Localization and regularization for iterative ensemble smoothers
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Publication:1702330
DOI10.1007/s10596-016-9599-7zbMath1387.86042OpenAlexW2547561522MaRDI QIDQ1702330
Publication date: 28 February 2018
Published in: Computational Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10596-016-9599-7
regularizationlocalizationlocal analysisensemble Kalman filterhistory matchingiterative ensemble smoother
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Efficient derivative-free Bayesian inference for large-scale inverse problems ⋮ Seismic data assimilation with an imperfect model ⋮ Localized ensemble Kalman inversion ⋮ Ensemble Transform Algorithms for Nonlinear Smoothing Problems ⋮ A robust adaptive iterative ensemble smoother scheme for practical history matching applications
Uses Software
Cites Work
- Relation between two common localisation methods for the EnKF
- Combining sensitivities and prior information for covariance localization in the ensemble Kalman filter for petroleum reservoir applications
- Cross-covariances and localization for EnKF in multiphase flow data assimilation
- Estimation of high-dimensional prior and posterior covariance matrices in Kalman filter vari\-ants
- Levenberg-Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification
- Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter
- Data Assimilation
- Calculation of the inverse of the covariance
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