尉佳,岳龙,杨睿,等. 基于改进的广义S变换的海洋地震资料随机噪音压制[J]. 海洋地质与第四纪地质,2022,42(3): 184-193. doi: 10.16562/j.cnki.0256-1492.2021072801
引用本文: 尉佳,岳龙,杨睿,等. 基于改进的广义S变换的海洋地震资料随机噪音压制[J]. 海洋地质与第四纪地质,2022,42(3): 184-193. doi: 10.16562/j.cnki.0256-1492.2021072801
WEI Jia,YUE Long,YANG Rui,et al. 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,et al. 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

基于改进的广义S变换的海洋地震资料随机噪音压制

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

  • 摘要: 常规广义S变换采用固定的高斯窗参数,在时频分析时不能够兼顾高低频端的信号,同时标准S逆变换在时频域滤波时会产生滤波噪音。本文提出了基于变频率高斯窗的广义S变换,同时改进了S逆变换公式。该方法不仅提升了信号时频谱的聚焦度,而且还消除了滤波噪音。通过计算包含随机噪声干扰信号的瞬时信噪比阈值,然后根据不同阈值有针对性的选择压制随机噪音的处理策略。合成数据和实际地震数据处理结果表明,该方法能够有效的压制随机噪音,提高地震数据信噪比。

     

    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.

     

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