Abstract
Least-squares reverse time migration (LSRTM) is an iterative inversion algorithm for estimating the broadband-wavenumber reflectivity model. Although it produces superior results compared with conventional reverse time migration (RTM), LSRTM is computationally expensive. We have developed a one-step LSRTM method by considering the demigrated and observed data to design a deblurring preconditioner in the data domain using the Wiener filter. For the Wiener filtering, we further use a stabilized division algorithm via the Taylor expansion. The preconditioned observed data are then remigrated to obtain a deblurred image. The total cost of this method is about two RTMs. Through synthetic and real data experiments, we see that one-step LSRTM is able to enhance image resolution and balance source illumination at low computational costs.
Original language | English (US) |
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Pages (from-to) | R361-R368 |
Journal | Geophysics |
Volume | 83 |
Issue number | 4 |
DOIs | |
State | Published - Jul 1 2018 |
Keywords
- Inversion
- Least-squares migration
- Reverse time migration
ASJC Scopus subject areas
- Geochemistry and Petrology