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    Joint Minimization of the Mean and Information Entropy of the Matching Filter Distribution for a Robust Misfit Function in Full-Waveform Inversion

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    Type
    Article
    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
    2020-02-11
    Online Publication Date
    2020-02-11
    Print Publication Date
    2020-07
    Submitted Date
    2019-07-06
    Permanent link to this record
    http://hdl.handle.net/10754/661499
    
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    Abstract
    A full-waveform inversion (FWI) is a highly nonlinear inversion methodology. FWI tends to converge to a local minimum rather than a global one. We refer to this phenomenon as ``cycle skipping'' in FWI. A cost-effective solution for resolving this issue is to design a more convex misfit function for the optimization problem. A global comparison based on using a matching filter (MF) admits more robust misfit functions. In this case, we would compute an MF first by deconvolving the predicted data from the measured ones. When the velocity model is accurate, the predicted data resemble the measured ones, and the resulting MF would be an approximated Dirac delta function. If the velocity produces data that are different from the observed ones, a misfit function can be formulated by penalizing the energy away from the zero-lag time (the center). Here, we develop a general mechanism for an evolution of the MF to our objective in FWI. Specifically from the statistics point of view, rather than using a penalty, we propose a novel misfit by minimization of the mean and information entropy of the MF distribution. We show that the resulting misfit function can mitigate the ``cycle skipping'' as well as reduce the mean and variance of the resulting MF distribution. We use a modified Marmousi example to demonstrate the features of the proposed misfit. We also evaluate the robustness of the proposed method using inaccurate (rotation in phase) source wavelets and measured data with different levels of Gaussian random noise.
    Citation
    Sun, B., & Alkhalifah, T. A. (2020). Joint Minimization of the Mean and Information Entropy of the Matching Filter Distribution for a Robust Misfit Function in Full-Waveform Inversion. IEEE Transactions on Geoscience and Remote Sensing, 58(7), 4704–4720. doi:10.1109/tgrs.2020.2966115
    Sponsors
    The work was supported financially by the King Abdullah University of Science and Technology (KAUST) in general.
    The authors would like to thank the members of SWAG for useful discussions.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Geoscience and Remote Sensing
    DOI
    10.1109/TGRS.2020.2966115
    Additional Links
    https://ieeexplore.ieee.org/document/8994166/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8994166
    ae974a485f413a2113503eed53cd6c53
    10.1109/TGRS.2020.2966115
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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