R. Ahmed

Enhancing Drilling Performance Using Real-Time Machine Learning Models: A Framework for Predicting Formation Transitions During Drilling Operations

Accurate real-time identification of formation transitions is essential for improving drilling efficiency and reducing nonproductive time, particularly in geologically complex environments. Accurate estimates of sonic and bulk density logs are crucial inputs for subsurface formation identification; however, acquiring...