高斯小波用于测井层序地层自动划分的研究

不同级别层序界面的识别是层序地层学研究的关键问题。在层序地层单元的分界面上，测井曲线表现为突变，而高斯小波对信号突变点具有敏感性和多尺度分析特性，因此测井数据的高斯小波变换能够表征这种突变。以胜坨油田某井为例，对自然电位测井数据进行高斯小波变换，将一维测井数据拓展为二维深度一尺度空间，使其内部的能量聚集与分布得以清晰展示。依据小波时频色谱信息和能量信息，选取识别不同级别层序地层界面的最佳尺度，获取最佳尺度下小波系数模极值的信息。结果表明，小波系数曲线模极值能反映地层岩性的变化，与各级层序界面具有较好的对应关系，从而可据其实现不同级别层序界面的划分。与岩性剖面相比，该方法可用来准确划分层序界面。这些探索为地层层序的自动划分提供了一种新的思路。

Application of Gauss wavelet to demarcate log stratigraphic sequence automatically.

The key to sequence stratigraphy analysis is to identify sequence boundaries of different levels.Due to the sensitivity of Guass wavelet to the flex points of the signal and the multi-scale analysis of the wavelet resolution,the abruptly changing points at the interface of stratigraphic sequence shown from the logging curve can be revealed clearly by Gauss wavelet transformation of logging data.Spontaneous potential(SP) logging curve from a well in Shengtuo Oilfield was processed by Gauss wavelet transformation.By this transformation,the logging data were expanded from 1-D depth space to 2-D depth-scale space,which makes the collection and distribution of its inner energy revealed clearly.The optimum scales corresponding to boundaries of stratigraphic sequence were determined by time-frequency chromatogram and energy information.On the basis of the scales,the information on the modulus of wavelet coefficient was obtained.The modulus maxima of wavelet coefficient were found to reflect the lithology and to correspond to the stratigraphic sequence of different level,and therefore realizing the clarification of stratigraphic sequence automatically.Compared with the lithological profile,this method can be applied to detect sequence boundaries quantitatively and correctly.All these researches provide a completely new and effective method for demarcating sequence.