An ensemble-transform Kalman filter: Full-waveform inversion scheme for uncertainty estimation
| Autor: | Julien Thurin, Ludovic Métivier, Romain Brossier |
|---|---|
| Přispěvatelé: | Institut des Sciences de la Terre (ISTerre), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut de recherche pour le développement [IRD] : UR219-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Equations aux Dérivées Partielles (EDP ), Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]) |
| Rok vydání: | 2017 |
| Předmět: |
010504 meteorology & atmospheric sciences
Covariance matrix Computer science full-waveform inversion [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph] Kalman filter tomography 010502 geochemistry & geophysics [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation 01 natural sciences Invariant extended Kalman filter Extended Kalman filter Data assimilation Fast Kalman filter Ensemble Kalman filter statistical Alpha beta filter Algorithm 2D 0105 earth and related environmental sciences |
| Zdroj: | SEG Technical Program Expanded Abstracts 2017 SEG Technical Program Expanded Abstracts 2017, Sep 2017, Houston, United States. pp.1307-1313, ⟨10.1190/segam2017-17733053.1⟩ |
| DOI: | 10.1190/segam2017-17733053.1 |
| Popis: | International audience; Uncertainty Quantification is a major topic for most geophysical tomography techniques, in particular for large-scale problems. In this work, we present an original application of ensemble-based methods to Full Waveform Inversion. This approach relies on a deterministic Ensemble-Transform Kalman Filter borrowed from the Data Assimilation community, and a frequency-domain Full Waveform Inversion. This methodology gives access to a low-rank version of the posterior covariance matrix of our inverse problem, thanks to the ensemble repartition. We can thus extract information from this covariance matrix to assess uncertainty in the Bayesian sense. This proof-of-concept is applied to a 2D Marmousi case, before discussing many questions associated with the design of the scheme. |
| Databáze: | OpenAIRE |
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