Day 10-The Hidden Climate Solution Underground: AI for CO₂-EOR and Carbon Storage

Carbon capture and geological storage are becoming essential technologies for reducing CO₂ emissions. But predicting how CO₂ moves underground is difficult because reservoirs are complex, heterogeneous, and uncertain. In this video, we will explore how machine learning and deep learning can accelerate reservoir simulation for CO₂-EOR and carbon storage in the SACROC carbonate field. The video covers the motivation for CCUS, geological complexity, reservoir simulation workflow, Random Forest, Gradient Boosting, XGBoost, 3D-CNN, saturation-map prediction, feature importance, and future directions such as physics-informed deep learning and uncertainty quantification. This video is designed for students, researchers, engineers, and anyone interested in AI for geoenergy, carbon capture and storage, enhanced oil recovery, and subsurface digital twins. #CarbonCapture #CCUS #MachineLearning #DeepLearning #ReservoirSimulation #Geoenergy #CO2Storage #EnhancedOilRecovery #ArtificialIntelligence #ClimateTechnology #SubsurfaceEnergy