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dc.contributor.authorLiu, Q.
dc.contributor.authorPeter, Daniel
dc.date.accessioned2020-06-09T10:55:27Z
dc.date.available2020-06-09T10:55:27Z
dc.date.issued2018-10-16
dc.identifier.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
dc.identifier.isbn9789462822542
dc.identifier.doi10.3997/2214-4609.201801373
dc.identifier.urihttp://hdl.handle.net/10754/663459
dc.description.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.
dc.description.sponsorshipThe 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.
dc.publisherEAGE Publications
dc.relation.urlhttp://www.earthdoc.org/publication/publicationdetails/?publication=92763
dc.rightsArchived with thanks to EAGE Publications BV
dc.titleSquare-root variable metric based elastic full waveform inversion and its uncertainty estimation
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentExtreme Computing Research Center
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.conference.date2018-06-11 to 2018-06-14
dc.conference.name80th EAGE Conference and Exhibition 2018: Opportunities Presented by the Energy Transition
dc.conference.locationCopenhagen, DNK
dc.eprint.versionPost-print
kaust.personLiu, Q.
kaust.personPeter, Daniel
dc.identifier.eid2-s2.0-85083937613
kaust.acknowledged.supportUnitExtreme Computing Research Center (ECRC)
kaust.acknowledged.supportUnitInformation Technology Division


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