Reversible and non-reversible Markov chain Monte Carlo algorithms for reservoir simulation problems

DOI10.1007/s10596-020-09947-4zbMath1439.65004arXiv1903.06960OpenAlexW3011594197MaRDI QIDQ2192802

Michela Ottobre, I. Fursov, Gabriel J. Lord, Paul W. Dobson

Publication date: 18 August 2020

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

Full work available at URL: https://arxiv.org/abs/1903.06960

zbMATH Keywords

Markov chain Monte Carlo methodsnon-reversible Markov chainshigh-dimensional samplingsubsurface reservoir simulation

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Potentials, prospecting (86A20)

Related Items (3)

Efficient Bayesian Computation for Low-Photon Imaging Problems ⋮ Geometric Integration of Measure-Preserving Flows for Sampling ⋮ Non-reversible processes: GENERIC, hypocoercivity and fluctuations

Uses Software

• ECLIPSE

Cites Work

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• The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method
• Variance reduction using nonreversible Langevin samplers
• Markov chain Monte Carlo and irreversibility
• Hybrid Monte Carlo on Hilbert spaces
• Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains
• Calculating derivatives for automatic history matching
• Variance reduction for irreversible Langevin samplers and diffusion on graphs
• Irreversible Langevin samplers and variance reduction: a large deviations approach
• Hypocoercivity
• Markov Chain Monte Carlo and Numerical Differential Equations
• A function space HMC algorithm with second order Langevin diffusion limit

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