Multi-term multiple prediction using separated reflections and diffractions combined with curvelet-based subtraction

UBC Faculty Research and Publications

Multi-term multiple prediction using separated reflections and diffractions combined with curvelet-based subtraction Verschuur, Dirk J.; Wang, Deli; Herrmann, Felix J.

Abstract

The surface-related multiple elimination (SRME) method has proven to be successful on a large number of data cases. Most of the applications are still 2D, as the full 3D implementation is still expensive and under development. However, the earth is a 3D medium, such that 3D effects are difficult to avoid. Most of the 3D effects come from diffractive structures, whereas the specular reflections normally have less of a 3D behavior. By separating the seismic data in a specular reflecting and a diffractive part, multiple prediction can be carried out with these different subsets of the input data, resulting in several categories of predicted multiples. Because each category of predicted multiples can be subtracted from the input data with different adaptation filters, a more flexible SRME procedure is obtained. Based on some initial results from a Gulf of Mexico dataset, the potential of this approach is investigated.

Item Metadata

Title	Multi-term multiple prediction using separated reflections and diffractions combined with curvelet-based subtraction
Creator	Verschuur, Dirk J.; Wang, Deli; Herrmann, Felix J.
Contributor	University of British Columbia. Seismic Laboratory for Imaging and Modeling
Publisher	Society of Exploration Geophysicists
Date Issued	2007
Description	The surface-related multiple elimination (SRME) method has proven to be successful on a large number of data cases. Most of the applications are still 2D, as the full 3D implementation is still expensive and under development. However, the earth is a 3D medium, such that 3D effects are difficult to avoid. Most of the 3D effects come from diffractive structures, whereas the specular reflections normally have less of a 3D behavior. By separating the seismic data in a specular reflecting and a diffractive part, multiple prediction can be carried out with these different subsets of the input data, resulting in several categories of predicted multiples. Because each category of predicted multiples can be subtracted from the input data with different adaptation filters, a more flexible SRME procedure is obtained. Based on some initial results from a Gulf of Mexico dataset, the potential of this approach is investigated.
Extent	4301656 bytes
Subject	Surface related multiple elimination; SRME; 2D; 3D; Curvelet; Subtraction; Curvelet transform; Gulf of Mexico; Multiple; Removal
Genre	Conference Paper
Type	Text
File Format	application/pdf
Language	eng
Date Available	2008-03-11
Provider	Vancouver : University of British Columbia Library
Rights	All rights reserved
DOI	10.14288/1.0107411
URI	http://hdl.handle.net/2429/561
Affiliation	Science, Faculty of; Earth and Ocean Sciences, Department of
Citation	Verschuur, Dirk Jacob, Wang, Deli, Herrmann, Felix J. 2007. Multi-term multiple prediction using separated reflections and diffractions combined with curvelet-based subtraction. SEG International Exposition and 77th Annual Meeting.
Peer Review Status	Unreviewed
Scholarly Level	Faculty; Graduate
Copyright Holder	Herrmann, Felix J.
Aggregated Source Repository	DSpace

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