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dc.contributor.authorBallesio, Marco
dc.contributor.authorBeck, Joakim
dc.contributor.authorPandey, Anamika
dc.contributor.authorParisi, Laura
dc.contributor.authorvon Schwerin, Erik
dc.contributor.authorTempone, Raul
dc.date.accessioned2019-01-13T05:34:00Z
dc.date.available2019-01-13T05:34:00Z
dc.date.issued2018-09-07
dc.identifier.urihttp://hdl.handle.net/10754/630795
dc.description.abstractWe will present results from a case study based on an earthquake with seismograms recorded on a small dense seismic network in the Ngorongoro Conservation Area in Tanzania. We consider forward seismic wave propagation in an inhomogeneous linear viscoelastic media with random wave speeds and densities, subject to deterministic boundary and initial conditions. The random parameters model the inherent uncertainty of the Earth parameters. We use multilevel Monte Carlo simulations for computing statistics of quantities of interest chosen to formulate a suitable loss function for the corresponding source inversion problem. We use recorded seismograms to study a noise model for use in Bayesian inverse problems. This work provides a benchmark for the implementation of Multilevel algorithms to accelerate Seismic Inversion addressing earthquake source estimation as well as inferring Earth structure.
dc.rightsAttribution-NoDerivs 3.0 United States
dc.rights.urihttp://creativecommons.org/licenses/by-nd/3.0/us/
dc.titleA Case Study of Seismic Wave Propagation with Random Parameters
dc.typePoster
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.conference.date5-7 September, 2018
dc.conference.nameFrontUQ18 Workshop on Frontiers of Uncertainty Quantification in Subsurface Environments
dc.conference.locationPavia, Italy
refterms.dateFOA2019-01-13T05:34:01Z


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Except where otherwise noted, this item's license is described as Attribution-NoDerivs 3.0 United States