Adaptive curvelet-domain primary-multiple separation

Adaptive curvelet-domain primary-multiple separation

Herrmann, F.J.
Wang, D.
Verschuur, D.J.

Civil Engineering and Geosciences

Imaging Science and Technology

2008-05-08

In many exploration areas, successful separation of primaries and multiples greatly determines the quality of seismic imaging. Despite major advances made by surface-related multiple elimination (SRME), amplitude errors in the predicted multiples remain a problem. When these errors vary for each type of multiple in different ways (as a function of offset, time, and dip), they pose a serious challenge for conventional least-squares matching and for the recently introduced separation by curvelet-domain thresholding. We propose a data-adaptive method that corrects amplitude errors, which vary smoothly as a function of location, scale (frequency band), and angle. With this method, the amplitudes can be corrected by an elementwise curvelet-domain scaling of the predicted multiples. We show that this scaling leads to successful estimation of primaries, despite amplitude, sign, timing, and phase errors in the predicted multiples. Our results on synthetic and real data show distinct improvements over conventional least-squares matching in terms of better suppression of multiple energy and high-frequency clutter and better recovery of estimated primaries.

geophysical techniques
least squares approximations
seismology

http://resolver.tudelft.nl/uuid:cacc1e07-acd7-43a6-8d39-b16ad3a3abf0

https://doi.org/10.1190/1.2904986

Society of Exploration Geophysicists

0016-8033

Geophyscis, 73 (3), 2008

Institutional Repository

journal article

© 2008 Society of Exploration Geophysicists