安全なCCSに向けた連続モニタリング・モデリング技術

抄録

Continuous monitoring of stored CO₂ is strongly required to achieve safe and effective CCS. We first introduce our recent studies focused on developing a continuous monitoring system based on portable active seismic source（PASS）and distributed acoustic sensing（DAS）. For the continuous analysis of this monitoring data, machine learning emerges as a valuable tool, enabling automated seismic interpretation. These monitoring technologies including machine learning should be optimized for each CO₂ storage site. Moreover, integrating the monitoring outcomes into CO₂ behavior modeling（i.e., reservoir simulation）is crucial to predict the future fate of stored CO₂. The geologic model for the reservoir simulation should be updated（or improved）by reflecting the continuous monitoring data. Our modeling study particularly emphasizes the integration of molecular-scale and pore-scale CO₂ behaviors into reservoir-scale simulations, aiming for an accurate description of CO₂ behavior within the reservoir.