This project integrates conventional and image well logs for lithofacies classification using tree-based machine learning models, including Random Forest and Extremely Randomized Trees.
-
Updated
Jul 5, 2025 - Jupyter Notebook
This project integrates conventional and image well logs for lithofacies classification using tree-based machine learning models, including Random Forest and Extremely Randomized Trees.
Tools for plotting and analyzing stratigraphic data in R
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.
Lithofacies and temporal variation predict composition of Siluro-Devonian vertebrate, invertebrate, and plant communities
To associate your repository with the lithofacies topic, visit your repo's landing page and select "manage topics."