Generalized diffraction-stack migration and filtering of coherent noise
KAUST DepartmentCenter for Subsurface Imaging and Fluid Modeling
Earth Science and Engineering Program
Environmental Science and Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2014-01-27
Print Publication Date2014-05
Permanent link to this recordhttp://hdl.handle.net/10754/563355
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AbstractWe reformulate the equation of reverse-time migration so that it can be interpreted as summing data along a series of hyperbola-like curves, each one representing a different type of event such as a reflection or multiple. This is a generalization of the familiar diffraction-stack migration algorithm where the migration image at a point is computed by the sum of trace amplitudes along an appropriate hyperbola-like curve. Instead of summing along the curve associated with the primary reflection, the sum is over all scattering events and so this method is named generalized diffraction-stack migration. This formulation leads to filters that can be applied to the generalized diffraction-stack migration operator to mitigate coherent migration artefacts due to, e.g., crosstalk and aliasing. Results with both synthetic and field data show that generalized diffraction-stack migration images have fewer artefacts than those computed by the standard reverse-time migration algorithm. The main drawback is that generalized diffraction-stack migration is much more memory intensive and I/O limited than the standard reverse-time migration method. © 2014 European Association of Geoscientists & Engineers.
SponsorsWe thank the Supercomputing Laboratory at the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia for the computer cycles provided to this project. We appreciate the reviews by the associate editor Ian Jones and the anonymous reviewers, who made a number of helpful suggestions that improved the quality of our manuscript. We would also like to thank WesternGeco for providing the field data. We acknowledge the support of the Center of Subsurface Imaging and Fluid Modelling (CSIM) sponsors (http://csim.kaust.edu.sa/).