Bayesian updating via bootstrap filtering combined with data-driven polynomial chaos expansions: methodology and application to history matching for carbon dioxide storage in geological formations

DOI10.1007/s10596-013-9350-6zbMath1382.86022OpenAlexW1988639030MaRDI QIDQ1693616

Sergey Oladyshkin, Holger Class, Wolfgang Nowak

Publication date: 31 January 2018

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-013-9350-6

zbMATH Keywords

chaosuncertainty quantificationhistory matchingBayesian updating\(\text{CO}_2\) storagearbitrary polynomialbootstrap filter

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Bootstrap, jackknife and other resampling methods (62F40) Geological problems (86A60)

Related Items

Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario ⋮ A fully Bayesian sparse polynomial chaos expansion approach with joint priors on the coefficients and global selection of terms ⋮ Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems ⋮ Surrogate-based Bayesian comparison of computationally expensive models: application to microbially induced calcite precipitation

Uses Software

• EnKF
• KernSmooth

Cites Work

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• A deterministic filter for non-Gaussian Bayesian estimation -- Applications to dynamical system estimation with noisy measurements
• A multi-resolution workflow to generate high-resolution models constrained to dynamic data
• On optimization algorithms for the reservoir oil well placement problem
• Multi-element probabilistic collocation method in high dimensions
• Stochastic spectral methods for efficient Bayesian solution of inverse problems
• Kernel principal component analysis for efficient, differentiable parametrization of multipoint geostatistics
• Variance reduction in Monte Carlo computations using multi-dimensional Hermite polynomials
• An efficient, high-order perturbation approach for flow in random porous media via Karhunen-Loève and polynomial expansions.
• Modeling uncertainty in flow simulations via generalized polynomial chaos.
• Estimate CO\(_{2}\) storage capacity of the Johansen formation: numerical investigations beyond the benchmarking exercise
• Recent progress on reservoir history matching: a review
• Adapted polynomial chaos expansion for failure detection
• Efficient real-time reservoir management using adjoint-based optimal control and model updating
• Calculating derivatives for automatic history matching
• On the construction and analysis of stochastic models: characterization and propagation of the errors associated with limited data
• \(\text{CO}_{2}\) leakage through an abandoned well: problem-oriented benchmarks
• Polynomial Chaos in Stochastic Finite Elements
• Multi-Element Generalized Polynomial Chaos for Arbitrary Probability Measures
• Fast Bayesian approach for parameter estimation
• Spectral Methods for Uncertainty Quantification
• Subdomain radial basis collocation method for heterogeneous media
• Identification of Parameters in Distributed Parameter Systems by Regularization
• Applications of the methods of weighted residuals in system science
• Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure
• Inverse Problem Theory and Methods for Model Parameter Estimation
• The Homogeneous Chaos
• Data Assimilation
• A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data