Correlation-based reflection full-waveform inversion.

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Title: Correlation-based reflection full-waveform inversion.
Authors: Benxin Chi1 10chibcnxin@tongji.edu.cn, Liangguo Dong1 dlg@tongji.edu.cn, Yuzhu Liu1 liuyuzhu@tongji.edu.cn
Source: Geophysics. Jul/Aug2015, Vol. 80 Issue 4, pR189-R202. 14p.
Subjects: Wave analysis, Scattering potentials, Wavenumber, Nonlinear theories, Fluid dynamics
Abstract: Because modeling for full-waveform inversion (FWI) cannot produce reflections unless the velocity model has the scattering potential (high wavenumbers), using a migration/demigration process to generate modeling data, which is a key step in what is now known as reflection FWI (RFWI), is a credible alternative to tackle the reflection nonlinearity associated with FWI. However, because RFWI depends on a conventional data residual or zero-lag correlation objective function, high nonlinearity can still exist when the true amplitude migration is not used, as well as at far offsets due to cycle skipping. To avoid the cycle skipping and the need for a true amplitude migration, we have developed a correlation-based reflection full-waveform inversion method to update the low-wavenumber components of the velocity model. The success of this method relies on a sensitivity kernel decomposition and a correlation-based objective function. The sensitivity kernel decomposition makes it possible to separate out the contributions of different subkernels and to smear the reflected wave residuals along the "rabbit-ear" wavepath to obtain middle and deep background model estimates. The correlation-based objective function measures differences in kinematic information and behaves in a more linear way than the traditional waveform residual misfit. Moreover, our approach is less sensitive to the frequency content and amplitude information of the seismic data, enabling reliable background velocity estimates to be obtained without the need for low frequencies and full-physics modeling. Because the kinematic features of reflected waves are described correctly, the inversion result of the proposed method can be used as a migration model or an initial model for conventional FWI to achieve a correct high-wavenumber model update. [ABSTRACT FROM AUTHOR]
Copyright of Geophysics is the property of Society of Exploration Geophysicists and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Correlation-based reflection full-waveform inversion.
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  Data: <searchLink fieldCode="AR" term="%22Benxin+Chi%22">Benxin Chi</searchLink><relatesTo>1</relatesTo><i> 10chibcnxin@tongji.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Liangguo+Dong%22">Liangguo Dong</searchLink><relatesTo>1</relatesTo><i> dlg@tongji.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Yuzhu+Liu%22">Yuzhu Liu</searchLink><relatesTo>1</relatesTo><i> liuyuzhu@tongji.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Geophysics%22">Geophysics</searchLink>. Jul/Aug2015, Vol. 80 Issue 4, pR189-R202. 14p.
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%22Wave+analysis%22">Wave analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Scattering+potentials%22">Scattering potentials</searchLink><br /><searchLink fieldCode="DE" term="%22Wavenumber%22">Wavenumber</searchLink><br /><searchLink fieldCode="DE" term="%22Nonlinear+theories%22">Nonlinear theories</searchLink><br /><searchLink fieldCode="DE" term="%22Fluid+dynamics%22">Fluid dynamics</searchLink>
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  Label: Abstract
  Group: Ab
  Data: Because modeling for full-waveform inversion (FWI) cannot produce reflections unless the velocity model has the scattering potential (high wavenumbers), using a migration/demigration process to generate modeling data, which is a key step in what is now known as reflection FWI (RFWI), is a credible alternative to tackle the reflection nonlinearity associated with FWI. However, because RFWI depends on a conventional data residual or zero-lag correlation objective function, high nonlinearity can still exist when the true amplitude migration is not used, as well as at far offsets due to cycle skipping. To avoid the cycle skipping and the need for a true amplitude migration, we have developed a correlation-based reflection full-waveform inversion method to update the low-wavenumber components of the velocity model. The success of this method relies on a sensitivity kernel decomposition and a correlation-based objective function. The sensitivity kernel decomposition makes it possible to separate out the contributions of different subkernels and to smear the reflected wave residuals along the "rabbit-ear" wavepath to obtain middle and deep background model estimates. The correlation-based objective function measures differences in kinematic information and behaves in a more linear way than the traditional waveform residual misfit. Moreover, our approach is less sensitive to the frequency content and amplitude information of the seismic data, enabling reliable background velocity estimates to be obtained without the need for low frequencies and full-physics modeling. Because the kinematic features of reflected waves are described correctly, the inversion result of the proposed method can be used as a migration model or an initial model for conventional FWI to achieve a correct high-wavenumber model update. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Geophysics is the property of Society of Exploration Geophysicists and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1190/GEO2014-0345.1
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 14
        StartPage: R189
    Subjects:
      – SubjectFull: Wave analysis
        Type: general
      – SubjectFull: Scattering potentials
        Type: general
      – SubjectFull: Wavenumber
        Type: general
      – SubjectFull: Nonlinear theories
        Type: general
      – SubjectFull: Fluid dynamics
        Type: general
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      – TitleFull: Correlation-based reflection full-waveform inversion.
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            NameFull: Benxin Chi
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            NameFull: Liangguo Dong
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          Name:
            NameFull: Yuzhu Liu
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            – D: 01
              M: 07
              Text: Jul/Aug2015
              Type: published
              Y: 2015
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              Value: 80
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            – TitleFull: Geophysics
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