Review of nonlinear kalman, ensemble and particle filtering with application to the reservoir history matching problem

Xiaodong Luo; Ibrahim Hoteit; Lian Duan; Wenhui Wang

Review of nonlinear kalman, ensemble and particle filtering with application to the reservoir history matching problem

Xiaodong Luo^*, Ibrahim Hoteit, Lian Duan, Wenhui Wang

^*Corresponding author for this work

Physical Sciences and Engineering

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

6 Scopus citations

Abstract

This chapter reviews the recent advances in Bayesian filtering approaches, with the focus on those suitable for data assimilation in high-dimensional systems. We discuss the similarities and differences of these filtering approaches, and compare their performance in an application to the history matching problem in a synthetic, twodimensional, oil-water reservoir model.

Original language	English (US)
Title of host publication	Nonlinear Estimation and Applications to Industrial Systems Control
Publisher	Nova Science Publishers, Inc.
Pages	197-224
Number of pages	28
ISBN (Print)	9781619428980
State	Published - Nov 2012

Keywords

Data assimilation
Ensemble Kalman filter
Gaussian sum filter
History matching in reservoir models
Nonlinear Kalman filter
Particle filter
Sequential Bayesian filtering

ASJC Scopus subject areas

General Social Sciences

Cite this

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title = "Review of nonlinear kalman, ensemble and particle filtering with application to the reservoir history matching problem",

abstract = "This chapter reviews the recent advances in Bayesian filtering approaches, with the focus on those suitable for data assimilation in high-dimensional systems. We discuss the similarities and differences of these filtering approaches, and compare their performance in an application to the history matching problem in a synthetic, twodimensional, oil-water reservoir model.",

keywords = "Data assimilation, Ensemble Kalman filter, Gaussian sum filter, History matching in reservoir models, Nonlinear Kalman filter, Particle filter, Sequential Bayesian filtering",

author = "Xiaodong Luo and Ibrahim Hoteit and Lian Duan and Wenhui Wang",

year = "2012",

month = nov,

language = "English (US)",

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booktitle = "Nonlinear Estimation and Applications to Industrial Systems Control",

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Review of nonlinear kalman, ensemble and particle filtering with application to the reservoir history matching problem. / Luo, Xiaodong; Hoteit, Ibrahim; Duan, Lian et al.
Nonlinear Estimation and Applications to Industrial Systems Control. Nova Science Publishers, Inc., 2012. p. 197-224.

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

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T1 - Review of nonlinear kalman, ensemble and particle filtering with application to the reservoir history matching problem

AU - Luo, Xiaodong

AU - Hoteit, Ibrahim

AU - Duan, Lian

AU - Wang, Wenhui

PY - 2012/11

Y1 - 2012/11

N2 - This chapter reviews the recent advances in Bayesian filtering approaches, with the focus on those suitable for data assimilation in high-dimensional systems. We discuss the similarities and differences of these filtering approaches, and compare their performance in an application to the history matching problem in a synthetic, twodimensional, oil-water reservoir model.

AB - This chapter reviews the recent advances in Bayesian filtering approaches, with the focus on those suitable for data assimilation in high-dimensional systems. We discuss the similarities and differences of these filtering approaches, and compare their performance in an application to the history matching problem in a synthetic, twodimensional, oil-water reservoir model.

KW - Data assimilation

KW - Ensemble Kalman filter

KW - Gaussian sum filter

KW - History matching in reservoir models

KW - Nonlinear Kalman filter

KW - Particle filter

KW - Sequential Bayesian filtering

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M3 - Chapter

AN - SCOPUS:84895414428

SN - 9781619428980

SP - 197

EP - 224

BT - Nonlinear Estimation and Applications to Industrial Systems Control

PB - Nova Science Publishers, Inc.

ER -

Review of nonlinear kalman, ensemble and particle filtering with application to the reservoir history matching problem

Abstract

Keywords

ASJC Scopus subject areas

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