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dc.contributor.authorLiu, Zhaolun
dc.contributor.authorLi, Jing
dc.contributor.authorHanafy, Sherif M.
dc.contributor.authorLu, Kai
dc.contributor.authorSchuster, Gerard T.
dc.date.accessioned2020-02-10T13:51:13Z
dc.date.available2020-02-10T13:51:13Z
dc.date.issued2020-01-09
dc.date.submitted2019-08-06
dc.identifier.citationLiu, Z., Li, J., Hanafy, S. M., Lu, K., & Schuster, G. (2020). 3D Wave-equation Dispersion Inversion of Surface Waves Recorded on Irregular Topography. GEOPHYSICS, 1–93. doi:10.1190/geo2019-0537.1
dc.identifier.doi10.1190/geo2019-0537.1
dc.identifier.doi10.1190/segam2019-3215009.1
dc.identifier.urihttp://hdl.handle.net/10754/661455
dc.description.abstractIrregular topography can cause strong scattering and defocusing of propagating surface waves, so it is important to account for such effects when inverting surface waves for the shallow S-wave velocity structures. We now present a 3D surface-wave dispersion inversion method that takes into account the topographic effects modeled by a 3D spectral element solver. The objective function is the frequency summation of the squared wavenumber differences κ(ω) along each azimuthal angle of the fundamental mode or higher-order modes of Rayleigh waves in each shot gather. The wavenumbers Δκ(ω)<jats:sup>2</jats:sup> associated with the dispersion curves are calculated using the data recorded along the irregular free surface. Numerical tests on both synthetic and field data demonstrate that 3D topographic wave equation dispersion inversion (TWD) can accurately invert for the S-wave velocity model from surface-wave data recorded on irregular topography. Field data tests for data recorded across an Arizona fault suggest that, for this example, the 2D TWD can be as accurate as the 3D tomographic model. This suggests that in some cases the 2D TWD inversion is preferred over 3D TWD because of its significant reduction in computational costs. Compared to the 3-D P-wave velocity tomogram, the 3D S-wave tomogram agrees much more closely with the geological model taken from the trench log. The agreement with the trench log is even better when the Vp/Vs tomogram is computed, which reveals a sharp change in velocity across the fault. The localized velocity anomaly in the Vp/Vs tomogram is in very good agreement with the well log. Our results suggest that integrating the Vp and Vs tomograms can sometimes give the most accurate estimates of the subsurface geology across normal faults.
dc.description.sponsorshipWe dedicate this paper to Dimitri Komatitsch and his loving family members, he is a light that has gone out much too early. We also thank Ron Bruhn for his valuable advice about the geological explanation of our eld results. The research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling Consortium for their nancial 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.
dc.publisherSociety of Exploration Geophysicists
dc.relation.urlhttps://library.seg.org/doi/10.1190/geo2019-0537.1
dc.rightsArchived with thanks to GEOPHYSICS
dc.title3D Wave-equation Dispersion Inversion of Surface Waves Recorded on Irregular Topography
dc.typeArticle
dc.contributor.departmentCenter for Subsurface Imaging and Fluid Modeling
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentFormerly 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..
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalGEOPHYSICS
dc.eprint.versionPost-print
dc.contributor.institutionCollege of Geo-Exploration Science and Technology, Jilin University, Changchun 130021, China..
kaust.personLiu, Zhaolun
kaust.personHanafy, Sherif M.
kaust.personLu, Kai
kaust.personSchuster, Gerard T.
refterms.dateFOA2020-02-10T13:51:49Z
kaust.acknowledged.supportUnitCenter for Subsurface Imaging and Modeling Consortium
kaust.acknowledged.supportUnitIT Research Computing Group
kaust.acknowledged.supportUnitSupercomputing Laboratory at KAUST
dc.date.published-online2020-01-09
dc.date.published-print2020-05-01


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