Codes on Carbon Capture Utilisation and Storage with the use of Machine Learinng
This repository contains machine learning models applied to optimize various processes in CCUS, including site selection, lithology classification, and CO2 plume monitoring. The codebase leverages algorithms such as Random Forest, Neural Networks, and Support Vector Machines to enhance data-driven decision-making in carbon storage. Explore the examples to understand how machine learning can be integrated with geophysical and subsurface datasets for efficient carbon management.