A stochastic approach to uncertainty quantification in residual moveout analysis

T. Johng-Ay; E. Landa; S. Dossou-Gbété; L. Bordes

doi:10.1016/j.jappgeo.2015.02.023

A stochastic approach to uncertainty quantification in residual moveout analysis

T. Johng-Ay^*, E. Landa, S. Dossou-Gbété, L. Bordes

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

Abstract

Oil and gas exploration and production relies usually on the interpretation of a single seismic image, which is obtained from observed data. However, the statistical nature of seismic data and the various approximations and assumptions are sources of uncertainties which may corrupt the evaluation of parameters. The quantification of these uncertainties is a major issue which supposes to help in decisions that have important social and commercial implications. The residual moveout analysis, which is an important step in seismic data processing is usually performed by a deterministic approach. In this paper we discuss a Bayesian approach to the uncertainty analysis.

Original language	English
Pages (from-to)	52-59
Number of pages	8
Journal	Journal of Applied Geophysics
Volume	117
DOIs	https://doi.org/10.1016/j.jappgeo.2015.02.023
State	Published - 1 Jun 2015
Externally published	Yes

Keywords

Bayesian approach
Common image gathers
Residual moveout analysis
Uncertainty analysis

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10.1016/j.jappgeo.2015.02.023

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title = "A stochastic approach to uncertainty quantification in residual moveout analysis",

abstract = "Oil and gas exploration and production relies usually on the interpretation of a single seismic image, which is obtained from observed data. However, the statistical nature of seismic data and the various approximations and assumptions are sources of uncertainties which may corrupt the evaluation of parameters. The quantification of these uncertainties is a major issue which supposes to help in decisions that have important social and commercial implications. The residual moveout analysis, which is an important step in seismic data processing is usually performed by a deterministic approach. In this paper we discuss a Bayesian approach to the uncertainty analysis.",

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author = "T. Johng-Ay and E. Landa and S. Dossou-Gb{\'e}t{\'e} and L. Bordes",

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AU - Johng-Ay, T.

AU - Landa, E.

AU - Dossou-Gbété, S.

AU - Bordes, L.

PY - 2015/6/1

Y1 - 2015/6/1

N2 - Oil and gas exploration and production relies usually on the interpretation of a single seismic image, which is obtained from observed data. However, the statistical nature of seismic data and the various approximations and assumptions are sources of uncertainties which may corrupt the evaluation of parameters. The quantification of these uncertainties is a major issue which supposes to help in decisions that have important social and commercial implications. The residual moveout analysis, which is an important step in seismic data processing is usually performed by a deterministic approach. In this paper we discuss a Bayesian approach to the uncertainty analysis.

AB - Oil and gas exploration and production relies usually on the interpretation of a single seismic image, which is obtained from observed data. However, the statistical nature of seismic data and the various approximations and assumptions are sources of uncertainties which may corrupt the evaluation of parameters. The quantification of these uncertainties is a major issue which supposes to help in decisions that have important social and commercial implications. The residual moveout analysis, which is an important step in seismic data processing is usually performed by a deterministic approach. In this paper we discuss a Bayesian approach to the uncertainty analysis.

KW - Bayesian approach

KW - Common image gathers

KW - Residual moveout analysis

KW - Uncertainty analysis

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JO - Journal of Applied Geophysics

JF - Journal of Applied Geophysics

ER -

A stochastic approach to uncertainty quantification in residual moveout analysis

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Keywords

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