In this paper, we recover the amplitude of a seismic image by approximating the normal (demigration-migration) operator. In this approximation, we make use of the property that curvelets remain invariant under the action of the normal operator. We propose a seismic amplitude recovery method that employs an eigenvalue like decomposition for the normal operator using curvelets as eigen-vectors. Subsequently, we propose an approximate non-linear singularity-preserving solution to the least-squares seismic imaging problem with sparseness in the curvelet domain and spatial continuity constraints. Our method is tested with a reverse-time `wave-equation' migration code simulating the acoustic wave equation on the SEG-AA salt model.
|Name||SEG Technical Program Expanded Abstracts|
|Publisher||Society of Exploration Geophysicists|
|Conference||SEG Technical Program Expanded Abstracts - 2007|
|Period||23/09/07 → 28/09/07|
|Other||23-28 September 2007|