Publication Date:
2021-10-17
Description:
Denoising becomes a non-trivial task when noise and signal overlap in multiple domains such as time, frequency, and velocity. Fortunately, signal and noise waveforms in general tend to remain morphologically different. This paper shows how morphological differences can be used to separate body-wave signals from other waveforms such as ground roll and cultural noise. The key was finding a wavelet that was a close approximation of the true source signature (SS) and remained uncontaminated by the Greens function in any significant manner. An inverse filter designed using such a wavelet selectively compressed the body waves which was then extracted using median and low-pass filters. The overall phenomenon is explained with a synthetic example. The idea is also tested on a land dataset that was generated using a large weight drop source where a wavelet recorded ∼3 m from the source location fulfilled the criteria set in the proposed method. Results suggest that the incremental effort of recording an extra trace close to the source location during acquisition may provide previously unavailable denoising opportunities during processing although the trace itself may be redundant for imaging.
Print ISSN:
0016-8033
Electronic ISSN:
1942-2156
Topics:
Geosciences
,
Physics
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