摘要
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。
It is very difficult to clearly identify the P-wave and S^wave due to the low SNR of microseismic data. According to the characteristics of randomness and non-stationary of microseismic signals, we proposed a method to extract the weak signal from microseismic data based on synchrosqueezing transform （SST）. Firstly, we utilize the SST to conduct the adaptive threshold denoising. Then, the SST coefficients are extracted near the center frequency of effective signal by integrating. Fi- naliy, we carry out the SST reconstruction using the extracted effective signal SST coefficients to implement the weak signal extractiorL The test results of the synthesis non-stationary signal models with different noise intensity and the actual micro- seismic single-channel record show that this method has better noise immunity and higher signal extraction accuracy. Through the processing and analysis of the actual borehole mieroseismic data and the comparison with conventional low-pass filtering, the proposed method has good capability and is better to extract the weak effective signal from the noise.
出处
《石油物探》
EI
CSCD
北大核心
2016年第1期60-66,90,共8页
Geophysical Prospecting For Petroleum
基金
国家高技术研究发展计划(863计划)(2011AA060303)项目资助~~
关键词
微地震
同步压缩变换
弱信号提取
自适应阈值去噪
microseismic, synchrosqueezing transform, weak signal extraction, adaptive threshold denoising
