基于小波分解与Akaike信息准则的微地震初至拾取方法
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摘要
微地震震源的定位要求精确确定初至,人工拾取微地震有效事件需要很大的工作量。首先讨论了Akaike信息准则(AIC)初至拾取方法;然后根据微地震信号在相邻小波尺度上连续的特点,将基于AIC的初至拾取方法与小波多尺度分析方法相结合,对微地震资料进行多尺度分析;最后利用AIC拾取初至,并根据初至的分布特点确定地震记录中是否存在有效的微地震事件。克服了传统AIC法由于噪声影响使初至点模糊而难以准确拾取的缺点。模型与实际资料的应用表明,基于小波分解与AIC相结合的初至拾取方法能够从信噪比低的资料中较准确地识别出有效微地震事件。
Positioning of microseismic source requires accurate first-break picking-up,and manually identifying effective microseismic event costs plenty of time.Firstly,we discussed the first-break picking-up method on the basis of Akaike information criteria(AIC).Then, according to the continuous characteristics of microseismic signal over neighbouring wavelet scale,the first-break picking-up based on AIC was combined with wavelet multi-scale analysis to carry out multi-scale analysis on microseismic data.Finally,AIC was used to pick up first break,and the distribution of first break was analyzed to identify whether existing effective microseismic event or not in seismic record.When using traditional AIC,the first-break points are obscure because of the impact of noise,so the first break cannot be accurately picked up,our method overcomes the shortcoming. Model and actual data application results indicate that the first-break picking-up method based on wavelet decomposition and AIC can relatively accurately pick up effective microseismic event.
Positioning of microseismic source requires accurate first-break picking-up,and manually identifying effective microseismic event costs plenty of time.Firstly,we discussed the first-break picking-up method on the basis of Akaike information criteria(AIC).Then, according to the continuous characteristics of microseismic signal over neighbouring wavelet scale,the first-break picking-up based on AIC was combined with wavelet multi-scale analysis to carry out multi-scale analysis on microseismic data.Finally,AIC was used to pick up first break,and the distribution of first break was analyzed to identify whether existing effective microseismic event or not in seismic record.When using traditional AIC,the first-break points are obscure because of the impact of noise,so the first break cannot be accurately picked up,our method overcomes the shortcoming. Model and actual data application results indicate that the first-break picking-up method based on wavelet decomposition and AIC can relatively accurately pick up effective microseismic event.
引文
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[2]宋维琪,孙英杰,朱卫星.微地震资料频域相干一时间域偏振滤波方法[J].石油地球物理勘探,2008, 43(2):161-167
[3]周彦文,刘希强.初至震相自动识别方法研究与发展趋势[J].华北地震科学,2007,25(4):18-21
[4]刘希强,周彦文,曲均浩,等.应用单台垂向记录进行区域地震事件实时检测和直达P波初至自动识别[J].地震学报,2009,31(3):260-271
[5]陈爱萍,邹文,何光明,等.基于分维和相关性的自动初至拾取技术及应用[J].物探化探计算技术,2009, 31(2):100-107
[6]Tetsuo T,Genshiro K.Estimation of arrival of seismic waves by multivariate time series model[J].Annals of the Institute of Statistical Mathematics, 1991,43(3):407-433
[7]Maeda N.A method for reading and checking phase times in autoprocessing system of seismic wave data [J].Zisin,1985,38(3):365-379
[8]Zhang H J,Thurber C,Rowe C.Automatic P-wave arrival detection and picking with multiscale wavelet analysis for single-component recording[J].Bulletin of the Seismological Soiciety of America,2003, 93(5):1904-1912
[9]景占荣,羊彦.信号检测与估计[M].北京:化学工业出版社,2004:333-334
[10]Sleeman R,Van Eck T.Robust automatic seismic Pphase picking:an on-line implementation in analysis of broadband seismogram recording[J].Physic of the Earth and Planetary Interiors,1999,113(1):265- 275
[11]王海军,靳平,刘忠贵,等.区域震相初至估计[J].西北地震学报,2003,25(4):298-303
[12]皇甫堪,陈建文,楼生强.现代数字信号处理[M].北京:电子工业出版社,2003:26-35,340-345
[13]韩世勤,张玉芬.小波变换及其在信号分析中的应用[J].中南民族学院学报,1996,15(4):86-91
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