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针对微地震资料的信噪比低,无法清晰识别P波和S波的问题,根据微地震信号具有随机性、非平稳性的特点,研究了基于同步压缩变换(synchrosqueezing transform,SST)微地震弱信号提取方法。首先利用SST对信号进行自适应阈值去噪,然后在有效信号的频率中心附近进行SST系数的积分抽取,再利用抽取的有效信号进行SST重构实现弱信号的提取。应用于合成的含不同强度噪声的非平稳信号模型以及实际微地震单道记录的处理结果表明,该方法具有较好的抗噪能力和较高的信号提取精度。将该方法应用于实际井中微地震数据的试处理和分析,并与常规低通滤波结果进行了对比,表明该方法能够较好地将弱有效信号从噪声中提取出来,具有较好的实用价值。
In view of the low signal-to-noise ratio of microseismic data, the problem of P-wave and S-wave can not be clearly identified. Based on the characteristics of microseismic signal being stochastic and non-stationary, microseismic weakening based on synchrosqueezing transform (SST) Signal extraction method. Firstly, SST is used to adaptively de-noisy the signal, and then the SST coefficients are integrated and extracted around the frequency center of the effective signal. SST reconstruction is performed using the extracted effective signal to extract the weak signal. The results show that this method has good noise immunity and high signal extraction accuracy. The method is applied to the trial processing and analysis of microseismic data in real wells and compared with the results of conventional low-pass filtering. It shows that the proposed method can extract weakly effective signals from noise well and has good practical value .