Varying-Window-Length Time-Frequency Peak Filtering and its Application to Seismic Data
Varying-Window-Length Time-Frequency Peak Filtering and its Application to Seismic Data
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DOI：
10.1109/cis.2008.160
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发表时间：
2008-12
期刊：
影响因子：
--
通讯作者：
Hongbo Lin;Yue Li;Baojun Yang
中科院分区：
文献类型：
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作者：
Hongbo Lin;Yue Li;Baojun Yang
本文提出了变窗长度时频峰值滤波（VWL-TFPF），以提高其去除随机噪声和保留非线性信号高频分量的能力。 TFPF具有良好的去除随机白噪声和增强带限确定性信号的性能，但在去除随机噪声时可能会使具有各种主频率的复杂非线性信号（例如地震信号）的波形失真。应使用PWVD来保证TFP的线性中频条件，因此加窗长度对于消除随机噪声和保留信号波形很重要。本文分析了窗长、采样频率和信号主频之间的关系。根据该关系，VWL-TFPF方法在信号的不同时间段选择不同的时间窗长度，以解决由于TFPF窗长不合适而导致的高频分量失真。该方法不需要设计滤波器的频段，信号先验条件也很少。利用合成资料和共炮点地震资料对该方法进行了验证。结果表明，VWL-TFPF技术在衰减随机噪声和保持滤波后的地震反射信号频率特性方面比TFPF具有更好的性能。
The varying-window-length time-frequency peak filtering (VWL-TFPF) is proposed in this paper to promote its ability of removing random noise and holding higher frequency component of non-linear signal. TFPF has good performance of removing random white noise and enhancing band-limited deterministic signal, but it maybe distort the waveform of complex nonlinear signal with various dominant frequencies, such as seismic signal, when it remove the random noise. PWVD should be used to ensure the linear IF condition of TFP, thus the windowing length is important to remove random noise and to preserve the waveform of signal. In this paper, the relationship between window-length, sampled frequency and dominant frequency of signal is analyzed. According to the relationship, VWL-TFPF method chose different time-window-length at different time section of signal to resolve the distortion of high frequency components resulted from unsuitable window length of TFPF. This method don¿t need design the frequency band of filter and little prior condition of signal. Testing of this method is made on synthetic data and common shot point seismic data. The results show that VWL-TFPF technique has better performance on attenuating random noise and holding frequency character of filtered seismic reflected signal than TFPF.