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Abstract

Summary

Oil production optimization of petroleum reservoirs under uncertainty give rise to large-scale optimization problems.

Ensemble-based methods for production optimization are used in combination with gradient-based optimization algorithms.

Use of commercial-grade simulators able to handle real-scale reservoir models and compute the gradient by the adjoint method is essential for implementing such methods in real-life.

However, the simulation time for a single ensemble model renders the problem computationally intractable. Therefore, model reduction is needed.

We introduce a grid coarsening method that maintains the overall dynamics of the flow, by preserving the geological features of the model.

In this paper, we present a software tool for oil production optimization and a semi-automated workflow for grid coarsening and property upscaling.

The software tool integrates state-of-the-art optimization algorithms, ensemble-based optimization strategies and reservoir simulators with adjoint capability.

The software is based on the Eclipse input file-format, which enables use of existing reservoir models for production optimization.

This allows for oil production optimization of both black-oil and compositional flow models and brings model based production optimization a step closer to routinely implementation in reservoir management workflow.

We present the workflow of the optimization software and numerical examples that demonstrates the application of ensemble-based production optimization.

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/content/papers/10.3997/2214-4609.201802211
2018-09-03
2024-04-26

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References

  1. Aliyev, E. and Durlofsky, L.J.
    [2015] Multilevel Field-Development Optimization using a Sequence of Upscaled Models. In: SPE Reservoir Simulation Symposium.Society of Petroleum Engineers.
     [Google Scholar]
  2. Aziz, K., Durlofsky, L.J. and Tchelepi, H.
    [2005] Notes for petroleum reservoir simulation.Stanford University, Stanford, Califormia, USA.
     [Google Scholar]
  3. Barker, J.W. and Thibeau, S.
    [1997] A Critical Review of the Use of Pseudorelative Permeabilities for Upscaling.SPE Reservoir Engineering, 12(2), 138–143.
     [Google Scholar]
  4. Brouwer, D.R. and Jansen, J.D.
    [2004] Dynamic Optimization of Waterflooding With Smart Wells Using Optimal Control Theory.SPE Journal, 9(04), 391–402.
     [Google Scholar]
  5. Capolei, A., Völcker, C., Frydendall, J. and Jørgensen, J.B.
    [2012] Oil Reservoir Production Optimization using Single Shooting and ESDIRK Methods. IFAC Proceedings Volumes, 45(8), 286–291.
     [Google Scholar]
  6. Cardoso, M.A. and Durlofsky, L.J.
    [2010] Linearized reduced-order models for subsurface flow simulation.Journal of Computational Physics, 229(3), 681–700.
     [Google Scholar]
  7. Chen, Y. and Wu, X.H.
    [2008] Upscaled modeling of well singularity for simulating flow in heterogeneous formations.Computational Geosciences, 12(1), 29–45.
     [Google Scholar]
  8. Chen, Z., Huan, G. and Ma, Y.
    [2006] Computational methods for multiphase flows in porous media.SIAM.
     [Google Scholar]
  9. Christie, M.A. and Blunt, M.J.
    [2001] Tenth SPE Comparative Solution Project: A Comparison of Upscaling Techniques. In: SPE Reservoir Simulation Symposium.Society of Petroleum Engineers.
     [Google Scholar]
  10. Codas, A., Hanssen, K.G., Foss, B., Capolei, A. and Jørgensen, J.B.
    [2016] Multiple Shooting applied to robust reservoir control optimization including output constraints on coherent risk measures. Computational Geosciences, 1–19.
     [Google Scholar]
  11. van Doren, J.F.M., Markovinović, R. and Jansen, J.D.
    [2005] Reduced-order optimal control of water flooding using proper orthogonal decomposition.Computational Geosciences, 10(1), 137–158.
     [Google Scholar]
  12. van Essen, G., Zandvliet, M., Van den Hof, P., Bosgra, O. and Jansen, J.D.
    [2009] Robust Waterflooding Optimization of Multiple Geological Scenarios.SPE Journal, 14(01), 202–210.
     [Google Scholar]
  13. Fonseca, R.M., Reynolds, A.C. and Jansen, J.D.
    [2016] Generation of a Pareto front for a bi-objective water flooding optimization problem using approximate ensemble gradients.Journal of Petroleum Science and Engineering, 147, 249–260.
     [Google Scholar]
  14. Fonseca, R.M., Stordal, A.S., Leeuwenburgh, O., Van den Hof, P.M.J. and Jansen, J.D.
    [2014] Robust ensemble-based multi-objective optimization. In: ECMOR XIV-14th European conference on the mathematics ofoil recovery.
     [Google Scholar]
  15. Hørsholt, S., Nick, H.M. and Jørgensen, J.B.
    [2018] Oil Production Optimization of Black-Oil Models by Integration of Matlab and Eclipse E300. In: 3rd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production.
     [Google Scholar]
  16. Jansen, J.D., Fonseca, R.M., Kahrobaei, S., Siraj, M., Van Essen, G. and Van den Hof, P.
    [2013] The Egg model.Delft University of Technology, The Netherlands, Tech. Rep., Research note and data set. http://repository.tudelft.nl/view/ir/uuid:1b85ee17-3e58-4fa4-be79-8328945a4491 and http://data.3tu.nl/repository/uuid:916c86cd-3558-4672-829a-105c62985ab2(accessed 23 March 2015).
     [Google Scholar]
  17. Killough, J.E.
    [1995] Ninth SPE Comparative Solution Project: A Reexamination of Black-Oil Simulation. In: SPE Reservoir Simulation Symposium.Society of Petroleum Engineers.
     [Google Scholar]
  18. Krogstad, S., Raynaud, X. and Nilsen, H.M.
    [2016] Reservoir management optimization using well-specific upscaling and control switching.Computational Geosciences, 20(3), 695–706.
     [Google Scholar]
  19. Lie, K.A., Kedia, K., Skaflestad, B., Wang, X., Yang, Y., Wu, X.H. and Hoda, N.
    [2017] A General Non-Uniform Coarsening and Upscaling Framework for Reduced-Order Modeling. In: SPE Reservoir Simulation Conference.Society of Petroleum Engineers.
     [Google Scholar]
  20. Oliveira, D.F. and Reynolds, A.
    [2015] Hiererarchical Multiscale Methods for Life-Cycle-Production Optimization: A Field Case Study.SPE Reservoir Simulation Symposium, (SPE-173273-MS).
     [Google Scholar]
  21. Renard, P. and De Marsily, G.
    [1997] Calculating equivalent permeability: a review.Advances in water resources, 20(5–6), 253–278.
     [Google Scholar]
  22. Sarma, P., Durlofsky, L.J., Aziz, K. and Chen, W.H.
    [2006] Efficient Real-time Reservoir Management Using Adjoint-based Optimal Control and Model Updating.Computational Geosciences, 10(1), 3–36.
     [Google Scholar]
  23. Siraj, M.M., Van den Hof, P.M. and Jansen, J.D.
    [2015] Handling risk of uncertainty in model-based production optimization: a robust hierarchical approach.IFAC-PapersOnLine, 48(6), 248–253.
     [Google Scholar]
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Software For Industrial Scale Oil Production Optimization
Conference Proceedings 2018, 1 (2018); https://doi.org/10.3997/2214-4609.201802211
/content/papers/10.3997/2214-4609.201802211
/content/papers/10.3997/2214-4609.201802211
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