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Determination of lower and upper bounds of predicted production from history-matched models
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  • Original Paper
  • Open Access
  • Published: 02 June 2016

Determination of lower and upper bounds of predicted production from history-matched models

  • G. M. van Essen2,
  • S. Kahrobaei1,
  • H. van Oeveren1,
  • P. M. J. Van den Hof3 &
  • …
  • J. D. Jansen1 

Computational Geosciences volume 20, pages 1061–1073 (2016)Cite this article

  • 1340 Accesses

  • 1 Citations

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Abstract

We present a method to determine lower and upper bounds to the predicted production or any other economic objective from history-matched reservoir models. The method consists of two steps: 1) performing a traditional computer-assisted history match of a reservoir model with the objective to minimize the mismatch between predicted and observed production data through adjusting the grid block permeability values of the model. 2) performing two optimization exercises to minimize and maximize an economic objective over the remaining field life, for a fixed production strategy, by manipulating the same grid block permeabilities, however without significantly changing the mismatch obtained under step 1. This is accomplished through a hierarchical optimization procedure that limits the solution space of a secondary optimization problem to the (approximate) null space of the primary optimization problem. We applied this procedure to two different reservoir models. We performed a history match based on synthetic data, starting from a uniform prior and using a gradient-based minimization procedure. After history matching, minimization and maximization of the net present value (NPV), using a fixed control strategy, were executed as secondary optimization problems by changing the model parameters while staying close to the null space of the primary optimization problem. In other words, we optimized the secondary objective functions, while requiring that optimality of the primary objective (a good history match) was preserved. This method therefore provides a way to quantify the economic consequences of the well-known problem that history matching is a strongly ill-posed problem. We also investigated how this method can be used as a means to assess the cost-effectiveness of acquiring different data types to reduce the uncertainty in the expected NPV.

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Authors and Affiliations

  1. Delft University of Technology, Delft, The Netherlands

    S. Kahrobaei, H. van Oeveren & J. D. Jansen

  2. Shell Global Solutions International B.V., Rijswijk, The Netherlands

    G. M. van Essen

  3. Eindhoven University of Technology, Eindhoven, The Netherlands

    P. M. J. Van den Hof

Authors
  1. G. M. van Essen
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  2. S. Kahrobaei
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  3. H. van Oeveren
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  4. P. M. J. Van den Hof
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  5. J. D. Jansen
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Corresponding author

Correspondence to J. D. Jansen.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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van Essen, G.M., Kahrobaei, S., van Oeveren, H. et al. Determination of lower and upper bounds of predicted production from history-matched models. Comput Geosci 20, 1061–1073 (2016). https://doi.org/10.1007/s10596-016-9576-1

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  • Received: 20 August 2015

  • Accepted: 12 May 2016

  • Published: 02 June 2016

  • Issue Date: October 2016

  • DOI: https://doi.org/10.1007/s10596-016-9576-1

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Keywords

  • Computer-assisted history matching
  • Uncertainty
  • Hierarchical optimization
  • Multi-objective optimization
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