Fast least squares migration with a deblurring filer

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Publication Type thesis
School or College College of Mines & Earth Sciences
Department Geology & Geophysics
Author Aoki, Naoshi
Title Fast least squares migration with a deblurring filer
Date 2009-05
Description Least squares migration (LSM) is a linearized waveform inversion for estimating a subsurface reflectivity model that, relative to conventional migration, offers improved spatial resolution of migration images. The cost, however, is that LSM typically requires 10 or more iterations, which is about 20 times or more the computational cost of conventional migration. To alleviate this expense, I present a deblurring filter that can be employed in either a regularization scheme or a preconditioning scheme to give acceptable LSM images with less than | the cost of the standard LSM method. My results in applying deblurred LSM (DLSM) to synthetic data and field data support this claim. In particular, a Marmousi2 model test showed that the data residual for preconditioned DLSM decreases rapidly in the first iteration, which is equivalent to 10 or more iterations of LSM. Empirical results suggest that regularized DLSM after three iterations is equivalent to about 10 iterations of LSM. Applying DLSM to two-dimensional marine data gives a higher resolution image compared to those from migration or LSM with three iterations. These results suggest that LSM combined with a deblurring filter allows LSM to be a fast and practical tool for improved imaging of complicated structures.
Type Text
Publisher University of Utah
Subject Seismic prospecting; Least squares
Dissertation Institution University of Utah
Dissertation Name MS
Language eng
Relation is Version of Digital reproduction of "Fast least squares migration with a deblurring filter " J. Willard Marriott Library Special Collections, TNK7.5 2009 .A64
Rights Management © Naoshi Aoki
Format Medium application/pdf
Format Extent 112,016 bytes
Identifier us-etd2,105762
Source Original: University of Utah J. Willard Marriott Library Special Collections
Conversion Specifications Orginal scanned on Epson GT-30000 as 400 dpi to pdf using ABBYY FineReader 9.0 Professional Edition.
ARK ark:/87278/s6f19dbr
Setname ir_etd
Date Created 2012-04-23
Date Modified 2021-05-06
ID 193466
Reference URL