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    3D wave-equation dispersion inversion of Rayleigh waves

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    Liu_geo2019-0537.1.pdf
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    Description:
    Accepted manuscript
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    Type
    Article
    Authors
    Liu, Zhaolun cc
    Li, Jing cc
    Hanafy, Sherif M.
    Schuster, Gerard T. cc
    KAUST Department
    Center for Subsurface Imaging and Fluid Modeling
    Earth Science and Engineering Program
    Formerly King Abdullah University of Science and Technology, Department of Earth Science and Engineering, Thuwal, Saudi Arabia; presently King Fahd University of Petroleum and Minerals, College of Petroleum Engineering and Geosciences, Dhahran, Saudi Arabia..
    Physical Science and Engineering (PSE) Division
    Date
    2019-05-24
    Permanent link to this record
    http://hdl.handle.net/10754/660209
    
    Metadata
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    Abstract
    The 2D wave-equation dispersion (WD) inversion method is extended to 3D wave-equation dispersion inversion of surface waves for the shear-velocity distribution. The objective function of 3D WD is the frequency summation of the squared wavenumber [Formula: see text] differences along each azimuth angle of the fundamental or higher modes of Rayleigh waves in each shot gather. The S-wave velocity model is updated by the weighted zero-lag crosscorrelation between the weighted source-side wavefield and the back-projected receiver-side wavefield for each azimuth angle. A multiscale 3D WD strategy is provided, which starts from the pseudo-1D S-velocity model, which is then used to get the 2D WD tomogram, which in turn is used as the starting model for 3D WD. The synthetic and field data examples demonstrate that 3D WD can accurately reconstruct the 3D S-wave velocity model of a laterally heterogeneous medium and has much less of a tendency to getting stuck in a local minimum compared with full-waveform inversion.
    Citation
    Liu, Z., Li, J., Hanafy, S. M., & Schuster, G. (2019). 3D wave-equation dispersion inversion of Rayleigh waves. GEOPHYSICS, 84(5), R673–R691. doi:10.1190/geo2018-0543.1
    Sponsors
    The research reported in this publication was supported by the KAUST in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their support. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST and the IT Research Computing Group. We thank them for providing the computational resources required for carrying out this work.
    Publisher
    Society of Exploration Geophysicists
    Journal
    GEOPHYSICS
    DOI
    10.1190/geo2018-0543.1
    Additional Links
    https://library.seg.org/doi/10.1190/geo2018-0543.1
    ae974a485f413a2113503eed53cd6c53
    10.1190/geo2018-0543.1
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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