In this paper, we recover the amplitude of a seismic
image by approximating the normal (demigrationmigration)
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.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/613 |
| Date | January 2007 |
| Creators | Moghaddam, Peyman P., Herrmann, Felix J., Stolk, Christiaan C. |
| Publisher | Society of Exploration Geophysicists |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | text |
| Rights | Herrmann Felix J. |
Page generated in 0.002 seconds