Seismic data processing with curvelets: a multiscale and nonlinear approach.
Felix J. Herrmann, Deli Wang, Gilles Hennenfent, Peyman Poor Moghaddam · cIRcle (University of British Columbia) · 2008
In this abstract, we present a nonlinear curvelet-based sparsity promoting formulation of a seismic processing flow, consisting of the following steps: seismic data regularization and the restoration of migration amplitudes. We show that the curvelet’s wavefront detection capability and invariance under the migration-demigration operator lead to a formulation that is stable under noise and missing data.