Deconvolution of nonstationary seismic data using adaptive lattice filters

Mahalanbis, A. ; Prasad, S. ; Mohandas, K. (1983) Deconvolution of nonstationary seismic data using adaptive lattice filters IEEE Transactions on Acoustics, Speech and Signal Processing, 31 (3). pp. 591-598. ISSN 0096-3518

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This paper examines the results of the application of two lattice algorithm to the problem of adaptive deconvolution on non-stationary seismic data. A comparative study of the deconvolution performance of the recently proposed gradient lattice and least-squares lattice algorithms is made with the help of experiments on simulated and real seismic data. We show that the gradient lattice algorithm is computationally superior, but it suffers from a possible slow rate of convergence, while the least-squares lattice has better convergence properties and is more robust numerically. We also show that both algorithms can yield equally good deconvolution results with a moderate amount of computation. Finally we indicate that a modified deconvolved output, derived as a linear combination of the forward and backward residuals, improves the performance without involving any additional computational burden.

Item Type:Article
Source:Copyright of this article belongs to IEEE.
ID Code:54702
Deposited On:12 Aug 2011 06:10
Last Modified:12 Aug 2011 06:10

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