Integrating production data under uncertainty by parallel interacting Markov chains on a reduced dimensional space

DOI10.1007/s10596-008-9108-8zbMath1171.86384OpenAlexW2105642654MaRDI QIDQ732190

Thomas Romary

Publication date: 9 October 2009

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

Full work available at URL: https://doi.org/10.1007/s10596-008-9108-8

zbMATH Keywords

inverse problemreservoir characterizationhistory matchingKarhunen-Loève expansioninteracting Markov chains

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Geostatistics (86A32) Potentials, prospecting (86A20)

Related Items (8)

History matching of statistically anisotropic fields using the Karhunen-Loeve expansion-based global parameterization technique ⋮ New parameterizations for Bayesian seismic tomography ⋮ Adaptive conditioning of multiple-point statistical facies simulation to flow data with probability maps ⋮ Uncertainty assessment for inverse problems in high dimensional spaces using particle swarm optimization and model reduction techniques ⋮ Recent progress on reservoir history matching: a review ⋮ History matching of approximated lithofacies models under uncertainty ⋮ Multiscale parameterization of petrophysical properties for efficient history-matching ⋮ Bayesian inversion by parallel interacting Markov chains

Uses Software

• EnKF
• ARPACK

Cites Work

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• Equi-energy sampler with applications in statistical inference and statistical mechanics
• On the ergodicity properties of some adaptive MCMC algorithms
• The probability perturbation method: a new look at Bayesian inverse modeling
• Efficient real-time reservoir management using adjoint-based optimal control and model updating
• Coarse-gradient Langevin algorithms for dynamic data integration and uncertainty quantification
• ARPACK Users' Guide
• Inverse Problem Theory and Methods for Model Parameter Estimation
• Non-linear Markov Chain Monte Carlo
• An adaptive Metropolis algorithm

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