(352g) A Quantitative Approach to Assessing CO2 Permanence for California Air Resources Board (CARB) CCS Protocol
AIChE Annual Meeting
2024
2024 AIChE Annual Meeting
Sustainable Engineering Forum
Engineering Geologic Carbon Dioxide Storage Systems II
Tuesday, October 29, 2024 - 2:18pm to 2:36pm
The CARB CCS Protocol requirement for demonstrating storage permanence is quantitative because it requires quantifying probabilities of the occurrence of CO2 loss events and quantifying uncertainty in the magnitude of CO2 loss.
Quantitative risk assessment can be conducted in a variety of ways, depending on the quantity being evaluated (in this case, the probability of retaining at least 99% of injected CO2), the desired level of robustness and defensibility, and the resources (time, expertise, and money) available. Corresponding methodologies can range from direct âlumped assessmentâ of the desired quantity to highly sophisticated probabilistic, dynamic (time-stepping), disruptive-event-based numerical multiphase flow simulations, with various potential approaches in between.
In between these two ends of the approach spectrum are methods that balance adequate defensibility with resource cost. These methods involve analytical (nonnumerical) characterization of the probability of CO2 retention. These approaches describe how the system components could potentially fail and release CO2 from the storage complex.
One such approach identifies potential system or component âfailure modesâ that could occur and, if they occur, lead to âfailure.â Each failure mode is described in terms of two key elements:
- The probability of the failure mode occurring: Potential âtrigger eventsâ that could occur in various combinations and lead to the loss of CO2 are characterized in terms of âfault trees.â The probability of each trigger event is assessed using available data (from site characterization, testing, or modeling) and the judgment of subject matter experts (SMEs). These probabilities can then be combined through a probabilistic expression for the probability of the failure modeâs occurrence, defined by the fault tree, which in turn reflects the nature of the trigger event combinations leading to failure (e.g., Trigger Event A and Trigger Event B must occur to lead to failure).
- The amount of CO2 lost from the storage complex if the failure mode occurs: This potential loss can be characterized by a single (deterministic) value or an uncertain amount lost in the form of a probability distribution. These assessments also leverage available data and SMEs related to the movement of CO2 under the failure conditions or analogs.
The occurrence of each failure mode can then be simulated numerically, and if it occurs, the amount of CO2 lost can also be simulated numerically. The amount of CO2 lost across all the failure modes over the life of the project can be combined (added) to determine the amount of CO2 lost for one potential project future. Thousands of potential project futures can be simulated to infer a probability distribution for CO2 loss and, by extension, the probability of CO2 permanence.
This approach for evaluating the probability of CO2 permanence was adopted because the general methodology (i.e., failure modes and fault trees) has a historical usage pedigree for complex, uncertain problems because it provides adequate defensibility for reasonable effort (e.g., National Aeronautics and Space Administration, 2002; U.S. Nuclear Regulatory Commission, 1999; Vick, 2002).
References
California Air Resources Board, 2018, Carbon capture and sequestration protocol under the Low Carbon Fuel Standard [Online]: https: https://www.carb.ca.gov/sites/default/files/2020-03/CCS_Protocol_Under_LCFS_8-13-18_ada.pdf (accessed March 2024).
National Aeronautics and Space Administration, 2002, Fault tree handbook with aerospace applications: Washington, D.C., Office of Safety and Mission Assurance.
U.S. Nuclear Regulatory Commission, 1999, Framework for risk-informed regulation in the Office of Nuclear Material Safety and Regulation: SECY-99-100, Washington, D.C.
Vick, S.G., 2002, Degrees of beliefâsubjective probability and engineering judgment: Reston, Virginia, American Society of Civil Engineers.