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Combining Ensemble Transform Kalman Filter and FWI for Assessing UncertaintiesNormal access

Authors: J. Thurin, R. Brossier and L. Métivier
Event name: 81st EAGE Conference and Exhibition 2019 Workshop Programme
Session: WS14 Uncertainty Quantification in Seismic Modelling and Inversion
Publication date: 03 June 2019
DOI: 10.3997/2214-4609.201901997
Organisations: EAGE
Language: English
Info: Extended abstract, PDF ( 404.87Kb )
Price: € 20

Full Waveform Inversion (FWI) is an iterative inversion method whose purpose is to retrieve high-resolution models of subsurface physical parameters. Because FWI relies on the solution of a non-linear ill-posed inverse problem, uncertainty estimation is a crucial issue in practical applications, both in seismology and exploration seismic. While uncertainty assessment is a strongly desired feature for FWI, it remains a challenging problem. In this presentation, we investigate uncertainty estimation within the framework provided by ensemble data-assimilation strategies. We combine the Ensemble Transform Kalman Filter and FWI. We review the concepts underlying our ETKF-FWI method, discuss its limitations and appeals for uncertainty estimation, and illustrate it on a 2D multiparameter inversion of an exploration scale field dataset.

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