An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes

Abstract A new automatic method for dispersion curve picking based on Hessian matrix attributes is proposed, on which, an algorithm is developed in this paper. The algorithm is based on dispersion power spectra transformed from surface waves. It fulfills the automatic picking of the surface wave dis...

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Main Authors: Hou Xiaoping, Yu Jiashun, Yuan Jianlong, Fu Xiaobo, Fan Xinran, Han Chao, Liu Zhigang, Qian Guang, Zhou Qiang
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-04954-w
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author Hou Xiaoping
Yu Jiashun
Yuan Jianlong
Fu Xiaobo
Fan Xinran
Han Chao
Liu Zhigang
Qian Guang
Zhou Qiang
author_facet Hou Xiaoping
Yu Jiashun
Yuan Jianlong
Fu Xiaobo
Fan Xinran
Han Chao
Liu Zhigang
Qian Guang
Zhou Qiang
author_sort Hou Xiaoping
collection DOAJ
description Abstract A new automatic method for dispersion curve picking based on Hessian matrix attributes is proposed, on which, an algorithm is developed in this paper. The algorithm is based on dispersion power spectra transformed from surface waves. It fulfills the automatic picking of the surface wave dispersion curves from the fundamental to high orders, by ridge searching and extraction, ridge line segment connection, dispersion curve selecting and order sorting. The algorithm does not have to rely on model training and there is no manual interaction requirement. This inherent efficiency advantage of the algorithm provides an efficient tool for surface wave dispersion curve picking for large projects such as oil and gas exploration. The algorithm is tested using two conceptual models. On the synthetic data of the test models, surface wave dispersion curves up to the 8th order are successfully picked, which shows the excellent picking ability of the method. Further comparative experiments show that the algorithm is superior to other methods in terms of picking accuracy, completeness, anti-noise performance and computation efficiency. In order to evaluate the practicability of the algorithm, we applied it to surface wave data from an industrial prospecting project. Three dispersion curves, including the fundamental order, first order and second order, are successfully obtained. The dispersion curve inversion result matches perfectly with the vertical seismic profile. This application case verified the effectiveness and practicability of the algorithm.
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institution Kabale University
issn 2045-2322
language English
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series Scientific Reports
spelling doaj-art-3185e35ea756499882acbafecf44e2d82025-08-20T03:45:32ZengNature PortfolioScientific Reports2045-23222025-07-0115112510.1038/s41598-025-04954-wAn automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributesHou Xiaoping0Yu Jiashun1Yuan Jianlong2Fu Xiaobo3Fan Xinran4Han Chao5Liu Zhigang6Qian Guang7Zhou Qiang8College of Geophysics, Chengdu University of TechnologyCollege of Geophysics, Chengdu University of TechnologyCollege of Geophysics, Chengdu University of TechnologyBGP Inc., China National Petroleum CorporationCollege of Geophysics, Chengdu University of TechnologyCollege of Geophysics, Chengdu University of TechnologyBGP Inc., China National Petroleum CorporationCollege of Geophysics, Chengdu University of TechnologyCollege of Geophysics, Chengdu University of TechnologyAbstract A new automatic method for dispersion curve picking based on Hessian matrix attributes is proposed, on which, an algorithm is developed in this paper. The algorithm is based on dispersion power spectra transformed from surface waves. It fulfills the automatic picking of the surface wave dispersion curves from the fundamental to high orders, by ridge searching and extraction, ridge line segment connection, dispersion curve selecting and order sorting. The algorithm does not have to rely on model training and there is no manual interaction requirement. This inherent efficiency advantage of the algorithm provides an efficient tool for surface wave dispersion curve picking for large projects such as oil and gas exploration. The algorithm is tested using two conceptual models. On the synthetic data of the test models, surface wave dispersion curves up to the 8th order are successfully picked, which shows the excellent picking ability of the method. Further comparative experiments show that the algorithm is superior to other methods in terms of picking accuracy, completeness, anti-noise performance and computation efficiency. In order to evaluate the practicability of the algorithm, we applied it to surface wave data from an industrial prospecting project. Three dispersion curves, including the fundamental order, first order and second order, are successfully obtained. The dispersion curve inversion result matches perfectly with the vertical seismic profile. This application case verified the effectiveness and practicability of the algorithm.https://doi.org/10.1038/s41598-025-04954-wSurface waveDispersion curveAutomatic pickingHessian analysis
spellingShingle Hou Xiaoping
Yu Jiashun
Yuan Jianlong
Fu Xiaobo
Fan Xinran
Han Chao
Liu Zhigang
Qian Guang
Zhou Qiang
An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes
Scientific Reports
Surface wave
Dispersion curve
Automatic picking
Hessian analysis
title An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes
title_full An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes
title_fullStr An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes
title_full_unstemmed An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes
title_short An automatic algorithm for surface wave dispersion curve picking based on Hessian matrix attributes
title_sort automatic algorithm for surface wave dispersion curve picking based on hessian matrix attributes
topic Surface wave
Dispersion curve
Automatic picking
Hessian analysis
url https://doi.org/10.1038/s41598-025-04954-w
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