Shear-Wave Splitting Analysis Using Optimization Algorithms

AbstractShear-wave splitting (SWS) analysis is used to predict fractures in subsurface media. Specifically, two parameters relevant to SWS analysis (the azimuth of the fast shear wave and the time delay between the fast and slow shear waves) are used to quantify the main azimuth and...

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Main Authors: Zhengtao He, Yuyong Yang, Huailai Zhou
Format: Article
Language:English
Published: GeoScienceWorld 2022-12-01
Series:Lithosphere
Online Access:https://pubs.geoscienceworld.org/lithosphere/article/2022/1/3318196/619521/Shear-Wave-Splitting-Analysis-Using-Optimization
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author Zhengtao He
Yuyong Yang
Huailai Zhou
author_facet Zhengtao He
Yuyong Yang
Huailai Zhou
author_sort Zhengtao He
collection DOAJ
description AbstractShear-wave splitting (SWS) analysis is used to predict fractures in subsurface media. Specifically, two parameters relevant to SWS analysis (the azimuth of the fast shear wave and the time delay between the fast and slow shear waves) are used to quantify the main azimuth and degree of the fracture development, respectively. However, the algorithms of SWS analysis using a grid search have relatively low computational efficiency, as they need to calculate the objective function values of all grid points. To improve the efficiency of SWS analysis, we proposed new algorithms using the gradient descent, Newton, and advance-retreat methods. The new methods use the direction of the fastest gradient descent, the intersection points of the tangent plane of the first-order objective function with the zero plane, and narrowing the range of extremum points to determine the search path. Therefore, this removes the necessity to compare all grid points in the value region. We compared the three methods and the rotation-correlation method, and both synthetic and field data tests indicated that all three methods had higher computational efficiency than the traditional grid search method. Among the proposed methods, the gradient-descent method obtained the most accurate results for both synthetic and field data. Our study shows that SWS analysis combined with the gradient-descent method can accurately and efficiently obtain SWS parameters for fracture prediction.
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spelling doaj.art-326fc8864f83418f9954eadc5dc0eddd2023-05-25T14:42:21ZengGeoScienceWorldLithosphere1941-82641947-42532022-12-012022110.2113/2022/3318196Shear-Wave Splitting Analysis Using Optimization AlgorithmsZhengtao He0Yuyong Yang1http://orcid.org/0000-0001-8139-3923Huailai Zhou21 College of Geophysics Chengdu University of Technology Chengdu 610059 China cdut.edu.cn2 State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Chengdu University of Technology Chengdu 610059 China cdut.edu.cn1 College of Geophysics Chengdu University of Technology Chengdu 610059 China cdut.edu.cn AbstractShear-wave splitting (SWS) analysis is used to predict fractures in subsurface media. Specifically, two parameters relevant to SWS analysis (the azimuth of the fast shear wave and the time delay between the fast and slow shear waves) are used to quantify the main azimuth and degree of the fracture development, respectively. However, the algorithms of SWS analysis using a grid search have relatively low computational efficiency, as they need to calculate the objective function values of all grid points. To improve the efficiency of SWS analysis, we proposed new algorithms using the gradient descent, Newton, and advance-retreat methods. The new methods use the direction of the fastest gradient descent, the intersection points of the tangent plane of the first-order objective function with the zero plane, and narrowing the range of extremum points to determine the search path. Therefore, this removes the necessity to compare all grid points in the value region. We compared the three methods and the rotation-correlation method, and both synthetic and field data tests indicated that all three methods had higher computational efficiency than the traditional grid search method. Among the proposed methods, the gradient-descent method obtained the most accurate results for both synthetic and field data. Our study shows that SWS analysis combined with the gradient-descent method can accurately and efficiently obtain SWS parameters for fracture prediction.https://pubs.geoscienceworld.org/lithosphere/article/2022/1/3318196/619521/Shear-Wave-Splitting-Analysis-Using-Optimization
spellingShingle Zhengtao He
Yuyong Yang
Huailai Zhou
Shear-Wave Splitting Analysis Using Optimization Algorithms
Lithosphere
title Shear-Wave Splitting Analysis Using Optimization Algorithms
title_full Shear-Wave Splitting Analysis Using Optimization Algorithms
title_fullStr Shear-Wave Splitting Analysis Using Optimization Algorithms
title_full_unstemmed Shear-Wave Splitting Analysis Using Optimization Algorithms
title_short Shear-Wave Splitting Analysis Using Optimization Algorithms
title_sort shear wave splitting analysis using optimization algorithms
url https://pubs.geoscienceworld.org/lithosphere/article/2022/1/3318196/619521/Shear-Wave-Splitting-Analysis-Using-Optimization
work_keys_str_mv AT zhengtaohe shearwavesplittinganalysisusingoptimizationalgorithms
AT yuyongyang shearwavesplittinganalysisusingoptimizationalgorithms
AT huailaizhou shearwavesplittinganalysisusingoptimizationalgorithms