AI-Driven Reservoir Modeling & Optimization
Wednesday, 21 October
Room 370 ADBE
Technical Session
This session highlights the latest advances in artificial intelligence and machine learning for reservoir modeling and optimization, including physics-informed approaches, thermodynamic property prediction, data-driven forecasting, and integrated subsurface–surface workflows. Contributions demonstrate how autonomous and intelligent systems can enhance decision-making, improve prediction accuracy, and enable more efficient reservoir management across a range of applications, from geosteering to CO2 EOR and field-scale production optimization.
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1400-1425 234123A Sequential Decision Framework for Geosteering: Trajectory Selection using Reinforcement Learning and Multi-Objective Optimization
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1425-1450 233993Data Analytic Coupled Machine Learning Applications for Active Reservoir Management: CO2-EOR Use Case
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1450-1515 234206AI-Driven Reservoir Modeling For Field-Scale Production Optimization In A Mature Offshore Oil Field: A Gulf of Suez Case Study
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1545-1610 233918A Two-Token Physics-Constrained Transformer and Gray-Box Correlation for CO2 Solubility Prediction in Ionic Liquids Without IL-Specific Calibration
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1610-1635 233852Scaling the Expert Eye: Automating Subsurface Model Evaluation and Tuning via Reservoir Engineering Inspired AI Agents
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1635-1700 234136A Conversational User Interface For Autonomous Reservoir Simulation Deck Generation And Execution
