Seismic attributes via robust and high-resolution seismic complex trace analysis
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RESEARCH ARTICLE - APPLIED GEOPHYSICS
Seismic attributes via robust and high‑resolution seismic complex trace analysis Mohsen Kazemnia Kakhki1,4 · Kamal Aghazade3 · Webe João Mansur1,2 · Franciane Conceição Peters1,2 Received: 17 April 2020 / Accepted: 6 October 2020 © Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2020
Abstract Seismic attribute analysis has been a useful tool for interpretation objectives; therefore, high-resolution images of them are of particular concern. The calculation of these attributes by conventional methods is susceptible to noise, and the conventional filtering supposed to lessen the noise causes the loss of the spectral bandwidth. The challenge of having a high-resolution and robust signal processing tool motivated us to propose a sparse time–frequency decomposition which is stabilised for random noise. The procedure initiates by using sparsity-based, adaptive S-transform to regularise abrupt variations in the frequency content of the non-stationary signals. An adaptive filter is then applied to the previously sparsified time–frequency spectrum. The proposed zero adaptive filter enhances the high-amplitude frequency components while suppressing the lower ones. The performance of the proposed method is compared to the sparse S-transform and the robust window Hilbert transform in the estimation of instantaneous attributes through studying synthetic and real data sets. Seismic attributes estimated by the proposed method are superior to the conventional ones, in terms of robustness and high-resolution imaging. The proposed approach has a detailed application in the interpretation and classification of geological structures. Keywords Time–frequency decomposition · Sparsity-based adaptive S-transform · Zero adaptive filter · Robust window Hilbert transform
Introduction Data interpretation in signal analysis can be better accomplished if a distinct aspect of the data is accessible. This aim can be achieved by transforming the data from one domain to another. The Fourier transform is one of the common transformations which empower us to survey the average properties of a remarkably vast portion of a trace, although it does not represent local variations. The complex trace was first introduced to seismology by Taner et al. (1979); it
* Mohsen Kazemnia Kakhki [email protected] 1
Modelling Methods in Engineering and Geophysics Laboratory (LAMEMO), COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941‑596, Brazil
2
Department of Civil Engineering, COPPE, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
3
Institute of Geophysics, University of Tehran, Tehran, Iran
4
Ferdowsi University of Mashhad, Mashhad, Iran
resolved this problem by maintaining the local significance and providing a new perspective. Traditional seismic interpretation methods are incapable of deciphering subtle geological features; this fact has been investigated by researchers, who have explored various techniques to resolve this challenge. Inst
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