Research
120d agoUnsupervised ML Maps Ghana's Keta Basin
Researchers analyzed 11,195 wireline log samples from the Keta Basin using K-means clustering. The workflow identified four distinct electrofacies with a 0.50 average silhouette coefficient. This unsupervised approach characterizes porosity and clay content where core data are scarce.
The Signal
It provides a scalable template for geological mapping in data-poor offshore environments.