Technical Session 46: Physics-informed and Hybrid AI for Drilling and Operations
Friday, 26 March
Lotus Suite 3-4, Level 22
Technical Session
-
1400-1430 25362High-precision Fault Prediction Technology Based On Extreme Value Probability Constraint And Self-attention Mechanism
-
1430-1500 25316Advancing Well Construction Automation With Physics-informed AI For Stuck-pipe Avoidance
-
1500-1530 25396Physics-informed Surrogate Modeling Workflow For Multiphase Flow Behavior Prediction In Wellbore
-
Alternate 25650Physics-informed Graph Neural Network Surrogate Coupled With Deep Reinforcement Learning For Real-time Reservoir Production Optimization
-
Alternate 25385Physics-informed Graph Learning For Cross-well PDC Bit Wear Diagnosis: Coupling Bit Structure With Operating Dynamics
-
Alternate 25602Real-time Formation Drillability Characterization: A Physics-informed And Interpretable Machine Learning Approach
-
Alternate 25558Dynamic Package Control: Physics-based Digital Twins And Edge Control To Enhance Well Deliverability And Optimize Runtime, Utilization And Emissions Performance
-
Alternate 25533Physics-conditioned Synthetic Reservoir Data At Scale: A Theta-conditioned Generative Engine For Cognitive Reservoir-management Suite Development
