Energy Transition: Data Science and Engineering Analytics in CCUS, Renewable Geothermal and LNG Applications
Tuesday, 21 October
Room 332AD
Technical Session
This technical session highlights several energy transition explorations with data science and engineering analytics. The coverage of the topics includes: 1) carbon storage and utilization for screening, pressure, and plume tracking, EOR, and uncertainty analysis with advanced machine learnings. 2) renewable energy of geothermal studies for fracture network quantification and thermal/heat behaviors in use cases with various of the machine learning techniques. 3) Oil & LNG markets studies with machine learning for trading dynamics. Encourage you join the session to catch up such innovative data science and engineering analytics applications, energy transition trends, and use cases.
Session Chairpersons
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0830-0855 228266Quantifying the Uncertainty of the 3D Evolution of CO2Mass and Pressure Plumes for Site Screening Applications with Fourier Neural Operators
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0855-0920 227900CO2-Brine Gravity-Driven Displacement Estimation Using Numerical Methods and Deep Learning
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0920-0945 228102Do We Really Need Hundreds of Machine Learning Models in Industry?
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1015-1040 227866Real Time CO2 Plume Monitoring and Visualization Considering Geologic Uncertainty at the Illinois Basin-Decatur Carbon Sequestration Project
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1040-1105 227935Deep Learning Driven Reservoir Simulation for Mapping Performance of Co2-EOR and Storage in Tight Oil Reservoir
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1105-1130 227883Knowledge-Guided Machine Learning for Optimizing Thermally Stable Cement Formulations in Co₂ Storage and Geothermal Wells
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Alternate 228167Leveraging Artificial Intelligence for Field-Scale Thermal Conductivity Prediction in the UTAH FORGE Geothermal System
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Alternate 228121Virtual Barrels, Real Markets: Bridging Physical & Financial Trading in Oil & LNG Markets Through System Dynamics & Machine Learning