基于峭度最大化的地震盲反褶积方法  

A seismic blind deconvolution method based on kurtosis maximization criterion

作　　者：蔡连芳 田学民[1] 

机构地区：[1]中国石油大学(华东)信息与控制工程学院,山东青岛266580

出　　处：《石油物探》2012年第1期30-36,111-112,共7页Geophysical Prospecting For Petroleum

基　　金：国家高技术研究发展计划(863)项目(2007AA04Z193);山东省自然科学基金项目(Y2007G49)共同资助

摘　　要：从地震褶积与反褶积过程的等效总系统出发,使脉冲响应满足单位脉冲序列形式,导出方差约束下反褶积输出的峭度最大化准则,作为地震盲反褶积的目标函数;针对目标函数关于反褶积算子的优化问题,采用粒子群算法进行全局寻优操作,实现地震信号的反褶积。数值模拟和实际资料处理结果表明,该方法不但适用于最小相位子波的反褶积,而且适用于混合相位子波的反褶积。与梯度法优化峭度准则的反褶积结果相比,能够更好地从地震记录中估计反射系数,拓宽地震资料的频谱,提高地震资料的分辨率。From the perspective of the equivalent overall system generated from the seismic convolution and deconvolution,a maximum kurtosis criterion of deconvolution output with the constraint of variance is derived as objective function of seismic blind deconvolution by making the impulse response in the form of unit impulse sequence.Aiming at optimizing the deconvolution operator of objective function,Particle Swarm Optimization(PSO)was applied to proceed a global search for deconvolution operator in order to realize deconvolution of seismic data.The results of numerical simulation and actual seismic data processing prove that,the method proposed in this paper can be suitable for minimum phase wavelet deconvolution and for mixed phase wavelet deconvolution.In contrast to the deconvolution results of gradient method with optimizing kurtosis criterion,the proposed method can obtain a better estimation of reflectivity from the seismic data,and broaden the spectrum of seismic data more effectively resulting in higher resolution of seismic data.

关 键 词：地震盲反褶积 峭度 反褶积算子 粒子群算法 混合相位子波 

分 类 号：P631.4[天文地球—地质矿产勘探]