Risk assessment highlights cross-domain uncertainties in carbon capture and storage, indicating the need for integrated models.
Carbon Capture and Storage projects face risks, known potential hazards, and uncertainties that are less predictable and often not fully understood. Addressing these risks effectively requires a comprehensive and multidisciplinary risk identification and mitigation approach. While much of the focus in storage projects usually centers on containment and injectivity, key risks can arise much earlier, beginning with CO₂ capture, conditioning, and transport, where impurities or operational variability may directly influence storage site performance and safety. CCS risk assessment requires a deep understanding of the reservoir system and the development of valid and defendable modeling assumptions. The accuracy of a numerical simulation depends heavily on how well we interpret surface and subsurface data, the accuracy of the data entered in the predictive models, the quality and vintage of the data, and how certain lingering uncertainties are managed. Inadequate modeling approaches can introduce significant errors into simulation outcomes, including false positives or negatives regarding fault reactivation or missing a real threat to caprock integrity, either of which can derail a project's safety and overall reliability. Surface and subsurface risks are often evaluated in isolation; however, cross-domain interactions can magnify hazards. For example, CO2 impurity-driven corrosion may compromise well injectivity or cause degradation of well integrity, creating backpressure on the compressor and potentially triggering high-impact events (e.g., containment breaches, unplanned shutdowns). Early detection and mitigation of these cross-domain risks are vital to ensure project safety, regulatory compliance, and economic viability. This work emphasizes the importance of integrated and transparent workflows, acknowledging that uncertainty cannot be eliminated but must be mitigated through data-informed models, sound engineering judgment, and continuous calibration against field observations. This study advocates for the need for technically robust practices as a foundation for safe, effective, and credible CO₂ storage
No takes yet. Share an insight, caveat, or question.
Garcia et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: