Migration deconvolution vs. least squares migration

Both migration deconvolution (MD) and least squares migration (LSM) are capable of improving the resolution and suppress acquisition footprints in migrated images. In this paper, we investigate the relative performance of these two technologies in enhancing migration image quality, suppressing artifacts and computational efficiency. Both MD and LSM were tested on SEG/EAGE overthrust models. The results indicate that both MD and LSM improve the energy focusing and illumination of the migration images. LSM sharpens the re ection events with increasing iterations at the cost of much more increase in CPU time. In comparison, MD produces significant improvements in the spatial resolution and migration noise suppression of migration images but at a low computation cost.