分级特征提取在中子寿命深度校正中的应用

Hierarchical Feature Extraction in the Application of Neutron Lifetime Depth Correction

随着油田进入开发中后期,中子寿命测井得到了广泛的应用.针对中子寿命测井曲线存在的深度误差,对两条测量不同地层信息的曲线进行对比校正,利用测井曲线顺序性的特点,对测井曲线进行分级特征提取并进行校正,提出了基于分级特征提取的测井曲线校正的方法.借鉴人工视觉校正的经验,利用曲线段的最大值位置、尖峰数目这两个特征先对曲线段进行分类匹配,然后利用最大值上下厚度比、相对斜率这两个特征进行相似性判断最终实现分级特征提取.实验结果表明该方法能够快速有效的对测井曲线进行校正.

Neutron lifetime logging has been widely used, as the oilfield enters the mid and late development. Aiming at the existence of neutron lifetime logging curve depth error, contrast correction curve of two different stratigraphic information, and take advantage of the characteristics of logging curve sequential, for logging curve of hierarchical feature extraction and calibration. Logging curve correction method is presented based on the hierarchical feature extraction. Using the maximum position, spike number to match and categorize, and then using the maximum thickness ratio, and relative slope characteristics of the curve segment to judge similarity, and Finally realize the hierarchical feature extraction, these all based on the experience of the artificial vision correction. The experimental results show that the method can quickly and efficiently correct the logging curves.