Square-root variable metric based elastic full waveform inversion and its uncertainty estimation

Q. Liu, Daniel Peter

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The 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.
Original languageEnglish (US)
Title of host publication80th EAGE Conference and Exhibition 2018
PublisherEAGE Publications BV
ISBN (Print)9789462822542
StatePublished - Oct 16 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The 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.


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