Geological Carbon Storage

Geological carbon storage (GCS) aims to safely and permanently sequester CO₂ underground, mitigating climate change. Current research heavily emphasizes developing efficient machine learning models, such as Fourier Neural Operators, DeepONets, and recurrent U-Nets, to accelerate simulations, improve data assimilation (integrating diverse data like seismic and well measurements), and optimize well placement and injection strategies. These advancements are crucial for reducing uncertainties associated with GCS, enabling better risk assessment, and facilitating the widespread deployment of this crucial carbon mitigation technology. The resulting improvements in prediction accuracy and computational efficiency are vital for making GCS a more viable and reliable climate solution.