基于S变换的软阈值滤波在深地震反射数据处理中的应用

深地震反射原始单炮数据是非平稳的弱能量反射信号,信噪比较低.如何提高信噪比一直是深地震反射数据前处理中的一大难题.S变换是一种适用于分析非平稳信号的时频变换方法.同其他分析时变信号的方法相比,S变换的基本小波不必满足小波在时间域均值为零的容许性条件,它的时频分辨率与分析信号的频率有关,且其在时间域的积分可以得到傅里叶频谱,其反变换也简单.因此,S变换容易表示深地震反射信号复杂的时频特性.本文在S变换的基础上,利用软阈值滤波方法对深地震反射数据进行处理,实验结果表明,该方法有效地提高了信噪比,压制了有效频带范围内的混频干扰,突出了弱反射信号,使得波组信息更加丰富,有利于连续追踪有效反射波组和识别薄地层,特别是提高了深部Moho界面反射层位的分辨率,为深地震反射剖面后续处理和准确解释奠定了基础.

Soft threshold filter based on S transform and its application to data processing of deep seismic reflection

Shot-gather data in deep seismic reflection profiling have complicated characteristics of non-stationary, weak energy, a wide variety of strong noise, and so on. How to increase signal to noise ratio of the shot gather has been one big hard nut to crack. We use the soft threshold filter based on S transform to process the obsolete data and show its chart flow is valid. Stockwell (1996) proposed S transform, which is a time-frequency transformation method to analyze non-stationary signal. Compared with other methods for analyzing time-varying signal, the basic wavelet of S transform does not meet an admissibility condition of zero mean in the time domain. The broadness of time window in S transform has an inverse ratio to frequency, which is wide at low frequency and narrow at high frequency. So, the time-frequency resolution in S transform is related to the signal frequency, which has high frequency resolution at low frequency and high time resolution at high frequency. A simple operation of sum along the time axis in the S transform domain can get the Fourier spectrum. Therefore, it is simple to invert S transform. The hard threshold and the soft threshold are the most common methods in de-noising. The soft threshold is better than the hard threshold generally, though it may cause over-smoothing effects. The threshold is calculated from the noise before the first break in the S transform domain. The data are collected in the junction of the southwest Tian Shan and Tarim Basin, northwestern China. This shot set is exploded with 40 kg charge placed in a 24 m-deep borehole and gathered on a 2 ms sampling rate with a 50 m group interval. The raw shot set has a variety of strong noise, and the signal after 5 s is difficult to recognize. After time-invariant bandpass filtering (5~25 Hz) and AGC, the signal to noise ratio is obviously improved. However, mixing interference in 5~25 Hz hampers the identification of thin layers at depth. So, we filter the data further using the soft threshold filter based on S transform to highlight the weak reflection and the Moho reflector. We use the soft threshold filter based on S transform to process the deep seismic reflection data. Our results show that the processing flow does improve signal to noise ratio in deep seismic reflection effectively, which suppresses the frequency mixing interference and enhances weak reflection signal, favorable to track wave groups and further to recognize thin layers. The method increases stratigraphic resolution of the Moho discontinuity especially, which provides the base for subsequent data processing and interpretation of deep seismic reflection profiling. In addition, S transform can be calculated in the frequency domain with the benefits of high calculation efficiency. So, the soft threshold filter based on S transform can also be used in de-noising of other seismic data.