α稳定分布地震信号特征指数估计方法  

α-Stable Distribution Seismic Signal Characteristic Exponent Estimation

作　　者：岳碧波[1] 彭真明[1] 张启衡[2] 

机构地区：[1]电子科技大学光电信息学院,成都610054 [2]中国科学院光电技术研究所,成都610209

出　　处：《吉林大学学报（地球科学版）》2013年第6期2026-2034,共9页Journal of Jilin University：Earth Science Edition

基　　金：国家自然科学基金项目(41274127;40874066;40839905);中央高校基本科研业务费专项资金(ZYGX2011YB021)

摘　　要：地震信号通常都被认为是服从高斯分布的。研究了实际地震信号的动态样本方差特征,假定地震信号是服从非高斯α稳定分布的。对于非高斯α稳定分布地震信号,其特征指数的取值大小表征了信号的脉冲强度,对地震信号去噪、阻抗反演等处理算法范数的选取起到了重要作用;当算法选取的范数大于特征指数时,将有可能得不到预期的结果。采用基于分数低阶统计量的α稳定分布特征指数计算方法,并结合粒子群优化算法,估计出了实际地震数据的特征指数最大为1.930 1。研究表明,实际地震数据的脉冲性强于高斯分布,其特征指数小于高斯分布的特征指数2。因此,将实际地震数据的统计分布假设为非高斯α稳定分布比假设为高斯分布更合理。It was assumed that seismic signals follow Gaussian distribution. After analyzing the dynamic sample variance of real seismic data, the authors proposed that seismic data obeys non-Gaussian a stable distribution. In the applications of non-Gaussian a-stable distribution seismic signal processing, such as noise suppressing and seismic impedance inversion, characteristic exponent is a key parameter; And if the norm greater than characteristic exponent, misleading results will be produced. Combining with particle swarm optimization algorithm, a-stable distribution characteristic exponent estimation method based on fractional lower order moments was applied to real seismic data and the characteristic exponent of real seismic data was obtained. The work of this paper shows that the pulse characteristic in real seismic data are stronger than that in Gaussian distribution; The proposition that real seismic data follow non-Gaussian a-stable distribution is reasonable; The calculation of real seismic data character exponent is also helpful to the selection of seismic signal processing algorithm.

关 键 词：非高斯 Α稳定分布 特征指数 信号处理 

分 类 号：P631.4[天文地球—地质矿产勘探]