Square-root variable metric based elastic full waveform inversion and its uncertainty estimation
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Earth Science and Engineering Program
Extreme Computing Research Center
Physical Science and Engineering (PSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/663459
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AbstractThe issue of uncertainty estimation is important to full waveform inversion (FWI) but still left behind. In our research, we apply a quasi-Newton method name Square-Root Variable Metric (SRVM) to FWI. To make it memory-affordable, we modify SRVM into a vector version. This approach allows us to retrieve the information about Hessian after the inversion is done. We validate our method on the elastic Marmousi model. The variance map is drawn to quantify the uncertainty, and the prior and posterior distributions are visually compared. The application of SRVM to elastic seems encouraging to have results of inversion and uncertainty estimation.
CitationLiu, Q., & Peter, D. (2018). Square-Root Variable Metric Based Elastic Full Waveform Inversion and Its Uncertainty Estimation. 80th EAGE Conference and Exhibition 2018. doi:10.3997/2214-4609.201801373
SponsorsThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). For computer time, this research used the resources of the Information Technology Division (IT) and Extreme Computing Research Center (ECRC) at KAUST.
Conference/Event name80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition