Seismic multiple removal with a Primal-Dual proximal algorithm
| Autor: | Jean-Christophe Pesquet, Caroline Chaux, Mai Quyen Pham, Laurent Duval |
|---|---|
| Přispěvatelé: | Laboratoire d'Informatique Gaspard-Monge (LIGM), Centre National de la Recherche Scientifique (CNRS)-Fédération de Recherche Bézout-ESIEE Paris-École des Ponts ParisTech (ENPC)-Université Paris-Est Marne-la-Vallée (UPEM), IFP Energies nouvelles (IFPEN), Laboratoire d'Analyse, Topologie, Probabilités (LATP), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Pham, Mai Quyen, Université Paris-Est Marne-la-Vallée (UPEM)-École des Ponts ParisTech (ENPC)-ESIEE Paris-Fédération de Recherche Bézout-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Mathematical optimization
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing Stochastic process Frame (networking) Process (computing) Wavelet transform 020206 networking & telecommunications 02 engineering and technology Geophysical signal processing Adaptive filter Wavelet transforms Wavelet [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Prior probability 0202 electrical engineering electronic engineering information engineering Adaptive filters 020201 artificial intelligence & image processing Algorithm Optimization methods [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Multiple [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing Mathematics Signal restoration |
| Zdroj: | Proc. ICASSP ICASSP ICASSP, May 2013, Vancouver, Canada. 5 pp |
| Popis: | International audience; Both random and structured perturbations affect seismic data. Their removal, to unveil meaningful geophysical information, requires additional priors. Seismic multiples are one form of structured perturbations related to wave-field bouncing. In this paper, we model these undesired signals through a time-varying filtering process accounting for inaccuracies in amplitude, time-shift and average frequency of available templates. We recast the problem of jointly estimating the filters and the signal of interest (primary) in a new convex variational formulation, allowing the incorporation of knowledge about the noise statistics. By making some physically plausible assumptions about the slow time variations of the filters, and by adopting a potential promoting the sparsity of the primary in a wavelet frame, we design a primal-dual algorithm which yields good performance in the provided simulation examples. |
| Databáze: | OpenAIRE |
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