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Blind seismic wavefield separation using frequency singular value decomposition

Lookup NU author(s): Aws Al-Qaisi, Dr Wai Lok Woo, Professor Satnam Dlay



This paper presents a new blind statistical approach based on frequency singular value decomposition to enhance the SNR of the full multicomponent seismic wavefield as well as separating the seismic primary waves. A model of wideband polarized seismic wavefield that are received by linear array of three component sensors is used as framework for implementing the proposed algorithm. This algorithm explicitly exploits the Eigen-structure of reduced dimensional spectral covariance matrix. The blind separation of first primary wave is achieved by projecting the first eigenvector that has the highest eigenvalue of this covariance matrix on the long data vector that contains information on all frequencies and all components interactions of the multicomponent seismic wave-field. In addition, the experimental results have shown that the proposed algorithm outperforms the conventional separation technique in terms of accuracy and complexity.

Publication metadata

Author(s): Al-Qaisi AK, Woo WL, Dlay SS

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: EUROCON

Year of Conference: 2009

Pages: 1378-1385

Date deposited: 28/05/2010

Publisher: IEEE


DOI: 10.1109/EURCON.2009.5167820

Library holdings: Search Newcastle University Library for this item

ISBN: 9781424438600