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Robust production optimization with capacitance-resistance model as precursor

Computational Geosciences volume 21, pages 1423–1442 (2017)Cite this article

Abstract

Many model-based techniques for optimizing hydrocarbon production, especially robust optimization (RO), carry prohibitive computational cost. Ensemble-based optimization (EnOpt) is a promising RO method but is computationally intensive when based on rich grid-based reservoir models with hundreds of realizations. We present a proxy-model workflow where a grid-based model is supplemented by a useful yet tractable proxy model. A capacitance-resistance model (CRM) can be a proxy model for waterflooding systems. We illustrate the use of CRM-based models and investigate their pros and cons using synthetic 2D and 3D models. A selected proxy model is embedded into the proxy-model workflow. The results obtained from the proxy-model and traditional workflows are compared. The impact of any differences is assessed by considering a relevant decision-making context. The main contributions are (1) a general RO workflow that embeds proxy models, (2) a discussion of the desiderata of proxy models, (3) illustration and discussion of the use of CRM-based models in the proxy-model workflow, and (4) a discussion of the impact of using a proxy model for production optimization in a decision-making context. Based on our study, we conclude that CRM-based models have high potential to serve as a cogent proxy model for waterflooding related decision-making context and that the proxy-model workflow, leveraging a faster, but relevant, production model, significantly speeds up the optimization yet gives robust results that leads to a near-optimal solution.

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Acknowledgements

The authors acknowledge the Research Council of Norway and the industry partners; ConocoPhillips Skandinavia AS, Aker BP ASA, Eni Norge AS, Maersk Oil Norway AS, DONG Energy A/S, Denmark, Statoil Petroleum AS, ENGIE E&P NORGE AS, Lundin Norway AS, Halliburton AS, Schlumberger Norge AS, Wintershall Norge AS of The National IOR Centre of Norway for support.

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Authors and Affiliations

  1. The National IOR Centre of Norway, Stavanger, Norway

    A. J. Hong, R. B. Bratvold & G. Nævdal

  2. Department of Petroleum Engineering, University of Stavanger, Stavanger, Norway

    A. J. Hong & R. B. Bratvold

  3. International Research Institute of Stavanger, Stavanger, Norway

    G. Nævdal

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  1. A. J. Hong
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  2. R. B. Bratvold
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  3. G. Nævdal
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Correspondence to A. J. Hong.

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Hong, A.J., Bratvold, R.B. & Nævdal, G. Robust production optimization with capacitance-resistance model as precursor. Comput Geosci 21, 1423–1442 (2017). https://doi.org/10.1007/s10596-017-9666-8

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  • DOI: https://doi.org/10.1007/s10596-017-9666-8

Keywords

  • Model-based hydrocarbon production optimization
  • Geological uncertainty
  • Robust production optimization
  • Ensemble-based optimization
  • Computational cost
  • Grid-based reservoir model
  • Capacitance-resistance model
  • Proxy model
  • Water injection
  • Decision-making
  • Value of verisimilitude