IUCRC Planning Grant University of Southern California: Center for CO2 Storage Modeling, Analytics, and Risk Reduction Technologies (CO2-Smart)

University Of Southern California, Los Angeles CA

Investigators

Abstract

Geologic CO2 storage offers a viable option for reducing CO2 in the atmosphere. Successful implementation of projects in this area hinges on scientific and technological advances in multi-physics flow modeling, subsurface monitoring data analytics, and risk assessment and mitigation strategies. This Industry-University Collaborative Research Center for CO2 Storage Modeling, Monitoring, Analytics, and Risk Reduction Technologies (CO2-SMART) aims to create a synergistic research program to accelerate the development, adaptation, and deployment of novel AI-enriched technologies to enable efficient and safe implementation of the geologic storage of CO2. The prospective members of the Center include the main CO2-producing sectors of the industry, including upstream and downstream oil and gas companies, chemical and petrochemical companies, as well as power plants and utility companies. The Center will train the next generation of engineers and scientists as future leaders for implementing and managing large-scale GCS projects. This will help to address one of the most pressing challenges of our time with broad and significant societal, energy security, and public health impacts. The Center will be guided by an industry advisory board of Center members who will assist it in maintaining its focus on addressing the emerging industry challenges for successful implementation of CO2 storage in the subsurface. The technical focus of the Center will be on integrating recent advances in multi-physics modeling and simulation, subsurface monitoring data acquisition, and modern AI and data science algorithms to develop reliable technologies for safe and sustainable subsurface geologic storage of CO2. The emerging AI-based technologies are bound to replace the traditional labor-intensive modeling workflows with efficient automated platforms, where big data analytics is used not only to enhance data processing, visualization, and management, but also to provide advanced physics-informed predictive analytics, anomaly/fault detection, and decision support capabilities for real-time operation. The Center will focus on several key research and development thrust areas, including (1) modeling and characterization of subsurface fluid, rock, and fracture properties, as well as the parameters pertaining to the underlying multi-physics processes, (2) multiscale and multi-physics modeling and prediction of subsurface flow processes, (3) high-resolution dynamic characterization and imaging using multi-physics monitoring data modalities and advanced deep learning architectures, (4) modern risk assessment and uncertainty quantification technologies pertaining to complex multi-physics systems, and (5) optimization and control of the injected CO2 plume movement under risk and uncertainty. Developing and advancing state-of-the-art technologies in these research areas will directly benefit the industry members and serve the general industrial and scientific communities, as well as the public at large. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.