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    The application of an optimal transport to a preconditioned data matching function for robust waveform inversion

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    Type
    Conference Paper
    Authors
    Sun, Bingbing
    Alkhalifah, Tariq Ali cc
    KAUST Department
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Seismic Wave Analysis Group
    Date
    2018-08-27
    Online Publication Date
    2018-08-27
    Print Publication Date
    2018-08-27
    Permanent link to this record
    http://hdl.handle.net/10754/631152
    
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    Abstract
    Full Waveform Inversion updates the subsurface model iteratively by minimizing a misfit function, which measures the difference between observed and predicted data. The conventional l norm misfit function is widely used as it provides a simple, sample by sample, high resolution misfit function. However it is susceptible to local minima if the low wavenum-ber components of the initial model are not accurate. A deconvolution of the predicted and observed data offers an extend space comparison, which is more global. The matching filter calculated from the deconvolution has energy focussed at zero lag, like a Dirac Delta function, when the predicted data matches the observed ones. We use the Wasserstein distance to measure the difference between the matching filter and a Dirac Delta function. Unlike data, the matching filter can be easily transformed to a distribution satisfying the requirement of optimal transport theory. Compared with the conventional normalized penalty applied to non-zero lag energy in the matching filter, the new misfit function is a metric and has solid mathematical foundation based on optimal transport theory. Both synthetic and real data examples verified the effectiveness of the proposed misfit function.
    Citation
    Sun B, Alkhalifah T (2018) The application of an optimal transport to a preconditioned data matching function for robust waveform inversion. SEG Technical Program Expanded Abstracts 2018. Available: http://dx.doi.org/10.1190/segam2018-2995285.1.
    Sponsors
    We thank KAUST for its support and the Shaheen super computing laboratory for the computational recourses . We acknowledge CGG for providing the real data.
    Publisher
    Society of Exploration Geophysicists
    Journal
    SEG Technical Program Expanded Abstracts 2018
    Conference/Event name
    88th Society of Exploration Geophysicists International Exposition and Annual Meeting, SEG 2018
    DOI
    10.1190/segam2018-2995285.1
    Additional Links
    https://library.seg.org/doi/10.1190/segam2018-2995285.1
    ae974a485f413a2113503eed53cd6c53
    10.1190/segam2018-2995285.1
    Scopus Count
    Collections
    Conference Papers; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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