In this work, a method for well log data classification is presented. The method relies on a coordinate transformation to restructure the data in an optimal way and a quasi-probabilistic interpolation technique capable of smoothing noisy data. The approach does not require case-specific design, is computationally efficient and provides a statistical characterization of the classification problem. Consequently, transition zones between facies can be modelled in a realistic fashion and intermediate rock types can be identified with ease. Apart from being capable of classifying unseen data with high accuracy, the technique can also be used as an informative quality and consistency assessment tool for manually classified data. The properties of the method are demonstrated on a realistic test case study.

在这项工作中，提出了一种测井数据分类的方法。该方法依赖于坐标变换以最佳方式重组数据，以及能够平滑噪声数据的准概率插值技术。该方法不需要特定于案例的设计，计算效率高，并且提供了分类问题的统计特征。因此，可以以现实的方式对相之间的过渡带建模，并且可以轻松识别中间岩石类型。除了能够对未见数据进行高精度分类外，该技术还可以用作手动分类数据的信息质量和一致性评估工具。该方法的特性在一个实际的测试案例研究中得到了证明。