Addressing cycle‐skipping in full‐waveform inversion using acoustic wave energy

Abstract Limitations in acquisition technologies lead to insufficient low‐frequency signals in field seismic data. Local optimization methods are the common approaches for full‐waveform inversion. Inaccurate initial velocity models and lack of low‐frequency signals in seismic data typically cause the local‐gradient‐based full‐waveform inversion to converge to a local minimum due to cycle‐skipping. The existing energy‐based objective functions can generate artificial low‐frequency signals successfully by squaring the pressure but overlook the law of energy conservation, which may mislead model updates. To overcome this issue, we combine acoustic wave potential energy and kinetic energy to develop a new objective function that fits the acoustic wave energy. The new acoustic‐wave‐energy‐based full‐waveform inversion considers the law of energy conservation. The new system creates low‐frequency signals to avoid cycle‐skipping and produce an accurate smooth background velocity model, which provides a sufficient starting model for conventional full‐waveform inversion. Numerical examples demonstrate that the combination of acoustic‐wave‐energy‐based full‐waveform inversion and conventional full‐waveform inversion can deliver more faithful and accurate final results than conventional full‐waveform inversion alone.

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Publication Details

Journal
Geophysical Prospecting
Published
2024-10-14
DOI
https://doi.org/10.1111/1365-2478.13630
Citations
1
Primary Topic
Seismic Imaging and Inversion Techniques
Type
article
Field-Weighted Citation Impact
0.53

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article

Addressing cycle‐skipping in full‐waveform inversion using acoustic wave energy

Gang Yao, Zhenchun Li
1 citations
Geophysical Prospecting
Seismic Imaging and Inversion Techniques
0.53
article

Addressing cycle‐skipping in full‐waveform inversion using acoustic wave energy

Gang Yao, Zhenchun Li
article en
1 citations

Abstract

Abstract Limitations in acquisition technologies lead to insufficient low‐frequency signals in field seismic data. Local optimization methods are the common approaches for full‐waveform inversion. Inaccurate initial velocity models and lack of low‐frequency signals in seismic data typically cause the local‐gradient‐based full‐waveform inversion to converge to a local minimum due to cycle‐skipping. The existing energy‐based objective functions can generate artificial low‐frequency signals successfully by squaring the pressure but overlook the law of energy conservation, which may mislead model updates. To overcome this issue, we combine acoustic wave potential energy and kinetic energy to develop a new objective function that fits the acoustic wave energy. The new acoustic‐wave‐energy‐based full‐waveform inversion considers the law of energy conservation. The new system creates low‐frequency signals to avoid cycle‐skipping and produce an accurate smooth background velocity model, which provides a sufficient starting model for conventional full‐waveform inversion. Numerical examples demonstrate that the combination of acoustic‐wave‐energy‐based full‐waveform inversion and conventional full‐waveform inversion can deliver more faithful and accurate final results than conventional full‐waveform inversion alone.

Geophysical ProspectingVol. 73(3)
China University of Petroleum, Beijing (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 33%
Seismic Imaging and Inversion Techniques
0.53
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Addressing cycle‐skipping in full‐waveform inversion using acoustic wave energy — Gang Yao, Zhenchun Li · Geophysical Prospecting (2024) | TGRS Research Map | TGRS