Multiscale phase inversion of anisotropic data

Shihang Feng; Lei Fu; Zongcai Feng; Gerard T. Schuster

doi:10.1190/segam2019-3216198.1

Multiscale phase inversion of anisotropic data

Shihang Feng, Lei Fu, Zongcai Feng, Gerard T. Schuster

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

The multiscale phase inversion (MPI) methodology is extended to anisotropic media. MPI is developed to avoid the cycle-skipping problem of full waveform inversion (FWI) by temporally integrating the traces several times. The input data are also filtered into different narrow frequency bands for the MPI implementation and the magnitude spectrum of the recorded data is used to replace that of the predicted data. The simultaneous inversion of anisotropic parameters vp0 and e is performed while d is set as 0. Numerical tests on synthetic data and field data demonstrate the superiority of this method compared to conventional multiscale full waveform inversion.

Original language	English (US)
Title of host publication	SEG Technical Program Expanded Abstracts 2019
Publisher	Society of Exploration Geophysicists
Pages	1430-1434
Number of pages	5
DOIs	https://doi.org/10.1190/segam2019-3216198.1
State	Published - Aug 10 2019

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10.1190/segam2019-3216198.1

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title = "Multiscale phase inversion of anisotropic data",

abstract = "The multiscale phase inversion (MPI) methodology is extended to anisotropic media. MPI is developed to avoid the cycle-skipping problem of full waveform inversion (FWI) by temporally integrating the traces several times. The input data are also filtered into different narrow frequency bands for the MPI implementation and the magnitude spectrum of the recorded data is used to replace that of the predicted data. The simultaneous inversion of anisotropic parameters vp0 and e is performed while d is set as 0. Numerical tests on synthetic data and field data demonstrate the superiority of this method compared to conventional multiscale full waveform inversion.",

author = "Shihang Feng and Lei Fu and Zongcai Feng and Schuster, {Gerard T.}",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their financial support. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST and the IT Research Computing Group. We thank them for providing the computational resources required for carrying out this work.",

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doi = "10.1190/segam2019-3216198.1",

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AU - Schuster, Gerard T.

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their financial support. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST and the IT Research Computing Group. We thank them for providing the computational resources required for carrying out this work.

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N2 - The multiscale phase inversion (MPI) methodology is extended to anisotropic media. MPI is developed to avoid the cycle-skipping problem of full waveform inversion (FWI) by temporally integrating the traces several times. The input data are also filtered into different narrow frequency bands for the MPI implementation and the magnitude spectrum of the recorded data is used to replace that of the predicted data. The simultaneous inversion of anisotropic parameters vp0 and e is performed while d is set as 0. Numerical tests on synthetic data and field data demonstrate the superiority of this method compared to conventional multiscale full waveform inversion.

AB - The multiscale phase inversion (MPI) methodology is extended to anisotropic media. MPI is developed to avoid the cycle-skipping problem of full waveform inversion (FWI) by temporally integrating the traces several times. The input data are also filtered into different narrow frequency bands for the MPI implementation and the magnitude spectrum of the recorded data is used to replace that of the predicted data. The simultaneous inversion of anisotropic parameters vp0 and e is performed while d is set as 0. Numerical tests on synthetic data and field data demonstrate the superiority of this method compared to conventional multiscale full waveform inversion.

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BT - SEG Technical Program Expanded Abstracts 2019

PB - Society of Exploration Geophysicists

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Multiscale phase inversion of anisotropic data

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