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  • 1
    Publication Date: 2015-09-18
    Description: Attenuating random noise is of great significance in seismic data processing. In recent years, time–frequency peak filtering (TFPF) has been successfully applied to seismic random noise attenuation field. However, a fixed window length (WL) is used in the conventional TFPF. Since a short WL in the TFPF is used to preserve signals while a long WL can eliminate random noise effectively, signal preserving and noise attenuation cannot be balanced by a fixed WL especially when the signal-to-noise ratio of the noisy seismic record is low. Thus, we need to divide a noisy signal into signal and noise segments before the filtering. Then a short WL is used to the signal segments to preserve signals and a long WL is chosen for noise segments to eliminate random noise. In this paper, we test the smoothness of signals and random noise in time using the Hurst exponent which is a statistic for representing smoothness characteristics of signals. The time-series of signals with higher smoothness which lead to larger Hurst exponent values, however random noise is a random series in time without fixed waveforms and thus its smoothness is low, so the signal and noise segments can be divided by the Hurst exponent values. After the segmentation, we can adopt different filtering WLs in the TFPF for different segments to make a trade-off between signal preserving and random noise attenuation. Synthetic and real data experiments demonstrate that the proposed method can remove random noise from seismic record and preserve reflection events effectively.
    Keywords: Marine Geosciences and Applied Geophysics
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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