The research on full-waveform inversion method and its application based on Hessian operator preprocessing

Full-waveform inversion (FWI) can provide accurate velocity field for fine imaging in depth domain of seismic data. Its mathematics foundation determines that FWI is a strong nonlinearity with the solution being non-unique and the function being difficult to converge. In this paper, adjoint gradient...

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Main Authors: Fei-Long Yang, Hui-Li Zhang, Feng-Ming Yao, Lei Wang, Yun-Hong Zhu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Earth Science
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Online Access:https://www.frontiersin.org/articles/10.3389/feart.2025.1526073/full
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author Fei-Long Yang
Fei-Long Yang
Fei-Long Yang
Hui-Li Zhang
Feng-Ming Yao
Lei Wang
Yun-Hong Zhu
author_facet Fei-Long Yang
Fei-Long Yang
Fei-Long Yang
Hui-Li Zhang
Feng-Ming Yao
Lei Wang
Yun-Hong Zhu
author_sort Fei-Long Yang
collection DOAJ
description Full-waveform inversion (FWI) can provide accurate velocity field for fine imaging in depth domain of seismic data. Its mathematics foundation determines that FWI is a strong nonlinearity with the solution being non-unique and the function being difficult to converge. In this paper, adjoint gradient and Hessian operators are introduced into the calculation of FWI objective function to improve the inversion accuracy. Firstly, the adjoint gradient method is used to iteratively optimize the gradient of the model with respect to the residuals of the observed data when solving the objective function. Secondly, in view of the energy inconsistency gradient amplitudes across space, the diagonal elements of Hessian operator are used to scale the gradient, which ensures that the gradient amplitude is inversely proportional to the sensitivity of the synthesized data, thereby the imaging accuracy in deep and weak reflected areas. Finally, the sub-sag model and the overthrust model are used to perform the proposed method in this paper. The inversion results indicated that the FWI method with Hessian operator pre-processing significantly reduced the impact of abnormal amplitude of wave field gradient on structures near the shot detection point and deep structure, and enhanced the accuracy and resolution of FWI modeling. It provides a more accurate velocity model for fine imaging of deep complex structures.
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issn 2296-6463
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publisher Frontiers Media S.A.
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spelling doaj-art-9d502b24a10b429683e2ee7a97d842e42025-08-20T03:41:56ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632025-03-011310.3389/feart.2025.15260731526073The research on full-waveform inversion method and its application based on Hessian operator preprocessingFei-Long Yang0Fei-Long Yang1Fei-Long Yang2Hui-Li Zhang3Feng-Ming Yao4Lei Wang5Yun-Hong Zhu6School of Earth Sciences and Engineering, Xi’an Shiyou University, Xi’an, ChinaAcademician and Expert Workstation, Xi’an Shiyou University, Xi’an, ChinaShaanxi Key Laboratory of Petroleum Accumulation Geology, Xi’an, ChinaSchool of Earth Sciences and Engineering, Xi’an Shiyou University, Xi’an, ChinaBGP Inc., China National Petroleum Corporation, Xi'an Branch, Xi’an, ChinaTuha branch of China Petroleum Group Logging Co., Ltd., Ha mi, ChinaTarim Geophysical Prospecting Branch, BGP Inc., China National Petroleum Corporation, Korla, ChinaFull-waveform inversion (FWI) can provide accurate velocity field for fine imaging in depth domain of seismic data. Its mathematics foundation determines that FWI is a strong nonlinearity with the solution being non-unique and the function being difficult to converge. In this paper, adjoint gradient and Hessian operators are introduced into the calculation of FWI objective function to improve the inversion accuracy. Firstly, the adjoint gradient method is used to iteratively optimize the gradient of the model with respect to the residuals of the observed data when solving the objective function. Secondly, in view of the energy inconsistency gradient amplitudes across space, the diagonal elements of Hessian operator are used to scale the gradient, which ensures that the gradient amplitude is inversely proportional to the sensitivity of the synthesized data, thereby the imaging accuracy in deep and weak reflected areas. Finally, the sub-sag model and the overthrust model are used to perform the proposed method in this paper. The inversion results indicated that the FWI method with Hessian operator pre-processing significantly reduced the impact of abnormal amplitude of wave field gradient on structures near the shot detection point and deep structure, and enhanced the accuracy and resolution of FWI modeling. It provides a more accurate velocity model for fine imaging of deep complex structures.https://www.frontiersin.org/articles/10.3389/feart.2025.1526073/fullHessian operatorpre-processingadjoint gradientwave field gradientFWI
spellingShingle Fei-Long Yang
Fei-Long Yang
Fei-Long Yang
Hui-Li Zhang
Feng-Ming Yao
Lei Wang
Yun-Hong Zhu
The research on full-waveform inversion method and its application based on Hessian operator preprocessing
Frontiers in Earth Science
Hessian operator
pre-processing
adjoint gradient
wave field gradient
FWI
title The research on full-waveform inversion method and its application based on Hessian operator preprocessing
title_full The research on full-waveform inversion method and its application based on Hessian operator preprocessing
title_fullStr The research on full-waveform inversion method and its application based on Hessian operator preprocessing
title_full_unstemmed The research on full-waveform inversion method and its application based on Hessian operator preprocessing
title_short The research on full-waveform inversion method and its application based on Hessian operator preprocessing
title_sort research on full waveform inversion method and its application based on hessian operator preprocessing
topic Hessian operator
pre-processing
adjoint gradient
wave field gradient
FWI
url https://www.frontiersin.org/articles/10.3389/feart.2025.1526073/full
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