A Second-order Squeezed Wavelet Transform Algorithm for Seismic Signal Analysis
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摘要: 地震信号分析在地质岩性、储层、流体、沉积相带的检测，以及地层界面识别与储层分析、地震资料处理和解释等方面具有重要研究意义。针对现有时频分析算法在处理地震信号时，存在时频分辨率低、能量聚集性差等问题，该文以Ricker子波为数学模型，提出了一种新的2阶挤压小波变换算法(SWT2)。考虑到传统时频同步压缩变换中的瞬时频率估计对地震信号失效，利用改进的母小波对地震信号进行匹配，进而通过谱峰对齐对参考频率进行修正，从而提升时频能量聚集性和时频分辨率。仿真实验结果表明，提出的2阶挤压小波变换算法可以极大地提升地震信号的时频聚集性，精确地反映信号的时延和主频，对地层结构的刻画更加精确。Abstract: Seismic signal is of great significance in the detection of geological lithology, reservoir, fluid and sedimentary facies, as well as the identification of stratigraphic interface, reservoir analysis, seismic data processing and interpretation. In view of the problems of low time-frequency resolution and poor energy aggregation when the traditional time-frequency analysis algorithms process seismic signals, a new 2nd-order Synchrosqueezing Wavelet Transform (SWT2) algorithm is proposed based on the model of Ricker wavelet. The proposed second-order squeezing algorithm uses the improved mother wavelet to match the seismic signals, and then corrects the reference frequency through spectral peak alignment, thus improving the time-frequency energy concentration and time-frequency resolution. Simulation results show that the proposed method can greatly improve the time-frequency aggregation, accurately reflect the time delay and dominant frequency of signals, and describe the stratigraphic structure more accurately.
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Key words:
- Signal processing /
- Seismic signal /
- Synchrosqueezing transform /
- Spectral decomposition
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表 1 各种时频分析方法的瑞利熵对比
时频分布 STFT WVD 伪WVD CWT SST SST2 改进CWT SWT SWT2 瑞利熵 24.7226 24.4484 24.0051 28.6346 17.6892 16.5572 28.5278 17.6841 16.0846 
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