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Curvelet-based migration amplitude recovery

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dc.contributor.author P. Moghaddam, Peyman
dc.date.accessioned 2010-05-04T17:27:36Z
dc.date.available 2010-05-04T17:27:36Z
dc.date.copyright 2010 en
dc.date.issued 2010-05-04T17:27:36Z
dc.identifier.uri http://hdl.handle.net/2429/24421
dc.description.abstract Migration can accurately locate reflectors in the earth but in most cases fails to correctly resolve their amplitude. This might lead to mis-interpretation of the nature of reflector. In this thesis, I introduced a method to accurately recover the amplitude of the seismic reflector. This method relies on a new transform-based recovery that exploits the expression of seismic images by the recently developed curvelet transform. The elements of this transform, called curvelets, are multi-dimensional, multi-scale, and multi-directional. They also remain approximately invariant under the imaging operator. I exploit these properties of the curvelets to introduce a method called Curvelet Match Filtering (CMF) for recovering the seismic amplitude in presence of noise in both migrated image and data. I detail the method and illustrate its performance on synthetic dataset. I also extend CMF formulation to other geophysical applications and present results on multiple removal. In addition of that, I investigate preconditioning of the migration which results to rapid convergence rate of the iterative method using migration. en
dc.language.iso eng en
dc.publisher University of British Columbia
dc.rights Attribution-NonCommercial 2.5 Canada *
dc.rights.uri http://creativecommons.org/licenses/by-nc/3.0/ *
dc.title Curvelet-based migration amplitude recovery en
dc.type Electronic Thesis or Dissertation
dc.degree.name Doctor of Philosophy - PhD en
dc.degree.discipline Geophysics en
dc.degree.grantor University of British Columbia
dc.date.graduation 2010-11 en
dc.degree.campus UBCV en
dc.description.scholarlevel Graduate en


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