Random noise suppression of marine seismic data based on improved generalized S transform

WEI Jia; YUE Long; YANG Rui; XU Qingfeng; LI Zhiqiang; LIU Yun

doi:10.16562/j.cnki.0256-1492.2021072801

2022 Vol. 42, No. 3

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Article navigation > Marine Geology & Quaternary Geology > 2022 > 42(3): 184-193

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WEI Jia, YUE Long, YANG Rui, XU Qingfeng, LI Zhiqiang, LIU Yun. Random noise suppression of marine seismic data based on improved generalized S transform[J]. Marine Geology & Quaternary Geology, 2022, 42(3): 184-193. doi: 10.16562/j.cnki.0256-1492.2021072801

Citation:

WEI Jia, YUE Long, YANG Rui, XU Qingfeng, LI Zhiqiang, LIU Yun. Random noise suppression of marine seismic data based on improved generalized S transform[J]. Marine Geology & Quaternary Geology, 2022, 42(3): 184-193. doi: 10.16562/j.cnki.0256-1492.2021072801

Random noise suppression of marine seismic data based on improved generalized S transform

1.
Key Laboratory of Gas Hydrate, Ministry of Natural Resources, Qingdao Institute of Marine Geology, Qingdao 266237, China
2.
Qingdao Seismic Station, Earthquake Administration of Shandong Province, Qingdao 266001, China

More Information

Corresponding author: XU Qingfeng, 845882668@qq.com

Received Date: 28 July 2021

Revised Date: 19 October 2021

Accepted Date: 10 October 2021

Publish Date: 28 June 2022

Abstract

Abstract

Conventional generalized S transform (GST) uses fixed parameters for Gaussian window, which makes it impossible to take into account the high and low frequency signals in the time-frequency analysis. At the same time, the standard S inverse transform produces filtering noise when filtering in the time-frequency domain. In this paper, a generalized S transform based on variable frequency Gaussian window is proposed, and the inverse S transform formula is revised. This method not only improves the focus of the frequency spectrum of the signal, but also eliminates the filtering noise. By calculating the instantaneous signal-to-noise ratio threshold value of the signal containing random interference noise, and according to different threshold values, the processing strategy of suppressing the random noise is selected in a targeted manner. The processing results of synthetic data and actual seismic data show that the method can effectively suppress random noise and improve the signal-to-noise ratio of seismic data.
- improved generalized S transform /
- time-frequency filtering /
- random noise suppression

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References

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