Calibration of imperfect models to biased observations
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Publication:1710300
DOI10.1007/s10596-017-9678-4zbMath1405.86024OpenAlexW2733830335MaRDI QIDQ1710300
Dean S. Oliver, Miguel Alfonzo
Publication date: 22 January 2019
Published in: Computational Geosciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10596-017-9678-4
model calibrationpredictabilitydata assimilationhistory matchingmodel errorrandomized maximum likelihoodobservation biasmodel improvement
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Cites Work
- A well-conditioned estimator for large-dimensional covariance matrices
- Minimization for conditional simulation: relationship to optimal transport
- A probability conditioning method (PCM) for nonlinear flow data integration into multipoint statistical facies simulation
- Bayesianly justifiable and relevant frequency calculations for the applied statistician
- Levenberg-Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification
- Recent progress on reservoir history matching: a review
- A multiscale method for distributed parameter estimation with application to reservoir history matching
- Bayesian Calibration of Computer Models
- Estimating and including observation-error correlations in data assimilation
- Geostatistics
- Computer Model Calibration Using High-Dimensional Output
- P Values for Composite Null Models
- Philosophy and the practice of Bayesian statistics
- Metropolized Randomized Maximum Likelihood for Improved Sampling from Multimodal Distributions
- Correlated observation errors in data assimilation
- Statistical Methods for Eliciting Probability Distributions
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