Automated lithology classification employing whole core CT scans

PhD candidate, kurdistan Chawshin

Main Supervisor, Kenneth Duffaut

Sponsor: Equinor

This project aims at developing automated routines and workflows for lithology classification and estimation of transport properties. The main objectives of this project can be summarized as below: 

• Enhance current utilization of whole core CT images in rock characterization workflows 
• Rock typing based on automated image analysis routines 
• Explore the application of machine learning algorithms to classify lithology 
• Explore the application of machine learning algorithms to estimate transport properties such as porosity, permeability and water saturation based on the underlying lithology classification 

Project result: Workflows to classify lithology using 2D and 3D CT images
Convolutional Neural Networks-based workflows for high-resolution classification of lithology and porosity