摘要
斜度和峰度作为非对称和非高斯分布时间序列的两个重要度量参数,分别反映了信号分布偏离对称分布的歪斜程度(对称性)和信号分布的集中程度(高斯性)。相对于常规地震资料,微地震资料的信号能量较弱,信噪比极低,若直接采用常规资料处理方法对其进行处理,往往得不到微地震有效信号。为此,提出了一种改进的时变斜度峰度法用于识别强干扰背景下较弱的微地震有效信号。首先求取局部微地震资料在不同长度滑动时窗内的时变斜度或峰度,然后对长、短时窗内的时变斜度或峰度求差,其差值极大值对应的位置就是微地震有效信号的位置。理论模型和实际资料的处理分析结果表明,改进的时变斜度峰度法能较好地消除噪声的非对称性或非高斯性影响,突出微地震有效信号。
As the two important metric parameters of non-Gaussian and asymmetrical distribution time series,skewness and kurtosis represent deviation degree from symmetrical distribution(symmetry) and distribution concentration(Gaussian) of the signal distribution respectively.Compared with conventional seismic data,the energy of microseismic signals are weak,and SNR is extremely low,it is difficult to get effective microseismic signals by using conventional signal processing methods directly.In view of this,an improved time-varying skewness and kurtosis method was proposed according to the characteristics of microseismic signals,which can be used to identify effective microseismic signals in strong interference background.Firstly,the time-varying skewness or the kurtosis for local seismic data is obtained in different length sliding windows.Then,the difference of time-varying skewness or kurtosis is achieved in the long-window and the short-window,and the maximum difference values are corresponding to the location of the effective microseismic signals.The analysis of the theoretical model and actual data showed that the improved time-varying skewness and kurtosis method can well eliminate the impact of asymmetry or non gaussian of noise and highlight effective microseismic signals.
出处
《石油物探》
EI
CSCD
北大核心
2012年第6期625-632,537-538,共8页
Geophysical Prospecting For Petroleum
基金
中国石油天然气集团公司科学研究与技术开发项目(2011A-3605)
复杂山地弯线采集优化设计与地震有色反演方法研究项目(2011B-3706)共同资助
关键词
微地震
高阶累积量
斜度
峰度
microseismic
higher-order statistics
skewness
kurtosis
