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New algorithms for sparse multichannel blind deconvolution

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posted on 02.05.2022, 18:14 by Kenji Nose FilhoKenji Nose Filho, Renato Lopes, Renan BrottoRenan Brotto, Thonia Senna, João Romano

In this paper we present three new algorithms for sparse multichannel blind deconvolution. The first algorithm is based on a cascade of a forward and a backward prediction error filter. The second consists in an alternating minimization algorithm for estimating both the reflectivity series and the seismic wavelet. The last one is a regularized version of the so called Euclid deconvolution, solved by the well known fast iterative shrinkage-thresholding algorithm (FISTA). Simulation results illustrate that the three algorithms presents some quite interesting results in both synthetic and real data.

Funding

São Paulo Research Foundation (FAPESP) under grants \#2019/20899-4, and \#2020/09838-0 (BI0S - Brazilian Institute of Data Science)

Coordination for the Improvement of Higher Education Personnel, code 001

National Council for Scientific and Technological Development (CNPq) under grant 310824/2021-4

History

Email Address of Submitting Author

kenjinose@yahoo.com.br

ORCID of Submitting Author

0000-0002-2559-1973

Submitting Author's Institution

Federal University of the ABC

Submitting Author's Country

Brazil

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