自适应预测反褶积

ADAPTIVE PREDICTIVE DECONVOLUTION

本文提出的反褶积方法是对常规最小平方反褶积的一种改进。这种反褶积方法首先要确定非零反射系数点的位置,即将地震信号分成可预测点和不可预测点两类,然后求取预测滤波器,使预测误差在可预测点上达到最小,从而得到反褶积结果。文中首次提出位置反褶积方法,即由已知非零反射系数点的位置,准确求得反射系数数值的方法;并且给出了一种自适应迭代算法来逐步确定可预测点和不可预测点,从而确定非零反射系数点的方法。理论模型试验表明,本方法适用于非白噪的反射系数序列及各种不同相位的子波。

The deconvolution technique present in this paper is referred to a modification of the conventional least-square one, which normally begins with the determination of the locations where non-zero reflection coefficients lie. In practice, seismic data are categorized into two types according to which type of points, predictable or unpredictable, they are subordinate to. A predictive filter is then defined to make predicted errors minimun at the predictable points. In this way, the deconvolution process is completed. This paper pioneers the so-called ' Location Deconvolution' by which reflection coefficients are correctly defined once the non-zero reflection coefficient locations are given. An adaptive iterative algorithm is also presented to succcsivcly estimate the predictable and unpredictable points for seismic data so as to determine the locations where non-zero reflection coefficients lie. The experiments on a thcoritical model show that the technique is suitable for non-white reflectivity sequences as well as the wavelets with various phases. The results from real data further confirm its effectiveness.