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dc.contributor.authorKormann, Jean
dc.contributor.authorRodriguez, Juan E.
dc.contributor.authorGutiérrez, Natalia
dc.contributor.authorFerrer, Miguel
dc.contributor.authorRojas, Otilio
dc.contributor.authorde la Puente, Josep
dc.contributor.authorHanzich, Mauricio
dc.contributor.authorCela, Jose M.
dc.contributor.otherBarcelona Supercomputing Center
dc.identifier.citationKormann, J. [et al.]. Toward an automatic full-wave inversion: Synthetic study cases. "The Leading Edge", Desembre 2016, vol. 35, núm. 12, p. 1047-1052.
dc.description.abstractFull-waveform inversion (FWI) in seismic scenarios continues to be a complex procedure for subsurface imaging that might require extensive human interaction in terms of model setup, constraints, and data preconditioning. The underlying reason is the strong nonlinearity of the problem that forces the addition of a priori knowledge (or bias) in order to obtain geologically sound results. In particular, when the use of a long-offset receiver is not possible or may not favor the reconstruction of the fine structure of the model, one needs to rely on reflection data. As a consequence, the inversion process is more prone to becoming stuck in local minima. Nevertheless, misfit functionals can be devised that can either cope with missing long-wavenumber features of initial models (e.g., cross-correlation-based misfit) or invert reflection-dominated data whenever the models are sufficiently good (e.g., normalized offset-limited least-squares misfit). By combining both, high-frequency data content with poor initial models can be successfully inverted. If one can figure out simple parameterizations for such functionals, the amount of uncertainty and manual work related to tuning FWI would be substantially reduced. Thus, FWI might become a semiautomatized imaging tool.
dc.description.sponsorshipWe want to thank Repsol for funding this research by means of the Aurora project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 644202. Additionally, the research leading to these results has received funding from the European Union’s Horizon 2020 Programme (2014-2020) and from Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP) under the HPC4E Project (, grant agreement No 689772. We acknowledge Chevron for the dataset that was used in our second example.
dc.format.extent6 p.
dc.publisherSociety of Exploration Geophysicists
dc.subjectÀrees temàtiques de la UPC::Desenvolupament humà i sostenible
dc.subject.lcshSeismic design
dc.subject.lcshWaveforms (Cathode ray oscillographs)
dc.subject.otherFull-waveform inversion
dc.titleToward an automatic full-wave inversion: Synthetic study cases
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/644202/EU/Geophysical Exploration using Advanced GAlerkin Methods/GEAGAM
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/689772/EU/HPC for Energy/HPC4E
upcommons.citation.publicationNameThe Leading Edge

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