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Two-dimensional coherent noise suppression in seismic data using eigendecomposition

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3 Author(s)
Done, W. ; Amoco Production Co. Res. Center, Tulsa, OK, USA ; Kirlin, R.L. ; Moghaddamjoo, A.

A method for the suppression of coherent noise in seismic data based on the eigendecomposition of a data covariance matrix is demonstrated. Based on the Karhunen-Loeve transform, the proposed procedure is useful against noise energy exhibiting both two-dimensional space and time coherencies or coherent two-dimensional patterns which are not necessarily linear and therefore cannot generally be velocity-filtered. This method trains on a region containing the undesired coherent noise; the dominant eigenvectors determined from the covariance matrix of that noise are used to reconstruct the noise in the region of interest. Subtracting the reconstruction from the original data leaves a residual in which the coherent noise has been suppressed. In the example considered, this method effectively suppresses the noise in a record of marine seismic data containing backscattered source energy

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Geoscience and Remote Sensing, IEEE Transactions on  (Volume:29 ,  Issue: 3 )