Articles | Volume 25, issue 4
https://doi.org/10.5194/npg-25-731-2018
https://doi.org/10.5194/npg-25-731-2018
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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Latest update: 27 Mar 2024
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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.