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相干体方法常被用于刻画地震数据的不连续性和非均质性,但相干体方法若使用线性相关系数度量两个随机变量(即两个地震道)之间的关系,由于随机变量的关系是非线性的,用线性相关系数度量描述非线性关系,根据数学定义,存在一定的局限性。为了能更准确度量地震道波形之间的相似性),本文提出一种基于Kendall一致性度量算法,克服线性相关系数度量存在一定的局限性。本文的重点是研究线性相关系数度量和一致性度量对波形相似性变化的敏感性,我们设计了两个数值模型测试这两种度量对波形相似性变化的敏感性,发现Kendall一致性度量对波形的变化比线性相关系数度量更敏感,可用于精细刻画波形的变化,并结合信息散度度量可更精细刻画地层非均质性方法,我们将其应用处理实际的地震资料数据,表明该方法不但有效并具有较高的分辨率。
The coherence method is often used to characterize the discontinuity and heterogeneity of seismic data. However, if the coherence method measures the relationship between two random variables (ie, two seismic traces) using the linear correlation coefficient, The relationship is non-linear. Using the linear correlation coefficient to describe the nonlinear relationship, according to the mathematical definition, there are some limitations. In order to more accurately measure the similarity between the seismic traces, this paper presents a Kendall based on the consistency measurement algorithm to overcome the linear correlation coefficient measurement has some limitations. The focus of this paper is to study the sensitivity of the linear correlation coefficient measure and the consistency measure to the variation of the waveform similarity. We design two numerical models to test the sensitivity of these two measures to the variation of the waveform similarity. We find that the Kendall consistency measure Is more sensitive than the linear correlation coefficient measure, which can be used to finely describe the waveform changes. Combined with the information divergence measure, the formation heterogeneity can be described more finely. We apply this data to the actual seismic data, which shows that this method not only Effective and with higher resolution.