Modelling-Based Quantitative Leakage Risk Analysis for Enhanced CCS Monitoring, Measurement and Verification Plans

Summary Risk evaluation in Carbon Capture and Storage (CCS) operations serves as the foundation for an efficient Monitoring, Measurement, and Verification (MMV) framework, which is critical to prevent unwanted events and mitigate their consequences. Current risk analysis approaches are inherently subjective and most of the times qualitative, as they often rely on expert judgment and interpretation. This subjectivity poses significant challenges, particularly given the long duration of CCS projects, which can span decades and involve changes in personnel, expertise, and organizational priorities over time. Variability introduced by subjective assessments can lead to inconsistencies in decision-making, undermining the robustness and effectiveness of the MMV processes. We propose here a general framework to enable subsurface modelling-based quantitative risk assessment (QRA). By utilizing numerical metrics directly derived from the subsurface evaluation results, user dependency and bias can be minimized, enabling more standardized and reproducible assessments. This shift to Modelling, Monitoring, Measurement, and Verification (3MV) will enhance transparency and facilitate clearer communication with regulators and public stakeholders, fostering greater trust and collaboration throughout the lifecycle of CCS operations.