1887

Abstract

Summary

The model is based on flow-network representation concept of the reservoir and is derived as a general physics framework (that is currently implemented for water and steam flooding reservoir operations). In addition to speedup due to nature of surrogate model, the simulation procedure inside of the model is highly parallelizable, this allows to significantly decrease computational complexity compared to classical reservoir simulator. History matching algorithm used is based on ESMDA method and is implemented, using the distributed memory parallelism concepts. After data fitting procedure the model is used for close-loop optimization reservoir management.

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/content/papers/10.3997/2214-4609.201800284
2018-04-09
2024-04-25
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References

  1. Cardoso, M.A., Durlofsky, L.J. and Sarma, P.
    , 2009. Development and application of reduced-order modeling procedures for subsurface flow simulation. International journal for numerical methods in engineering, 77(9), pp.1322–1350.
    [Google Scholar]
  2. Albertoni, Alejandro, and LarryW. Lake
    . “Inferring interwell connectivity only from well-rate fluctuations in waterfloods.”SPE Reservoir Evaluation & Engineering6.01 (2003): 6–16.
    [Google Scholar]
  3. Sayarpour, Morteza
    . Development and application of capacitance-resistive models to water/carbon dioxide floods.The University of Texas at Austin, 2008.
    [Google Scholar]
  4. Lake, Larry W.
    , et al.“Optimization of oil production based on a capacitance model of production and injection rates.”Hydrocarbon economics and evaluation symposium.Society of Petroleum Engineers, 2007.
    [Google Scholar]
  5. Lerlertpakdee, Pongsathorn, BehnamJafarpour, and EduardoGildin
    . “Efficient production optimization with flow-network models.”SPE Journal19.06 (2014): 1–083.
    [Google Scholar]
  6. Zhao, Hui
    , et al.“A Physics-Based Data-Driven Numerical Model for Reservoir History Matching and Prediction With a Field Application.”SPE Journal21.06 (2016): 2–175.
    [Google Scholar]
  7. , et al.“History matching and production optimization of water flooding based on a data-driven interwell numerical simulation model.”Journal of Natural Gas Science and Engineering31 (2016): 48–66.
    [Google Scholar]
  8. Emerick, Alexandre A., and AlbertC. Reynolds
    . “History-matching production and seismic data in a real field case using the ensemble smoother with multiple data assimilation.”SPE Reservoir Simulation Symposium.Society of Petroleum Engineers, 2013.
    [Google Scholar]
  9. Jansen, F. E., and M. G.Kelkar
    . “Application of wavelets to production data in describing inter-well relationships.”SPE Annual Technical Conference and Exhibition.Society of Petroleum Engineers, 1997.
    [Google Scholar]
  10. van Doren, Jorn FM, RenatoMarkovinović, and Jan-DirkJansen
    . “Reduced-order optimal control of water flooding using proper orthogonal decomposition.”Computational Geosciences10.1 (2006): 137–158.
    [Google Scholar]
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