SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment
Hema J. Siriwardane, Srikanta Mishra, Mark L. McKoy, Traci Rodosta, Gillian Rosen, Hari Viswanathan, Seyyed A. Hosseini, David Alumbaugh, Joseph P. Morris, Joshua A. White, Hongkyu Yoon · 2024
Our MotivationGrowing momentum for rapid commercial scale deployment of CCS Develop relevant experience / understanding among stakeholders Facilitate decision-making process during project planning, permitting, operations Traditional analysis involves physics-based models Data interpretation for characterization Pre-injection planning and system design Observational data integration for operational decision making Recent focus on Machine Learning based computationally expedient alternatives VISION: Transform our ability to make better, informed decisions related to the subsurface through real-time visualization, forecasting, and virtual learning. SMART-Initiative Science-informed Machine Learning to Accelerate Real Time (SMART) Decisions in Subsurface ApplicationsImprove the ability to consolidate technical knowledge, site-specific characterization information, and real-time data in a digestible way.Enable the optimization of carbon storage reservoirs by creating a capability for "real-time" forecasting of carbon storage reservoir behaviour.Enable improve the ability to understand and communicate expected subsurface behaviour during carbon storage operations to non-experts.