E-Lecture Webinar: FWI with Optimal Transport: a 3D Implementation and an Application on a Field Dataset
|Duration:||30 min + Q&A|
|Discipline:|| Surface Imagine
|Main topics:|| FWI
We present the application to a 3D real dataset of full waveform inversion (FWI) with optimal transport (OT) using the Kantorovich-Rubinstein (KR) distance as proposed by Métivier et al. (2016). This approach involves an efficient numerical implementation for OT in time and space directions, allowing the lateral coherency of the traces to be taken into account; this has an important impact on the quality of the results. The approach also exhibits a reduced sensitivity to local minima compared to least squares (LSQ) misfit. Moreover, the iterative method used for the computation of the KR distance allows the production of a set of intermediary solutions that span progressively from LSQ to OT. We recall the main components of the approach and present its numerical implementation in 3D. We show the improvement of the results compared to LSQ FWI on real datasets.
Any geophysicist (production or research), especially those interested in FWI.
About the Lecturer
Jeremie joined CGG in 2012; currently in a Research advisor position.
Research work on Orthorhombic tomography, a new RTM imaging condition, tomography and structural (Bayesian) uncertainties, Optimal transport FWI. Now focusing on Deep learning for seismic processing.
Especially motivated by evolving challenges related to new technologies, mathematics and physics.