Assessing the Long-Term Risks in Subsurface Carbon Storage (SCS) Projects: Learning from Past Injection and Storage Projects #8

Subsurface characterization is critical for any SCS project. In particular, we need to accurately quantify the storage volume, injectivity and containment potential of the target reservoir, and the associated chance of failure. An accurate and comprehensive understanding of the project subsurface is a prerequisite to the assessment of project risk. Without this work, early indicators of later events, which could result in project failure, may be missed.

To help ensure all potential risks and uncertainties are assessed, past projects should be carefully studied, particularly those that experienced unexpected events. While large-scale SCS is relatively new, the process of storing injected fluids underground is not. The history of these operations provides insights into the types and frequency of unexpected events and failure incidents. Analysis of these past projects can illuminate the difference between aleatory and epistemic risks and uncertainties and provide valuable lessons for future projects.

Consider, for example, the use of waterflooding for secondary recovery. During the first few decades of implementation, many valuable lessons were learned including 1) recovery factors are highly variable and dependent on rock and fluid properties as well as development strategies and operational practices, 2) an absence of analogs and understanding led to multiple missteps such as implementing peripheral injection in fields that required in-zone injection, 3) attempts to create simple empirical relationships between reservoir parameters and recovery efficiencies failed to produce statistically valid correlations, and 4) models only became truly useful for designing and managing waterfloods after they were calibrated to multiple long-term projects.

In the next set of posts, we describe several examples of injection project events, illustrating what happened, the factors responsible, and if these events could have been foreseen. We then propose a quantitative risk assessment framework suitable for evaluating long-term, low-frequency events which can inform monitoring, mitigation, and remediation plans to help ensure a successful project outcome.