Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based On Well Log Data

Abstract

Facies classification is the process of identifying rock lithology based on indirect measurements such as well log measurements. The facies classified manually by experienced geologists, so it takes a long time and is less efficient. Machine learning applications in facies classification can increase the effectiveness and efficiency of geophysical interpretation on complex data. The purpose of this study is to examine the application of machine learning algorithms SVM and KNN in facies estimation. The results showed that the KNN algorithm is better at estimating facies than the SVM algorithm.