【摘要】 地震震相初至拾取的准确性对地震事件判别及震源的定位工作有着重要影响。已有的初至拾取方法对低信噪比的地震资料的拾取效果并不理想,为了解决噪声问题(提高抗噪性能),提出了一种基于改进能量比法和小波变换的微震初至自动拾取方法,即首先将特征函数引入到传统能量比及小波变换中,通过改进的能量比算法搜索出P波的初至范围;然后采用小波变换精确定位P波的初至时刻;最后采用地震模型数据和实测地震数据进行试验。结果表明,基于特征函数的能量比和小波变换的拾取方法具有抗噪性强、稳定性好等优点,能从信噪比较低的地震资料中较为准确地识别出P波的初至时刻。更多还原

【Abstract】 The first-break picking accuracy greatly affects the seismic events discriminant and source localization. At present,none of the first-break picking algorithms proposed is ideal to collect the low SNR seismic data. In order to solve the noise problem( improve noise resistance performance),an improved first arrival picking method of micro-seismic event based on power ration and wavelet transform is proposed. Firstly,the characteristics function is introduced to the traditional energy ratio method wavelet transform method so as to search the range of the P-wave first break by adopting the improved energy ratio method. Then,the first break time of P-wave is positioned precisely by using wavelet transform. Finally,the seismic model data and actual measured seismic data are used to conduct experiment to analyze the performance of the method proposed in this paper. The results show that,the method based on energy ratio and wavelet transform is the first-break automatic picking method with the characteristics of noise resistance and stability. Besides that,it can identify the P-wave first arrival time from the data with a low signal to noise ratio accurately.更多还原