A simplified calculation for adaptive coefficients of finite-difference frequency-domain method
The finite-difference frequency domain (FDFD) method is widely applied for simulating seismic wavefields, and a key to achieving successful FDFD simulation is to construct FDFD coefficients that can effectively suppress numerical dispersion. Among the existing FDFD coefficients for seismic wavefield...
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Veröffentlicht in: | Applied geophysics 2023-09, Vol.20 (3), p.262-277 |
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description | The finite-difference frequency domain (FDFD) method is widely applied for simulating seismic wavefields, and a key to achieving successful FDFD simulation is to construct FDFD coefficients that can effectively suppress numerical dispersion. Among the existing FDFD coefficients for seismic wavefield simulation, adaptive FDFD coefficients that vary with the number of wavelengths per grid can suppress numerical dispersion to the maximum extent. The current methods for calculating adaptive FDFD coefficients involve numerical integration, conjugate gradient (CG) optimization, sequential initial value selection, and smooth regularization, which are difficult to implement and inefficient in calculations. To simplify the calculation of adaptive FDFD coefficients and improve the corresponding computational efficiency, this paper proposes a new method for calculating adaptive FDFD coefficients. First, plane-wave solutions with different discrete propagation angles are substituted in the FDFD scheme, and the corresponding least-squares problem is constructed. As this problem is ill-conditioned and obtaining smooth adaptive FDFD coefficients by the conventional solving method based on normal equations is difficult, this paper proposes solving the least-squares problem by solving the corresponding overdetermined linear system of equations through QR matrix decomposition. Compared with the existing methods for calculating adaptive FDFD coefficients based on numerical integration, CG optimization, and sequential initial value selection, the proposed method allows for a simplified computational process and considerably higher computational efficiency. Numerical wavefield simulation results show that the adaptive-coefficient FDFD method based on QR matrix decomposition can achieve the same accuracy as those based on numerical integration, CG optimization, and sequential initial value selection while requiring less computation time. |
doi_str_mv | 10.1007/s11770-023-1045-8 |
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Among the existing FDFD coefficients for seismic wavefield simulation, adaptive FDFD coefficients that vary with the number of wavelengths per grid can suppress numerical dispersion to the maximum extent. The current methods for calculating adaptive FDFD coefficients involve numerical integration, conjugate gradient (CG) optimization, sequential initial value selection, and smooth regularization, which are difficult to implement and inefficient in calculations. To simplify the calculation of adaptive FDFD coefficients and improve the corresponding computational efficiency, this paper proposes a new method for calculating adaptive FDFD coefficients. First, plane-wave solutions with different discrete propagation angles are substituted in the FDFD scheme, and the corresponding least-squares problem is constructed. As this problem is ill-conditioned and obtaining smooth adaptive FDFD coefficients by the conventional solving method based on normal equations is difficult, this paper proposes solving the least-squares problem by solving the corresponding overdetermined linear system of equations through QR matrix decomposition. Compared with the existing methods for calculating adaptive FDFD coefficients based on numerical integration, CG optimization, and sequential initial value selection, the proposed method allows for a simplified computational process and considerably higher computational efficiency. Numerical wavefield simulation results show that the adaptive-coefficient FDFD method based on QR matrix decomposition can achieve the same accuracy as those based on numerical integration, CG optimization, and sequential initial value selection while requiring less computation time.</description><identifier>ISSN: 1672-7975</identifier><identifier>EISSN: 1993-0658</identifier><identifier>DOI: 10.1007/s11770-023-1045-8</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Coefficients ; Computation ; Computational efficiency ; Computer applications ; Computing time ; Decomposition ; Dispersion ; Earth and Environmental Science ; Earth Sciences ; Finite difference method ; Frequency domain analysis ; Geophysics/Geodesy ; Geotechnical Engineering & Applied Earth Sciences ; Integration ; Least squares method ; Mathematical models ; Numerical integration ; Optimization ; Plane waves ; Regularization ; Seismic Modeling and Wave Propagation ; Simulation ; Wavelengths</subject><ispartof>Applied geophysics, 2023-09, Vol.20 (3), p.262-277</ispartof><rights>The Editorial Department of APPLIED GEOPHYSICS 2023</rights><rights>The Editorial Department of APPLIED GEOPHYSICS 2023.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-a10286a9f1ec86ab07b19e0b9dd9258e55e70f68ccf3204dc891e21bcf4e40903</citedby><cites>FETCH-LOGICAL-c316t-a10286a9f1ec86ab07b19e0b9dd9258e55e70f68ccf3204dc891e21bcf4e40903</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11770-023-1045-8$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11770-023-1045-8$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Xu, Wen-Hao</creatorcontrib><creatorcontrib>Ba, Jing</creatorcontrib><creatorcontrib>Carcione, José Maria</creatorcontrib><creatorcontrib>Yang, Zhi-Fang</creatorcontrib><creatorcontrib>Yan, Xin-Fei</creatorcontrib><title>A simplified calculation for adaptive coefficients of finite-difference frequency-domain method</title><title>Applied geophysics</title><addtitle>Appl. Geophys</addtitle><description>The finite-difference frequency domain (FDFD) method is widely applied for simulating seismic wavefields, and a key to achieving successful FDFD simulation is to construct FDFD coefficients that can effectively suppress numerical dispersion. Among the existing FDFD coefficients for seismic wavefield simulation, adaptive FDFD coefficients that vary with the number of wavelengths per grid can suppress numerical dispersion to the maximum extent. The current methods for calculating adaptive FDFD coefficients involve numerical integration, conjugate gradient (CG) optimization, sequential initial value selection, and smooth regularization, which are difficult to implement and inefficient in calculations. To simplify the calculation of adaptive FDFD coefficients and improve the corresponding computational efficiency, this paper proposes a new method for calculating adaptive FDFD coefficients. First, plane-wave solutions with different discrete propagation angles are substituted in the FDFD scheme, and the corresponding least-squares problem is constructed. As this problem is ill-conditioned and obtaining smooth adaptive FDFD coefficients by the conventional solving method based on normal equations is difficult, this paper proposes solving the least-squares problem by solving the corresponding overdetermined linear system of equations through QR matrix decomposition. Compared with the existing methods for calculating adaptive FDFD coefficients based on numerical integration, CG optimization, and sequential initial value selection, the proposed method allows for a simplified computational process and considerably higher computational efficiency. Numerical wavefield simulation results show that the adaptive-coefficient FDFD method based on QR matrix decomposition can achieve the same accuracy as those based on numerical integration, CG optimization, and sequential initial value selection while requiring less computation time.</description><subject>Coefficients</subject><subject>Computation</subject><subject>Computational efficiency</subject><subject>Computer applications</subject><subject>Computing time</subject><subject>Decomposition</subject><subject>Dispersion</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Finite difference method</subject><subject>Frequency domain analysis</subject><subject>Geophysics/Geodesy</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Integration</subject><subject>Least squares method</subject><subject>Mathematical models</subject><subject>Numerical integration</subject><subject>Optimization</subject><subject>Plane waves</subject><subject>Regularization</subject><subject>Seismic Modeling and Wave Propagation</subject><subject>Simulation</subject><subject>Wavelengths</subject><issn>1672-7975</issn><issn>1993-0658</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kE9LxDAUxIMouK5-AG8Bz9GXtE2b47L4Dxa86Dmk6YtmaZuadIX99kYqePI0c5iZ9_gRcs3hlgPUd4nzugYGomAcyoo1J2TFlSoYyKo5zV7WgtWqrs7JRUp7AFkIWa6I3tDkh6n3zmNHrentoTezDyN1IVLTmWn2X0htQOe89TjOiQZHnR_9jKzzzmHE0SJ1ET8P2R1ZFwbjRzrg_BG6S3LmTJ_w6lfX5O3h_nX7xHYvj8_bzY7ZgsuZGQ6ikUY5jjZrC3XLFUKruk6JqsGqwhqcbKx1hYCys43iKHhrXYklKCjW5GbZnWLIf6RZ78MhjvmkFqqpVAmSy5ziS8rGkFJEp6foBxOPmoP-4agXjjpz1D8cdZM7YumknB3fMf4t_1_6BtR5dsc</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Xu, Wen-Hao</creator><creator>Ba, Jing</creator><creator>Carcione, José Maria</creator><creator>Yang, Zhi-Fang</creator><creator>Yan, Xin-Fei</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope></search><sort><creationdate>20230901</creationdate><title>A simplified calculation for adaptive coefficients of finite-difference frequency-domain method</title><author>Xu, Wen-Hao ; Ba, Jing ; Carcione, José Maria ; Yang, Zhi-Fang ; Yan, Xin-Fei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-a10286a9f1ec86ab07b19e0b9dd9258e55e70f68ccf3204dc891e21bcf4e40903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Coefficients</topic><topic>Computation</topic><topic>Computational efficiency</topic><topic>Computer applications</topic><topic>Computing time</topic><topic>Decomposition</topic><topic>Dispersion</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Finite difference method</topic><topic>Frequency domain analysis</topic><topic>Geophysics/Geodesy</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Integration</topic><topic>Least squares method</topic><topic>Mathematical models</topic><topic>Numerical integration</topic><topic>Optimization</topic><topic>Plane waves</topic><topic>Regularization</topic><topic>Seismic Modeling and Wave Propagation</topic><topic>Simulation</topic><topic>Wavelengths</topic><toplevel>online_resources</toplevel><creatorcontrib>Xu, Wen-Hao</creatorcontrib><creatorcontrib>Ba, Jing</creatorcontrib><creatorcontrib>Carcione, José Maria</creatorcontrib><creatorcontrib>Yang, Zhi-Fang</creatorcontrib><creatorcontrib>Yan, Xin-Fei</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Applied geophysics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Wen-Hao</au><au>Ba, Jing</au><au>Carcione, José Maria</au><au>Yang, Zhi-Fang</au><au>Yan, Xin-Fei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A simplified calculation for adaptive coefficients of finite-difference frequency-domain method</atitle><jtitle>Applied geophysics</jtitle><stitle>Appl. Geophys</stitle><date>2023-09-01</date><risdate>2023</risdate><volume>20</volume><issue>3</issue><spage>262</spage><epage>277</epage><pages>262-277</pages><issn>1672-7975</issn><eissn>1993-0658</eissn><abstract>The finite-difference frequency domain (FDFD) method is widely applied for simulating seismic wavefields, and a key to achieving successful FDFD simulation is to construct FDFD coefficients that can effectively suppress numerical dispersion. Among the existing FDFD coefficients for seismic wavefield simulation, adaptive FDFD coefficients that vary with the number of wavelengths per grid can suppress numerical dispersion to the maximum extent. The current methods for calculating adaptive FDFD coefficients involve numerical integration, conjugate gradient (CG) optimization, sequential initial value selection, and smooth regularization, which are difficult to implement and inefficient in calculations. To simplify the calculation of adaptive FDFD coefficients and improve the corresponding computational efficiency, this paper proposes a new method for calculating adaptive FDFD coefficients. First, plane-wave solutions with different discrete propagation angles are substituted in the FDFD scheme, and the corresponding least-squares problem is constructed. As this problem is ill-conditioned and obtaining smooth adaptive FDFD coefficients by the conventional solving method based on normal equations is difficult, this paper proposes solving the least-squares problem by solving the corresponding overdetermined linear system of equations through QR matrix decomposition. Compared with the existing methods for calculating adaptive FDFD coefficients based on numerical integration, CG optimization, and sequential initial value selection, the proposed method allows for a simplified computational process and considerably higher computational efficiency. Numerical wavefield simulation results show that the adaptive-coefficient FDFD method based on QR matrix decomposition can achieve the same accuracy as those based on numerical integration, CG optimization, and sequential initial value selection while requiring less computation time.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s11770-023-1045-8</doi><tpages>16</tpages></addata></record> |
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subjects | Coefficients Computation Computational efficiency Computer applications Computing time Decomposition Dispersion Earth and Environmental Science Earth Sciences Finite difference method Frequency domain analysis Geophysics/Geodesy Geotechnical Engineering & Applied Earth Sciences Integration Least squares method Mathematical models Numerical integration Optimization Plane waves Regularization Seismic Modeling and Wave Propagation Simulation Wavelengths |
title | A simplified calculation for adaptive coefficients of finite-difference frequency-domain method |
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