The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion
Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jidong Yang [verfasserIn] Jie Xu [verfasserIn] Jianping Huang [verfasserIn] Youcai Yu [verfasserIn] Jiaxing Sun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: Frontiers in Earth Science - Frontiers Media S.A., 2014, 10(2022) |
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| Übergeordnetes Werk: |
volume:10 ; year:2022 |
| Links: |
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| DOI / URN: |
10.3389/feart.2022.961750 |
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| Katalog-ID: |
DOAJ022516131 |
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| 520 | |a Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. | ||
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10.3389/feart.2022.961750 doi (DE-627)DOAJ022516131 (DE-599)DOAJ2d5ab51ea182462bbbb47cb02cd30920 DE-627 ger DE-627 rakwb eng Jidong Yang verfasserin aut The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. full waveform inversion sensitivity kernels scattering-angle filtering hybrid gradient migration component tomography component Science Q Jie Xu verfasserin aut Jianping Huang verfasserin aut Youcai Yu verfasserin aut Jiaxing Sun verfasserin aut In Frontiers in Earth Science Frontiers Media S.A., 2014 10(2022) (DE-627)771399731 (DE-600)2741235-0 22966463 nnns volume:10 year:2022 https://doi.org/10.3389/feart.2022.961750 kostenfrei https://doaj.org/article/2d5ab51ea182462bbbb47cb02cd30920 kostenfrei https://www.frontiersin.org/articles/10.3389/feart.2022.961750/full kostenfrei https://doaj.org/toc/2296-6463 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 |
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10.3389/feart.2022.961750 doi (DE-627)DOAJ022516131 (DE-599)DOAJ2d5ab51ea182462bbbb47cb02cd30920 DE-627 ger DE-627 rakwb eng Jidong Yang verfasserin aut The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. full waveform inversion sensitivity kernels scattering-angle filtering hybrid gradient migration component tomography component Science Q Jie Xu verfasserin aut Jianping Huang verfasserin aut Youcai Yu verfasserin aut Jiaxing Sun verfasserin aut In Frontiers in Earth Science Frontiers Media S.A., 2014 10(2022) (DE-627)771399731 (DE-600)2741235-0 22966463 nnns volume:10 year:2022 https://doi.org/10.3389/feart.2022.961750 kostenfrei https://doaj.org/article/2d5ab51ea182462bbbb47cb02cd30920 kostenfrei https://www.frontiersin.org/articles/10.3389/feart.2022.961750/full kostenfrei https://doaj.org/toc/2296-6463 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 |
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10.3389/feart.2022.961750 doi (DE-627)DOAJ022516131 (DE-599)DOAJ2d5ab51ea182462bbbb47cb02cd30920 DE-627 ger DE-627 rakwb eng Jidong Yang verfasserin aut The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. full waveform inversion sensitivity kernels scattering-angle filtering hybrid gradient migration component tomography component Science Q Jie Xu verfasserin aut Jianping Huang verfasserin aut Youcai Yu verfasserin aut Jiaxing Sun verfasserin aut In Frontiers in Earth Science Frontiers Media S.A., 2014 10(2022) (DE-627)771399731 (DE-600)2741235-0 22966463 nnns volume:10 year:2022 https://doi.org/10.3389/feart.2022.961750 kostenfrei https://doaj.org/article/2d5ab51ea182462bbbb47cb02cd30920 kostenfrei https://www.frontiersin.org/articles/10.3389/feart.2022.961750/full kostenfrei https://doaj.org/toc/2296-6463 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 |
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10.3389/feart.2022.961750 doi (DE-627)DOAJ022516131 (DE-599)DOAJ2d5ab51ea182462bbbb47cb02cd30920 DE-627 ger DE-627 rakwb eng Jidong Yang verfasserin aut The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. full waveform inversion sensitivity kernels scattering-angle filtering hybrid gradient migration component tomography component Science Q Jie Xu verfasserin aut Jianping Huang verfasserin aut Youcai Yu verfasserin aut Jiaxing Sun verfasserin aut In Frontiers in Earth Science Frontiers Media S.A., 2014 10(2022) (DE-627)771399731 (DE-600)2741235-0 22966463 nnns volume:10 year:2022 https://doi.org/10.3389/feart.2022.961750 kostenfrei https://doaj.org/article/2d5ab51ea182462bbbb47cb02cd30920 kostenfrei https://www.frontiersin.org/articles/10.3389/feart.2022.961750/full kostenfrei https://doaj.org/toc/2296-6463 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 |
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10.3389/feart.2022.961750 doi (DE-627)DOAJ022516131 (DE-599)DOAJ2d5ab51ea182462bbbb47cb02cd30920 DE-627 ger DE-627 rakwb eng Jidong Yang verfasserin aut The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. full waveform inversion sensitivity kernels scattering-angle filtering hybrid gradient migration component tomography component Science Q Jie Xu verfasserin aut Jianping Huang verfasserin aut Youcai Yu verfasserin aut Jiaxing Sun verfasserin aut In Frontiers in Earth Science Frontiers Media S.A., 2014 10(2022) (DE-627)771399731 (DE-600)2741235-0 22966463 nnns volume:10 year:2022 https://doi.org/10.3389/feart.2022.961750 kostenfrei https://doaj.org/article/2d5ab51ea182462bbbb47cb02cd30920 kostenfrei https://www.frontiersin.org/articles/10.3389/feart.2022.961750/full kostenfrei https://doaj.org/toc/2296-6463 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 |
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Jidong Yang |
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The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion |
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connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion |
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The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion |
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Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. |
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Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. |
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Multi-scale strategies such as starting from the low-frequency and early-arrival part of recorded data are commonly used in full waveform inversion (FWI) to maneuver complex nonlinearity. An alternative way is to apply appropriate filtering and conditioning to the misfit gradient in the model domain. In acoustic constant-density media, we prove that velocity and impedance sensitivity kernels are equivalent to applying a high-pass and a low-pass scattering-angle filter to a conventional single-parameter velocity (CSV) kernel. The high-pass scattering-angle filter allows the velocity kernel to include low-wavenumber updates (tomography component). In contrast, the low-pass scattering-angle filter helps the impedance kernel to yield high-wavenumber updates (migration component). The velocity model can be updated using a hybrid gradient of two components combined with appropriate weights. This FWI scheme is able to overcome the potential nonlinearity and partially mitigate the cycle-skipping problem. Numerical examples for the SEG/EAGE overthrust model and the Marmousi model demonstrate that the hybrid gradient facilitates FWI to converge faster to the true model even in cases when conventional CSV-based FWI fails. |
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The connection of velocity and impedance sensitivity kernels with scattering-angle filtering and its application in full waveform inversion |
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