一种新的混合相位反褶积方法

在地震资料处理中,常用预测反褶积方法提高地震资料的分辨率,它具有两个基本的假设条件:①地震子波是最小相位;②反射系数序列是随机过程。上述假设条件与实际地震子波的混合相位存在较大差别。为此,笔者在借鉴前人研究的基础上,提出了一种新的混合相位反褶积方法。其实现过程为:①根据地震记录的自相关和地震子波自相关之间的关系,由最小二乘法拟合出地震子波的振幅谱,进而计算出地震子波的自相关;②利用计算出来的地震子波自相关设计一个最小相位滤波器,然后加一个延迟量于自相关函数的主对角线上,将最小相位反滤波器分解为一个长度很短的滤波器,再与一个长度较长的滤波器进行褶积,可得到一系列的混合相位子波和混合相位滤波器;③将得到的混合相位滤波器和原始地震道进行褶积,选取一定的判别准则,以选出最佳的混合相位滤波器以及相应的混合相位子波。通过模型试算和实际资料处理可知,分时窗反褶积的效果要好于单时窗反褶积,混合相位反褶积效果好于最小相位反褶积。在分时窗求取地震子波时,为了得到更好的反褶积效果,要注意时窗宽度与算子长度之间的关系。

A new mixed phase deconvelotion method.

The common predicted deconvolution can improve the resolution of seismic data in seismic data processing under the precondition of two basic hypotheses: (1)seismic wavelet is minimum phase; (2) reflectivity sequence is random process. There is large difference between above hypotheses and real seismic wavelets. For that reason, the authors presented a new mixed phase deconvolution on the basis of the predecessors studied. The implemented process is as follows:(1)the amplitude spectrum of seismic wavelet is fitted by least square method according to the relationship between the autocorrelation of seismic records and autocorrelation of seismic wavelet, and then the autocorrelation of seismic wavelet is further computed; (2)designing a minimum phase filter by using computed autocorrelation of seismic wavelet, then adding a delay to dominant diagonal of autocorrelation function, decomposing a minimum phase filter into short filter and convoluting with a longer filter, which resulted in series of mixed phase wavelets and mixed phase filter; (3)convoluting the resulted mixed phase filter with raw seismic traces and selecting a certain judging rule to choose a optimal mixed phase filter and associated mixed phase wavelet. It is known by model tests and real data processing that deconvolution in separate widows is better than in single window and mixed phase deconvolution is better than minimum phase deconvolution. It should pay attention to the relationship between the broadness of the window and length of operator when computing the seismic wavelet in separate windows in order to obtain better deconvolution results.