A new methodology for Bayesian history matching using parallel interacting Markov chain Monte Carlo-Reference-Cited by-同舟云学术

A new methodology for Bayesian history matching using parallel interacting Markov chain Monte Carlo

Published:2017-05-15 Issue:4 Volume:26 Page:498-529
ISSN:1741-5977
Container-title:Inverse Problems in Science and Engineering
language:en
Short-container-title:Inverse Problems in Science and Engineering

Author:

Maschio Célio¹,J. Schiozer Denis¹

Affiliation:

1. Center for Petroleum Studies (CEPETRO), (Department of Energy – Division of Petroleum Engineering), School of Mechanical Engineering, University of Campinas (UNICAMP) – Campinas, São Paulo, Brazil

Funder

Petrobras

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,General Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/17415977.2017.1322078

Reference38 articles.

1. A review of Markov Chain Monte Carlo and information theory tools for inverse problems in subsurface flow

2. Markov chain Monte Carlo method and its application

3. Equation of State Calculations by Fast Computing Machines

4. Monte Carlo sampling methods using Markov chains and their applications

5. The Metropolis Algorithm

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