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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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Cited articles

Aanonsen, S. I., Nævdal, G., Oliver, D. S., Reynolds, A. C., and Vallès, B.: The ensemble Kalman filter in reservoir engineering – a review, SPE Journal, 14, 393–412, 2009.
Bishop, C. H., Etherton, B. J., and Majumdar, S. J.: Adaptive Sampling with the Ensemble Transform Kalman Filter. Part I: Theoretical Aspects, Mon. Weather Rev., 129, 420–436, 2001.
Chen, Y. and Oliver, D. S.: Levenberg–Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification, Computat. Geosci., 17, 689–703, 2013.
Cheng, Y. and Reich, S.: Data assimilation: a dynamical system perspective, Frontiers in Applied Dynamical Systems: Reviews and Tutorials, 2, 75–118, 2015.
Doucet, A., de Freitas, N., and Gordon, N.: Sequential Monte-Carlo Methods in Practice, Springer-Verlag, New York, 2001.
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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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