Lithofacies classification using well log data from the Hugoton and Panoma Fields dataset. This project implements various machine learning algorithms including Support Vector Machines, Random Forest, Neural Networks, and others to predict facies groups. The study focuses on improving facies classification accuracy using well log data from 9 well.

Lithofacies classification is the process of identifying the rock type present at a point in an oil well, based on its properties, known as well logs. This is an end-to-end machine learning project for lithofacies classification using Random Forest models.