Unsupervised Electrofacies Classification and Porosity Characterization in the Offshore Keta Basin Using Wireline Logs

This study applies an unsupervised machine learning workflow, specifically K-means clustering, for electrofacies analysis and porosity characterization in offshore basin wireline log data. The methodology identified four distinct electrofacies with moderate separation, providing a robust log-only approach for geological interpretation where core data is scarce.