A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods

Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by...
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Autor*in:	Zhao, DongDong [verfasserIn] Zhang, QianJiang Wang, XuLong Mo, TaiPing Chen, ZhenCheng

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	CSEM,3D modeling standard FFT Gauss-FFT

Anmerkung:	© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Übergeordnetes Werk:	Enthalten in: Pure and applied geophysics - Basel : Birkhäuser, 1939, 181(2023), 2 vom: 20. Dez., Seite 451-466
Übergeordnetes Werk:	volume:181 ; year:2023 ; number:2 ; day:20 ; month:12 ; pages:451-466

Links:	Volltext

DOI / URN:	10.1007/s00024-023-03373-0

Katalog-ID:	SPR054957346

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520			\|a Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems.
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allfields	10.1007/s00024-023-03373-0 doi (DE-627)SPR054957346 (SPR)s00024-023-03373-0-e DE-627 ger DE-627 rakwb eng Zhao, DongDong verfasserin aut A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. CSEM,3D (dpeaa)DE-He213 modeling (dpeaa)DE-He213 standard FFT (dpeaa)DE-He213 Gauss-FFT (dpeaa)DE-He213 Zhang, QianJiang aut Wang, XuLong aut Mo, TaiPing aut Chen, ZhenCheng aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 181(2023), 2 vom: 20. Dez., Seite 451-466 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:181 year:2023 number:2 day:20 month:12 pages:451-466 https://dx.doi.org/10.1007/s00024-023-03373-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 181 2023 2 20 12 451-466
spelling	10.1007/s00024-023-03373-0 doi (DE-627)SPR054957346 (SPR)s00024-023-03373-0-e DE-627 ger DE-627 rakwb eng Zhao, DongDong verfasserin aut A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. CSEM,3D (dpeaa)DE-He213 modeling (dpeaa)DE-He213 standard FFT (dpeaa)DE-He213 Gauss-FFT (dpeaa)DE-He213 Zhang, QianJiang aut Wang, XuLong aut Mo, TaiPing aut Chen, ZhenCheng aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 181(2023), 2 vom: 20. Dez., Seite 451-466 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:181 year:2023 number:2 day:20 month:12 pages:451-466 https://dx.doi.org/10.1007/s00024-023-03373-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 181 2023 2 20 12 451-466
allfields_unstemmed	10.1007/s00024-023-03373-0 doi (DE-627)SPR054957346 (SPR)s00024-023-03373-0-e DE-627 ger DE-627 rakwb eng Zhao, DongDong verfasserin aut A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. CSEM,3D (dpeaa)DE-He213 modeling (dpeaa)DE-He213 standard FFT (dpeaa)DE-He213 Gauss-FFT (dpeaa)DE-He213 Zhang, QianJiang aut Wang, XuLong aut Mo, TaiPing aut Chen, ZhenCheng aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 181(2023), 2 vom: 20. Dez., Seite 451-466 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:181 year:2023 number:2 day:20 month:12 pages:451-466 https://dx.doi.org/10.1007/s00024-023-03373-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 181 2023 2 20 12 451-466
allfieldsGer	10.1007/s00024-023-03373-0 doi (DE-627)SPR054957346 (SPR)s00024-023-03373-0-e DE-627 ger DE-627 rakwb eng Zhao, DongDong verfasserin aut A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. CSEM,3D (dpeaa)DE-He213 modeling (dpeaa)DE-He213 standard FFT (dpeaa)DE-He213 Gauss-FFT (dpeaa)DE-He213 Zhang, QianJiang aut Wang, XuLong aut Mo, TaiPing aut Chen, ZhenCheng aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 181(2023), 2 vom: 20. Dez., Seite 451-466 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:181 year:2023 number:2 day:20 month:12 pages:451-466 https://dx.doi.org/10.1007/s00024-023-03373-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 181 2023 2 20 12 451-466
allfieldsSound	10.1007/s00024-023-03373-0 doi (DE-627)SPR054957346 (SPR)s00024-023-03373-0-e DE-627 ger DE-627 rakwb eng Zhao, DongDong verfasserin aut A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. CSEM,3D (dpeaa)DE-He213 modeling (dpeaa)DE-He213 standard FFT (dpeaa)DE-He213 Gauss-FFT (dpeaa)DE-He213 Zhang, QianJiang aut Wang, XuLong aut Mo, TaiPing aut Chen, ZhenCheng aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 181(2023), 2 vom: 20. Dez., Seite 451-466 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:181 year:2023 number:2 day:20 month:12 pages:451-466 https://dx.doi.org/10.1007/s00024-023-03373-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 181 2023 2 20 12 451-466
language	English
source	Enthalten in Pure and applied geophysics 181(2023), 2 vom: 20. Dez., Seite 451-466 volume:181 year:2023 number:2 day:20 month:12 pages:451-466
sourceStr	Enthalten in Pure and applied geophysics 181(2023), 2 vom: 20. Dez., Seite 451-466 volume:181 year:2023 number:2 day:20 month:12 pages:451-466
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topic_facet	CSEM,3D modeling standard FFT Gauss-FFT
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container_title	Pure and applied geophysics
authorswithroles_txt_mv	Zhao, DongDong @@aut@@ Zhang, QianJiang @@aut@@ Wang, XuLong @@aut@@ Mo, TaiPing @@aut@@ Chen, ZhenCheng @@aut@@
publishDateDaySort_date	2023-12-20T00:00:00Z
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id	SPR054957346
language_de	englisch
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author	Zhao, DongDong
spellingShingle	Zhao, DongDong misc CSEM,3D misc modeling misc standard FFT misc Gauss-FFT A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods
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topic_title	A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods CSEM,3D (dpeaa)DE-He213 modeling (dpeaa)DE-He213 standard FFT (dpeaa)DE-He213 Gauss-FFT (dpeaa)DE-He213
topic	misc CSEM,3D misc modeling misc standard FFT misc Gauss-FFT
topic_unstemmed	misc CSEM,3D misc modeling misc standard FFT misc Gauss-FFT
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title	A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods
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title_full	A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods
author_sort	Zhao, DongDong
journal	Pure and applied geophysics
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author_browse	Zhao, DongDong Zhang, QianJiang Wang, XuLong Mo, TaiPing Chen, ZhenCheng
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format_se	Elektronische Aufsätze
author-letter	Zhao, DongDong
doi_str_mv	10.1007/s00024-023-03373-0
title_sort	fast fourier finite element approach for 3d csem modeling using different fourier transform methods
title_auth	A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods
abstract	Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstractGer	Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
abstract_unstemmed	Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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title_short	A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods
url	https://dx.doi.org/10.1007/s00024-023-03373-0
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author2	Zhang, QianJiang Wang, XuLong Mo, TaiPing Chen, ZhenCheng
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up_date	2024-07-04T03:38:54.733Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR054957346</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20240301070824.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">240301s2023 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00024-023-03373-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR054957346</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00024-023-03373-0-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Zhao, DongDong</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A Fast Fourier Finite Element Approach for 3D CSEM Modeling Using Different Fourier Transform Methods</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2023</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract A novel Fourier finite element algorithm for 3D controlled-source electromagnetic (CSEM) problems using different 2D Fourier transform methods is presented. As an important and effective tool, the 2D Fourier transform method simplifies the 3D CSEM problem into multiple 1D problems solved by 1D finite element method, which can be used to significantly accelerate the 3D frequency-domain electromagnetic (EM) forward modeling algorithms. For this proposed Fourier finite element method, two different transformation techniques, including a standard FFT algorithm with different grid expansion coefficient, and a Gauss-FFT algorithm with different Gaussian quadrature nodes, are investigated and compared in terms of balancing modeling accuracy and efficiency. All the different Fourier transform algorithms are numerically checked by integral equation (IE) reference solutions. The comparison results of numerical tests show that the present 3D CSEM modeling method with standard FFT or Gauss-FFT not only can guarantee the accuracy, but can also reduce the computing cost for any EM problem in general. Additionally, the standard FFT algorithm has high simulation efficiency and relatively low accuracy, while the Gauss-FFT algorithm has high simulation accuracy and relatively low efficiency. Because of its faster numerical solution, we infer that the standard FFT with grid expansion is more applicable for solving large-scale CSEM forward problems.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">CSEM,3D</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modeling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">standard FFT</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Gauss-FFT</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, QianJiang</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wang, XuLong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Mo, TaiPing</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, ZhenCheng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Pure and applied geophysics</subfield><subfield code="d">Basel : Birkhäuser, 1939</subfield><subfield code="g">181(2023), 2 vom: 20. 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