Reflection full waveform inversion

Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the applicatio...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yao, Gang [verfasserIn] Wu, Di [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Full-waveform inversion Reflection full-waveform inversion Least-squares reverse-time migration Tomographic gradient Reflectivity gradient Deconvolution imaging condition

Übergeordnetes Werk:	Enthalten in: Science in China - Heidelberg : Springer, 1997, 60(2017), 10 vom: 18. Sept., Seite 1783-1794
Übergeordnetes Werk:	volume:60 ; year:2017 ; number:10 ; day:18 ; month:09 ; pages:1783-1794

Links:	Volltext

DOI / URN:	10.1007/s11430-016-9091-9

Katalog-ID:	SPR019248237

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520			\|a Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.
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allfields	10.1007/s11430-016-9091-9 doi (DE-627)SPR019248237 (SPR)s11430-016-9091-9-e DE-627 ger DE-627 rakwb eng 550 ASE 38.00 bkl Yao, Gang verfasserin aut Reflection full waveform inversion 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI. Full-waveform inversion (dpeaa)DE-He213 Reflection full-waveform inversion (dpeaa)DE-He213 Least-squares reverse-time migration (dpeaa)DE-He213 Tomographic gradient (dpeaa)DE-He213 Reflectivity gradient (dpeaa)DE-He213 Deconvolution imaging condition (dpeaa)DE-He213 Wu, Di verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 60(2017), 10 vom: 18. Sept., Seite 1783-1794 (DE-627)385614748 (DE-600)2142896-7 1862-2801 nnns volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794 https://dx.doi.org/10.1007/s11430-016-9091-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_65 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_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 38.00 ASE AR 60 2017 10 18 09 1783-1794
spelling	10.1007/s11430-016-9091-9 doi (DE-627)SPR019248237 (SPR)s11430-016-9091-9-e DE-627 ger DE-627 rakwb eng 550 ASE 38.00 bkl Yao, Gang verfasserin aut Reflection full waveform inversion 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI. Full-waveform inversion (dpeaa)DE-He213 Reflection full-waveform inversion (dpeaa)DE-He213 Least-squares reverse-time migration (dpeaa)DE-He213 Tomographic gradient (dpeaa)DE-He213 Reflectivity gradient (dpeaa)DE-He213 Deconvolution imaging condition (dpeaa)DE-He213 Wu, Di verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 60(2017), 10 vom: 18. Sept., Seite 1783-1794 (DE-627)385614748 (DE-600)2142896-7 1862-2801 nnns volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794 https://dx.doi.org/10.1007/s11430-016-9091-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_65 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_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 38.00 ASE AR 60 2017 10 18 09 1783-1794
allfields_unstemmed	10.1007/s11430-016-9091-9 doi (DE-627)SPR019248237 (SPR)s11430-016-9091-9-e DE-627 ger DE-627 rakwb eng 550 ASE 38.00 bkl Yao, Gang verfasserin aut Reflection full waveform inversion 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI. Full-waveform inversion (dpeaa)DE-He213 Reflection full-waveform inversion (dpeaa)DE-He213 Least-squares reverse-time migration (dpeaa)DE-He213 Tomographic gradient (dpeaa)DE-He213 Reflectivity gradient (dpeaa)DE-He213 Deconvolution imaging condition (dpeaa)DE-He213 Wu, Di verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 60(2017), 10 vom: 18. Sept., Seite 1783-1794 (DE-627)385614748 (DE-600)2142896-7 1862-2801 nnns volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794 https://dx.doi.org/10.1007/s11430-016-9091-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_65 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_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 38.00 ASE AR 60 2017 10 18 09 1783-1794
allfieldsGer	10.1007/s11430-016-9091-9 doi (DE-627)SPR019248237 (SPR)s11430-016-9091-9-e DE-627 ger DE-627 rakwb eng 550 ASE 38.00 bkl Yao, Gang verfasserin aut Reflection full waveform inversion 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI. Full-waveform inversion (dpeaa)DE-He213 Reflection full-waveform inversion (dpeaa)DE-He213 Least-squares reverse-time migration (dpeaa)DE-He213 Tomographic gradient (dpeaa)DE-He213 Reflectivity gradient (dpeaa)DE-He213 Deconvolution imaging condition (dpeaa)DE-He213 Wu, Di verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 60(2017), 10 vom: 18. Sept., Seite 1783-1794 (DE-627)385614748 (DE-600)2142896-7 1862-2801 nnns volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794 https://dx.doi.org/10.1007/s11430-016-9091-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_65 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_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 38.00 ASE AR 60 2017 10 18 09 1783-1794
allfieldsSound	10.1007/s11430-016-9091-9 doi (DE-627)SPR019248237 (SPR)s11430-016-9091-9-e DE-627 ger DE-627 rakwb eng 550 ASE 38.00 bkl Yao, Gang verfasserin aut Reflection full waveform inversion 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI. Full-waveform inversion (dpeaa)DE-He213 Reflection full-waveform inversion (dpeaa)DE-He213 Least-squares reverse-time migration (dpeaa)DE-He213 Tomographic gradient (dpeaa)DE-He213 Reflectivity gradient (dpeaa)DE-He213 Deconvolution imaging condition (dpeaa)DE-He213 Wu, Di verfasserin aut Enthalten in Science in China Heidelberg : Springer, 1997 60(2017), 10 vom: 18. Sept., Seite 1783-1794 (DE-627)385614748 (DE-600)2142896-7 1862-2801 nnns volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794 https://dx.doi.org/10.1007/s11430-016-9091-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-GGO SSG-OPC-ASE 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_65 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_152 GBV_ILN_161 GBV_ILN_171 GBV_ILN_187 GBV_ILN_224 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 38.00 ASE AR 60 2017 10 18 09 1783-1794
language	English
source	Enthalten in Science in China 60(2017), 10 vom: 18. Sept., Seite 1783-1794 volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794
sourceStr	Enthalten in Science in China 60(2017), 10 vom: 18. Sept., Seite 1783-1794 volume:60 year:2017 number:10 day:18 month:09 pages:1783-1794
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Full-waveform inversion Reflection full-waveform inversion Least-squares reverse-time migration Tomographic gradient Reflectivity gradient Deconvolution imaging condition
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container_title	Science in China
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author	Yao, Gang
spellingShingle	Yao, Gang ddc 550 bkl 38.00 misc Full-waveform inversion misc Reflection full-waveform inversion misc Least-squares reverse-time migration misc Tomographic gradient misc Reflectivity gradient misc Deconvolution imaging condition Reflection full waveform inversion
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topic_title	550 ASE 38.00 bkl Reflection full waveform inversion Full-waveform inversion (dpeaa)DE-He213 Reflection full-waveform inversion (dpeaa)DE-He213 Least-squares reverse-time migration (dpeaa)DE-He213 Tomographic gradient (dpeaa)DE-He213 Reflectivity gradient (dpeaa)DE-He213 Deconvolution imaging condition (dpeaa)DE-He213
topic	ddc 550 bkl 38.00 misc Full-waveform inversion misc Reflection full-waveform inversion misc Least-squares reverse-time migration misc Tomographic gradient misc Reflectivity gradient misc Deconvolution imaging condition
topic_unstemmed	ddc 550 bkl 38.00 misc Full-waveform inversion misc Reflection full-waveform inversion misc Least-squares reverse-time migration misc Tomographic gradient misc Reflectivity gradient misc Deconvolution imaging condition
topic_browse	ddc 550 bkl 38.00 misc Full-waveform inversion misc Reflection full-waveform inversion misc Least-squares reverse-time migration misc Tomographic gradient misc Reflectivity gradient misc Deconvolution imaging condition
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title	Reflection full waveform inversion
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title_full	Reflection full waveform inversion
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title_sort	reflection full waveform inversion
title_auth	Reflection full waveform inversion
abstract	Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.
abstractGer	Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.
abstract_unstemmed	Abstract Because of the combination of optimization algorithms and full wave equations, full-waveform inversion (FWI) has become the frontier of the study of seismic exploration and is gradually becoming one of the essential tools for obtaining the Earth interior information. However, the application of conventional FWI to pure reflection data in the absence of a highly accurate starting velocity model is difficult. Compared to other types of seismic waves, reflections carry the information of the deep part of the subsurface. Reflection FWI, therefore, is able to improve the accuracy of imaging the Earth interior further. Here, we demonstrate a means of achieving this successfully by interleaving least-squares RTM with a version of reflection FWI in which the tomographic gradient that is required to update the background macro-model is separated from the reflectivity gradient using the Born approximation during forward modeling. This provides a good update to the macro-model. This approach is then followed by conventional FWI to obtain a final high-fidelity high-resolution result from a poor starting model using only reflection data. Further analysis reveals the high-resolution result is achieved due to a deconvolution imaging condition implicitly used by FWI.
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title_short	Reflection full waveform inversion
url	https://dx.doi.org/10.1007/s11430-016-9091-9
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doi_str	10.1007/s11430-016-9091-9
up_date	2024-07-04T00:48:36.406Z
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