Improving stochastic inversion methods in history matching using proxy models

Karl Dunbar Stephen, Saleh Arwini

    Research output: Contribution to conferencePaper

    Abstract

    Assisted history methods have been developed to automatically search the parameter space to find optimal models. Stochastic approaches increase the breadth of the search but can be very costly. Proxy models improve convergence by producing parameter sensitivities. Better distributions may be used in stochastic generation of new models. In this paper we present modifications to the neighbourhood and a genetic algorithm. Quadratic proxy models are derived for the misfit surface so that the search process can be made more efficient. We test the approaches on several analytical test functions. We also apply them to the Schiehallion field from the west of Shetland in seismic history matching. A quadratic regression equation was derived from a representative sample of models and used to generate gradients of the misfit with respect to the parameters. These are used to direct the choice of new models during a random search increasing the chance of finding new models. The proxy based method improves convergence by a factor of three generally. Complex surfaces see a lesser improvement though and the regression equation can be updated as better models are found to maintain the benefits.
    Original languageEnglish
    Pages1-11
    Number of pages11
    Publication statusPublished - Sep 2010
    Event12th European Conference on the Mathematics of Oil Recovery 2010 - Oxford, United Kingdom
    Duration: 6 Sep 20109 Sep 2010

    Conference

    Conference12th European Conference on the Mathematics of Oil Recovery 2010
    Abbreviated titleECMOR XII
    CountryUnited Kingdom
    CityOxford
    Period6/09/109/09/10

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    history
    inversion
    method
    genetic algorithm
    parameter
    test

    Cite this

    Stephen, K. D., & Arwini, S. (2010). Improving stochastic inversion methods in history matching using proxy models. 1-11. Paper presented at 12th European Conference on the Mathematics of Oil Recovery 2010, Oxford, United Kingdom.
    Stephen, Karl Dunbar ; Arwini, Saleh. / Improving stochastic inversion methods in history matching using proxy models. Paper presented at 12th European Conference on the Mathematics of Oil Recovery 2010, Oxford, United Kingdom.11 p.
    @conference{daf3f4b8e3cb4e47bb56e3c28a29fe11,
    title = "Improving stochastic inversion methods in history matching using proxy models",
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    author = "Stephen, {Karl Dunbar} and Saleh Arwini",
    year = "2010",
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    language = "English",
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    note = "12th European Conference on the Mathematics of Oil Recovery 2010, ECMOR XII ; Conference date: 06-09-2010 Through 09-09-2010",

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    Stephen, KD & Arwini, S 2010, 'Improving stochastic inversion methods in history matching using proxy models' Paper presented at 12th European Conference on the Mathematics of Oil Recovery 2010, Oxford, United Kingdom, 6/09/10 - 9/09/10, pp. 1-11.

    Improving stochastic inversion methods in history matching using proxy models. / Stephen, Karl Dunbar; Arwini, Saleh.

    2010. 1-11 Paper presented at 12th European Conference on the Mathematics of Oil Recovery 2010, Oxford, United Kingdom.

    Research output: Contribution to conferencePaper

    TY - CONF

    T1 - Improving stochastic inversion methods in history matching using proxy models

    AU - Stephen, Karl Dunbar

    AU - Arwini, Saleh

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    N2 - Assisted history methods have been developed to automatically search the parameter space to find optimal models. Stochastic approaches increase the breadth of the search but can be very costly. Proxy models improve convergence by producing parameter sensitivities. Better distributions may be used in stochastic generation of new models. In this paper we present modifications to the neighbourhood and a genetic algorithm. Quadratic proxy models are derived for the misfit surface so that the search process can be made more efficient. We test the approaches on several analytical test functions. We also apply them to the Schiehallion field from the west of Shetland in seismic history matching. A quadratic regression equation was derived from a representative sample of models and used to generate gradients of the misfit with respect to the parameters. These are used to direct the choice of new models during a random search increasing the chance of finding new models. The proxy based method improves convergence by a factor of three generally. Complex surfaces see a lesser improvement though and the regression equation can be updated as better models are found to maintain the benefits.

    AB - Assisted history methods have been developed to automatically search the parameter space to find optimal models. Stochastic approaches increase the breadth of the search but can be very costly. Proxy models improve convergence by producing parameter sensitivities. Better distributions may be used in stochastic generation of new models. In this paper we present modifications to the neighbourhood and a genetic algorithm. Quadratic proxy models are derived for the misfit surface so that the search process can be made more efficient. We test the approaches on several analytical test functions. We also apply them to the Schiehallion field from the west of Shetland in seismic history matching. A quadratic regression equation was derived from a representative sample of models and used to generate gradients of the misfit with respect to the parameters. These are used to direct the choice of new models during a random search increasing the chance of finding new models. The proxy based method improves convergence by a factor of three generally. Complex surfaces see a lesser improvement though and the regression equation can be updated as better models are found to maintain the benefits.

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    Stephen KD, Arwini S. Improving stochastic inversion methods in history matching using proxy models. 2010. Paper presented at 12th European Conference on the Mathematics of Oil Recovery 2010, Oxford, United Kingdom.