A new correlation based least-squares reverse time migration

Feipeng Li; Jinghuai Gao; Xiudi Jiang; Wenbo Sun

doi:10.1190/segam2018-2995223.1

A new correlation based least-squares reverse time migration

Feipeng Li
, Jinghuai Gao
, Xiudi Jiang
, Wenbo Sun

Faculty of Electronic and Information Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

Least-squares reverse time migration (LSRTM) applies reverse time migration and demigration as migration and modeling operator to minimize the difference between the simulated and observed seismic data. We propose a new scheme for LSRTM and derive its corresponding conjugate gradient method to seek for the optimal image. By applying a correlation based objective function to LSRTM, we are able to emphasize not only on amplitude matching but also on phase information. The objective function incorporates the auto-correlation besides the cross-correlation. And it is the least-square of the two correlations. Numerical tests on synthetic models demonstrate that our new LSRTM scheme improves true amplitude imaging in the case of severely undersampled data and simultaneous source data.

Original language	English
Pages	4236-4240
Number of pages	5
DOIs	https://doi.org/10.1190/segam2018-2995223.1
State	Published - 2019
Event	88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018 - Anaheim, United States Duration: 14 Oct 2018 → 19 Oct 2018

Conference

Conference	88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018
Country/Territory	United States
City	Anaheim
Period	14/10/18 → 19/10/18

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10.1190/segam2018-2995223.1

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title = "A new correlation based least-squares reverse time migration",

abstract = "Least-squares reverse time migration (LSRTM) applies reverse time migration and demigration as migration and modeling operator to minimize the difference between the simulated and observed seismic data. We propose a new scheme for LSRTM and derive its corresponding conjugate gradient method to seek for the optimal image. By applying a correlation based objective function to LSRTM, we are able to emphasize not only on amplitude matching but also on phase information. The objective function incorporates the auto-correlation besides the cross-correlation. And it is the least-square of the two correlations. Numerical tests on synthetic models demonstrate that our new LSRTM scheme improves true amplitude imaging in the case of severely undersampled data and simultaneous source data.",

author = "Feipeng Li and Jinghuai Gao and Xiudi Jiang and Wenbo Sun",

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AU - Li, Feipeng

AU - Gao, Jinghuai

AU - Jiang, Xiudi

AU - Sun, Wenbo

PY - 2019

Y1 - 2019

N2 - Least-squares reverse time migration (LSRTM) applies reverse time migration and demigration as migration and modeling operator to minimize the difference between the simulated and observed seismic data. We propose a new scheme for LSRTM and derive its corresponding conjugate gradient method to seek for the optimal image. By applying a correlation based objective function to LSRTM, we are able to emphasize not only on amplitude matching but also on phase information. The objective function incorporates the auto-correlation besides the cross-correlation. And it is the least-square of the two correlations. Numerical tests on synthetic models demonstrate that our new LSRTM scheme improves true amplitude imaging in the case of severely undersampled data and simultaneous source data.

AB - Least-squares reverse time migration (LSRTM) applies reverse time migration and demigration as migration and modeling operator to minimize the difference between the simulated and observed seismic data. We propose a new scheme for LSRTM and derive its corresponding conjugate gradient method to seek for the optimal image. By applying a correlation based objective function to LSRTM, we are able to emphasize not only on amplitude matching but also on phase information. The objective function incorporates the auto-correlation besides the cross-correlation. And it is the least-square of the two correlations. Numerical tests on synthetic models demonstrate that our new LSRTM scheme improves true amplitude imaging in the case of severely undersampled data and simultaneous source data.

UR - https://www.scopus.com/pages/publications/85059390084

U2 - 10.1190/segam2018-2995223.1

DO - 10.1190/segam2018-2995223.1

M3 - 论文

AN - SCOPUS:85059390084

SP - 4236

EP - 4240

T2 - 88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018

Y2 - 14 October 2018 through 19 October 2018

ER -

A new correlation based least-squares reverse time migration

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