摘要
最小熵反褶积(简称MED)主要是用来从反射地震记录的振幅异常中提取尽可能详细的反射讯息,解释这些反射讯息需要对震源子波及地层滤波的复合效应作精确的补偿。最小熵反褶积实质上就相当于求解这样一个问题,这就是要找出一个线性算子,该算子能使我们所选用的道集中尖脉冲的特性能最大限度地得到加强。与预测反褶积不同,最小熵反褶积不需要对地震子波的相位特性作任何假定,也不需要假定反射序列是白噪序列——事实上,这种假定对于“亮点”占绝对优势的短时窗来说,是没有什么实际意义的。最小熵反褶积主要在于找出与实际资料相符的大尖脉冲的最小数目而不是去寻找白化资料。 合成资料的例子说明,可以根据未叠加道同相轴间非常微小的时差,利用最小熵反褶积的方法,确定出有效的算子。在使输出道尖脉冲得到加强的过程中,最小熵反褶积算子将有选择地对那些相干讯号与随机干扰的比率比较低的频率进行压制。对于存在亮点的反射区域来说,这种压制干扰的性能使未经叠加的输出道特别适合于用来分析与偏移距有关的各种变化。
Abstract
Minimum Entropy Deconvolution (MED-Western Geological Company of America Service Mark) was developed to aid the extraction of detailed reflectivity information from amplitude anomalies in reflection seismic recordings. Interpreting such reflectivity information depends on accurate compensation for the combined effects of the source wavelet and earth filtering. MED approaches this problem by finding a linear operator that maximizes the "spike-like" character of a representative set of traces. Uulike predictive deconvolution, the MED process makes no assumptions about the phase characteristics of the "seismic wavelet",nor does it assume that the reflection series is white-certainly a poor assumption over short-time windows where "bright spots" dominate. Rather than seeking to whiten data, the MED process seeks the smallest number of large spikes that is consistent with the data.Synthetic data examples show that the method can determine effective operators by exploiting quite small differential moveouts of events across unstacked traces. While maximizing the spikiness of output traces, the derived MED operator selectively suppresses frequencies over which the ratio of coherent signal to random noise is low. This noise suppression characteristic makes unstacked, output traces particularly suited for analysis of offset-dependent variations in reflectivity across bright spots.
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