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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Volume 25, issue 4
Nonlin. Processes Geophys., 25, 731–746, 2018
https://doi.org/10.5194/npg-25-731-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Nonlin. Processes Geophys., 25, 731–746, 2018
https://doi.org/10.5194/npg-25-731-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 06 Nov 2018

Research article | 06 Nov 2018

Application of ensemble transform data assimilation methods for parameter estimation in reservoir modeling

Sangeetika Ruchi and Svetlana Dubinkina

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Lorena Grabowski on behalf of the Authors (15 Jun 2018)  Author's response
ED: Referee Nomination & Report Request started (04 Jul 2018) by Takemasa Miyoshi
RR by Anonymous Referee #1 (13 Jul 2018)
RR by Anonymous Referee #2 (02 Aug 2018)
ED: Publish subject to minor revisions (review by editor) (21 Aug 2018) by Takemasa Miyoshi
AR by Svetlana Dubinkina on behalf of the Authors (24 Aug 2018)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (14 Sep 2018) by Takemasa Miyoshi
AR by Svetlana Dubinkina on behalf of the Authors (21 Sep 2018)  Author's response    Manuscript
ED: Publish as is (17 Oct 2018) by Takemasa Miyoshi
Publications Copernicus
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Short summary
Accurate estimation of subsurface geological parameters is essential for the oil industry. This is done by combining observations with an estimation from a model. Ensemble Kalman filter is a widely used method for inverse modeling, while ensemble transform particle filtering is a recently developed method that has been applied to estimate only a small number of parameters and in fluids. We show that for a high-dimensional inverse problem it is superior to an ensemble Kalman filter.
Accurate estimation of subsurface geological parameters is essential for the oil industry. This...
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