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Probabilistic waveform inversion: Quest for the law

Shigapov, Renat

Abstract (englisch):
Full-waveform inversion (FWI) is an algorithm (and a part of the measuring procedure in a wide sense) with the aim to find the governing law of a physical system using the partially measured physical fields with limited computational resources. A law is a forward theory equipped with the model parameters and the data parameters. The main characteristic of the law is the realizability assumption: the law explains all subsets of the measured data parameters and predicts all subsets of the unmeasured (in the given experiment) data parameters. To find the law, we have to guess a law (a forward theory and parametrization), measure some data parameters and check the realizability assumption.
To put it more precisely, I formulate a new probabilistic setting for inverse problems and full-waveform inversion. Instead of using the Bayes' theorem, the Tarantola-Valette conjunction or the principle of maximum entropy based on the prior information for the averaged quantities, I propose a principle of minimum relative information using the prior information for the non-averaged quantities. The Tarantola-Valette formula is obtained as a special ... mehr

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Volltext §
DOI: 10.5445/IR/1000091433
Veröffentlicht am 22.02.2019
Zugehörige Institution(en) am KIT Geophysikalisches Institut (GPI)
Publikationstyp Hochschulschrift
Jahr 2019
Sprache Englisch
Identifikator urn:nbn:de:swb:90-914330
KITopen-ID: 1000091433
Verlag KIT, Karlsruhe
Umfang VI, 73 S.
Abschlussart Dissertation
Fakultät Fakultät für Physik (PHYSIK)
Institut Geophysikalisches Institut (GPI)
Prüfungsdatum 08.02.2019
Referent/Betreuer Prof. T. Bohlen
Schlagworte Full-waveform inversion, probabilistic waveform inversion, probabilistic inverse problems, uncertainty and sensitivity analysis
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