation. Sci. China Math. 56(12), 2737–2751 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  19. Klie, H.M.: Krylov-Secant Methods for Solving Large-Scale Systems of Coupled Nonlinear Parabolic Equations. PhD thesis, Rice University (1997)

  20. Kwok, W.H.F.: Scalable Linear and Nonlinear Algorithms for Multiphase Flow in Porous Media. PhD thesis, Stanford University (2007)

  21. Lacroix, S., Vassilevski, Y., Wheeler, J., Wheeler, M.: Iterative solution methods for modeling multiphase flow in porous media fully implicitly. SIAM J. Sci. Comput. 25(3), 905–926 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  22. Lacroix, S., Vassilevski, Y.V., Wheeler, M.F.: Decoupling preconditioners in the implicit parallel accurate reservoir simulator (IPARS). Numer. Linear Algebra Appl. 8(8), 537–549 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  23. Saad, Y.: A flexible inner-outer preconditioned gmres algorithm. SIAM J. Sci. Comput. 14(2), 461–469 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  24. Saad, Y.: Iterative Methods for Sparse Linear Systems. SIAM, Philadelphia (2003)

    Book  MATH  Google Scholar 

  25. Scheichl, R., Masson, R., Wendebourg, J.: Decoupling and block preconditioning for sedimentary basin simulations. Comput. Geosci. 7(4), 295–318 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  26. Stüben, K.: Algebraic Multigrid (AMG): An Introduction with Applications. GMD-Forschungszentrum Informationstechnik Sankt Augustin (1999)

  27. Stueben, K., Clees, T., Klie, H., Lu, B., Wheeler, M.F., et al.: Algebraic multigrid methods (AMG) for the efficient solution of fully implicit formulations in reservoir simulation. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (2007)

  28. Trangenstein, J.A., Bell, J.B.: Mathematical structure of the black-oil model for petroleum reservoir simulation. SIAM J. Appl. Math. 49(3), 749–783 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  29. Vaněk, P., Mandel, J., Brezina, M.: Algebraic multigrid by smoothed aggregation for second and fourth order elliptic problems. Computing 56(3), 179–196 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  30. Wallis, J., et al.: Incomplete Gaussian elimination as a preconditioning for generalized conjugate gradient acceleration. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (1983)

  31. Wang, F., Xu, J.: A crosswind block iterative method for convection-dominated problems. SIAM J. Sci. Comput. 21(2), 620–645 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  32. Watts, J., Shaw, J., et al.: A new method for solving the implicit reservoir simulation matrix equation. In: SPE Reservoir Simulation Symposium. Society of Petroleum Engineers (2005)

  33. Wittum, G.: On the robustness of ILU smoothing. SIAM J. Sci. Stat. Comput. 10(4), 699–717 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  34. Wu, S., Feng, C., Zhang, C.-S., Li, Q., et al.: A multilevel preconditioner and its shared memory implementation for new generation reservoir simulator. Pet. Sci. 11, 540–549 (2014)

    Article  Google Scholar 

  35. Xu, J., Zhu, Y.: Uniform convergent multigrid methods for elliptic problems with strongly discontinuous coefficients. Math. Models Methods Appl. Sci. 18(01), 77–105 (2008)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This paper was finished during Li’s visit to the State Key Laboratory of Scientific and Engineering Computing (LSEC), China. Li is thankful for the kind support from LSEC. The authors would like to thank RIPED, PetroChina, for providing numerical test data and support through PetroChina New-generation Reservoir Simulation Software (2011A-1010) and PetroChina Joint Research Funding 12HT1050002654. Feng is partially supported by the NSFC Grant 61603322, Hunan Provincial Natural Science Foundation of China (2016JJ2129) and Open Foundation of Guangdong Provincial Engineering Technology Research Center for Data Science (2016KF03). The authors also appreciate various valuable comments from an anonymous referee on the early version of this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zheng Li.

Additional information

Communicated by Gabriel Wittum.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Z., Wu, S., Zhang, CS. et al. Numerical studies of a class of linear solvers for fine-scale petroleum reservoir simulation. Comput. Visual Sci. 18, 93–102 (2017). https://doi.org/10.1007/s00791-016-0273-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00791-016-0273-3

Keywords

Navigation