Robust Imaging Methodology for Challenging Environments: Wave Equation Dispersion Inversion of Surface Waves
KAUST DepartmentCenter for Subsurface Imaging and Fluid Modeling
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2017-10-12
Print Publication Date2017-10-12
Permanent link to this recordhttp://hdl.handle.net/10754/626768
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AbstractA robust imaging technology is reviewed that provide subsurface information in challenging environments: wave-equation dispersion inversion (WD) of surface waves for the shear velocity model. We demonstrate the benefits and liabilities of the method with synthetic seismograms and field data. The benefits of WD are that 1) there is no layered medium assumption, as there is in conventional inversion of dispersion curves, so that the 2D or 3D S-velocity model can be reliably obtained with seismic surveys over rugged topography, and 2) WD mostly avoids getting stuck in local minima. The synthetic and field data examples demonstrate that WD can accurately reconstruct the S-wave velocity distributions in laterally heterogeneous media if the dispersion curves can be identified and picked. The WD method is easily extended to anisotropic media and the inversion of dispersion curves associated with Love wave. The liability is that is almost as expensive as FWI and only recovers the Vs distribution to a depth no deeper than about 1/2~1/3 wavelength.
CitationLi J, Schuster G, Zeng Z (2017) Robust Imaging Methodology for Challenging Environments: Wave Equation Dispersion Inversion of Surface Waves. International Conference on Engineering Geophysics, Al Ain, United Arab Emirates, 9-12 October 2017. Available: http://dx.doi.org/10.1190/iceg2017-087.
SponsorsWe thank the sponsors of the CSIM consortium for their financial support. We also thank the KAUST supercomputing center for use of their supercomputer.
PublisherSociety of Exploration Geophysicists
JournalInternational Conference on Engineering Geophysics, Al Ain, United Arab Emirates, 9-12 October 2017