Combining Ensemble Transform Kalman Filter and FWI for Assessing Uncertainties

Julien Thurin (1) , Romain Brossier (1) , Ludovic Métivier (1, 2)

1 ISTerre - Institut des Sciences de la Terre
2 EDP - Equations aux Dérivées Partielles

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.

Domaines: Géophysique [physics.geo-ph]; Modélisation et simulation

Julien Thurin, Romain Brossier, Ludovic Métivier. Combining Ensemble Transform Kalman Filter and FWI for Assessing Uncertainties. 81st EAGE Conference and Exhibition 2019 Workshop Programme, Jun 2019, London, United Kingdom. ⟨10.3997/2214-4609.201901997⟩. ⟨hal-02325633⟩