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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。
The minimum entropy deconvolution (MED) is mainly used to extract the most detailed reflection information from the amplitude anomalies of reflected seismic records. Interpreting the reflected information requires accurate compensation for the complex effects of source wavelet and formation filtering. Minimal entropy deconvolution is essentially equivalent to solving the problem of finding a linear operator that maximizes the properties of the spikes in the gathers of our choice. Unlike predictive deconvolution, minimum entropy deconvolution does not require any assumptions about the phase characteristics of the seismic wavelet and does not require the reflection sequence to be a white noise sequence - in fact, this assumption is absolutely dominant for “bright spots” Short time window, there is no practical significance. The minimum entropy deconvolution mainly lies in finding the minimum number of large spikes consistent with the actual data rather than looking for whitened data. An example of the synthetic data shows that efficient operators can be determined by the method of minimum entropy deconvolution based on the very small time difference between non-superimposed channel events. During the enhancement of the output apex pulse, the minimum entropy deconvolution operator will selectively suppress those frequencies where the ratio of the coherent signal to the random interference is low. For reflective areas where there are bright spots, the performance of this suppression interference makes the non-superimposed output track particularly suitable for analyzing various variations related to offset.