Comparison Of Facies Estimation Of Well Log Data Using Machine Learning

Abstract

Facies classification is the process of identifying rock lithology based on indirect measurements such as well log measurements. The facies classification process is done manually by experienced geologists, which is time-consuming and inefficient. The application of machine learning in facies classification can improve the effectiveness and efficiency of geophysical interpretation on complex data. The purpose of this research is to study the application of SVM and KNN machine learning algorithms in facies estimation. The algorithm in this study uses the phyton programming language. The results show that the KNN algorithm is better at estimating facies than the SVM algorithm.