Bayesian partition models for subsurface characterization

Y. Efendiev; A. Datta-Gupta; K. Hwang; X. Ma; Bani Mallick

doi:10.1002/9780470685853.ch6

Bayesian partition models for subsurface characterization

Y. Efendiev, A. Datta-Gupta, K. Hwang, X. Ma, Bani Mallick

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

Original language	English (US)
Title of host publication	Large-Scale Inverse Problems and Quantification of Uncertainty
Publisher	Wiley
Pages	107-122
Number of pages	16
ISBN (Electronic)	9780470685853
ISBN (Print)	9780470697436
DOIs	https://doi.org/10.1002/9780470685853.ch6
State	Published - Jan 1 2010
Externally published	Yes

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

General Mathematics

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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 = "Y. Efendiev and A. Datta-Gupta and K. Hwang and X. Ma and Bani Mallick",

year = "2010",

month = jan,

day = "1",

doi = "10.1002/9780470685853.ch6",

language = "English (US)",

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booktitle = "Large-Scale Inverse Problems and Quantification of Uncertainty",

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TY - CHAP

T1 - Bayesian partition models for subsurface characterization

AU - Efendiev, Y.

AU - Datta-Gupta, A.

AU - Hwang, K.

AU - Ma, X.

AU - Mallick, Bani

PY - 2010/1/1

Y1 - 2010/1/1

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 - Wiley

ER -

Bayesian partition models for subsurface characterization

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this