A Master's Thesis at the University of Basrah Examines the Prediction of Reservoir Rock Permeability Using Conventional Borehole Logs and Deep Learning

A Master's Thesis at the University of Basrah Examines the Prediction of Reservoir Rock Permeability Using Conventional Borehole Logs and Deep Learning

A master's thesis from the College of Science at the University of Basrah was titled "Predicting Reservoir Rock Permeability Using Conventional Borehole Logs and Nuclear Magnetic Resonance Using Machine Learning and Deep Learning Using Python: A Case Study of a Clastic Reservoir in Southern Iraq."

The thesis, presented by student Ali Zuhair Abdullah, included the estimation of permeability using conventional methods based on empirical equations, in addition to methods based on machine learning and deep learning techniques.

The thesis recommends the application of machine learning and deep learning models to carbonate formations to evaluate the accuracy and reliability of these models in predicting permeability across diverse geological contexts.

Department of Media and Government Communication