A Developed Robust Model And Artificial Intelligence Techniques To Predict Drilling Fluid Density And Equivalent Circulation Density In Real-time For Drilling Efficiency Optimization

Prediction Of Stuck Pipe Events Using Artificial Intelligence

How Complex Lithology Schemes Affect Drilling Rate Prediction: Machine Learning Study

A Hybrid Data-driven Approach To Estimate The Least Principal Stresses And Safe Mud Window Using Petrophysical Logging Data

Cost-effective In-situ Estimation Of Rock Properties Using Drilling Data

A New Automated Carrying Capacity Index Model Optimizes Hole Cleaning Efficiency And Rate Of Penetration By Applying Machine Learning Technique

Application Of Machine Learning To Predict Well Path Deviation For Enhanced Drilling Efficiency

Advanced Lwd Technologies Complemented With Deep Learning