Seismic imaging and processing with curvelets Herrmann, Felix J.; Hennenfent, Gilles; Moghaddam, Peyman P.
In this paper, we present a nonlinear curvelet-based sparsity-promoting formulation for three problems in seismic processing and imaging namely, seismic data regularization from data with large percentages of traces missing; seismic amplitude recovery for subsalt images obtained by reverse-time migration and primary-multiple separation, given an inaccurate multiple prediction. We argue why these nonlinear formulations are beneficial.
Item Citations and Data
All rights reserved