Bayesian Partition Models for Subsurface Characterization

Yalchin Efendiev; A. Datta-Gupta; K. Hwang; X. Ma; B. Mallick

doi:10.1002/9780470685853.ch6

Bayesian Partition Models for Subsurface Characterization

Yalchin Efendiev^*, A. Datta-Gupta, K. Hwang, X. Ma, B. Mallick

^*Corresponding author for this work

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Scopus citations

Original language	English (US)
Title of host publication	Large-Scale Inverse Problems and Quantification of Uncertainty
Publisher	John Wiley and Sons
Pages	107-122
Number of pages	16
ISBN (Print)	9780470697436
DOIs	https://doi.org/10.1002/9780470685853.ch6
State	Published - Oct 12 2010

Keywords

Algorithm two-stage MCMC
Bayesian Partition Model (BPM)
Bayesian partition models - for subsurface characterization
Model equations and problem setting
New Bayesian approach, BPM in surface fitting - splitting space into unknown number of disjoint regions
Permeability field realizations
Reversible Jump Markov chain Monte Carlo (RJ-MCMC) methods
Simulation based Markov chain Monte Carlo (MCMC method) - from probability distribution samples
Transient pressure response, tracer or production history - preferential flow path or flow barriers
Uncertainties, of reservoir lithofacies, porosity, and permeability - and uncertainty in reservoir performance forecasting

ASJC Scopus subject areas

Mathematics(all)

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10.1002/9780470685853.ch6

Cite this

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title = "Bayesian Partition Models for Subsurface Characterization",

keywords = "Algorithm two-stage MCMC, Bayesian Partition Model (BPM), Bayesian partition models - for subsurface characterization, Model equations and problem setting, New Bayesian approach, BPM in surface fitting - splitting space into unknown number of disjoint regions, Permeability field realizations, Reversible Jump Markov chain Monte Carlo (RJ-MCMC) methods, Simulation based Markov chain Monte Carlo (MCMC method) - from probability distribution samples, Transient pressure response, tracer or production history - preferential flow path or flow barriers, Uncertainties, of reservoir lithofacies, porosity, and permeability - and uncertainty in reservoir performance forecasting",

author = "Yalchin Efendiev and A. Datta-Gupta and K. Hwang and X. Ma and B. Mallick",

year = "2010",

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day = "12",

doi = "10.1002/9780470685853.ch6",

language = "English (US)",

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TY - CHAP

T1 - Bayesian Partition Models for Subsurface Characterization

AU - Efendiev, Yalchin

AU - Datta-Gupta, A.

AU - Hwang, K.

AU - Ma, X.

AU - Mallick, B.

PY - 2010/10/12

Y1 - 2010/10/12

KW - Algorithm two-stage MCMC

KW - Bayesian Partition Model (BPM)

KW - Bayesian partition models - for subsurface characterization

KW - Model equations and problem setting

KW - New Bayesian approach, BPM in surface fitting - splitting space into unknown number of disjoint regions

KW - Permeability field realizations

KW - Reversible Jump Markov chain Monte Carlo (RJ-MCMC) methods

KW - Simulation based Markov chain Monte Carlo (MCMC method) - from probability distribution samples

KW - Transient pressure response, tracer or production history - preferential flow path or flow barriers

KW - Uncertainties, of reservoir lithofacies, porosity, and permeability - and uncertainty in reservoir performance forecasting

UR - http://www.scopus.com/inward/record.url?scp=84885499941&partnerID=8YFLogxK

U2 - 10.1002/9780470685853.ch6

DO - 10.1002/9780470685853.ch6

M3 - Chapter

AN - SCOPUS:84885499941

SN - 9780470697436

SP - 107

EP - 122

BT - Large-Scale Inverse Problems and Quantification of Uncertainty

PB - John Wiley and Sons

ER -

Bayesian Partition Models for Subsurface Characterization

Keywords

ASJC Scopus subject areas

Access to Document

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