10001 Richmond Ave., Q Auditorium
Houston, TX 77042
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Speaker: Zhigang Zhang, CGG
Updating a velocity model with salt using full-waveform inversion (FWI) has been a very challenging task. We proposed a time-lag cost function to minimize the amplitude discrepancy between real and synthetic data, and to make good use of low frequency signal to mitigate cycle-skipping, which addressed two key issues in the application of FWI for salt model update. We applied this algorithm to different data sets including wide-azimuth (WAZ) and full-azimuth (FAZ) streamer data as well as OBN data in areas with different salt complexities. In all cases, salt velocity models from FWI led to significantly improved subsalt images. We also demonstrated with one FAZ streamer data example in Keathley Canyon that we probably do not need to use very high frequency FWI for the purpose of subsalt imaging, or at least before we can resolve all the discrepancies between real and synthetic data (e.g., elastic effect, random and coherent noise etc. that are only present in real data). With all the examples seen so far, we believe that the combination of advanced FWI algorithms and appropriate data will bring a step-change to salt model building workflow and subsalt imaging.
Speaker Biography: Zhigang Zhang, CGG
Zhigang Zhang received B.S. (2002) and M.S. (2005) degrees in Geophysics from Peking University, China, and a Ph.D. degree in Oceanography from the University of Rhode Island in 2010. He worked as a Post-Doctorate Fellow at Los Alamos National Laboratory, Earth and Environmental Sciences Division from 2010, and then joined CGG in 2013. He currently serves as a Senior Lead Researcher in CGG's Houston office and works on a variety of topics, including signal processing and full-waveform inversion.
Breakfast will be available starting at 7:00 AM
Technical Talk will start at 7:30
Event will end by 8:30
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