Abstract
Full waveform inversion (FWI) is an ill-posed data-fitting technique that can benefit significantly from preconditioning and/or regularization. We propose to help constrain the FWI problem by using the readily available, imperfect information derived from seismic migration, namely the approximate position in space of the dominant seismic reflection events. A 2D Laplacian filtering framework is described that allows us to modify the local wavenumber content of the FWI gradient via non-stationary filtering. This workflow is applied to a 2D synthetic dataset to highlight its effectiveness. The application of the filtering adds little to no time to the FWI workflow and should be extended straightforwardly to a 3D application.
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