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Reverse time migration by Krylov subspace reduced order modeling.

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Title: Reverse time migration by Krylov subspace reduced order modeling.
Authors: Basir, Hadi Mahdavi1, Javaherian, Abdolrahim1,2 javaheri@ut.ac.ir, Shomali, Zaher Hossein2,3, Firouz-Abadi, Roohollah Dehghani4, Gholamy, Shaban Ali5
Source: Journal of Applied Geophysics. Apr2018, Vol. 151, p298-308. 11p.
Subjects: Imaging systems in seismology, Krylov subspace, Computer simulation, Parallel computers, Algorithms, Depth migration (Geophysics)
Abstract: Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Applied Geophysics is the property of Elsevier B.V. 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.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 128718398
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Applied+Geophysics%22">Journal of Applied Geophysics</searchLink>. Apr2018, Vol. 151, p298-308. 11p.
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  Data: Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Applied Geophysics is the property of Elsevier B.V. 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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      – Type: doi
        Value: 10.1016/j.jappgeo.2018.02.010
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 298
    Subjects:
      – SubjectFull: Imaging systems in seismology
        Type: general
      – SubjectFull: Krylov subspace
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Parallel computers
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Depth migration (Geophysics)
        Type: general
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      – TitleFull: Reverse time migration by Krylov subspace reduced order modeling.
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            NameFull: Basir, Hadi Mahdavi
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            NameFull: Javaherian, Abdolrahim
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            NameFull: Shomali, Zaher Hossein
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            NameFull: Firouz-Abadi, Roohollah Dehghani
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            NameFull: Gholamy, Shaban Ali
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              Text: Apr2018
              Type: published
              Y: 2018
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