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Probability estimation of CO2 leakage through faults at geologic carbon sequestration sites

AbstractLeakage of CO2 and brine along faults at geologic carbon sequestration (GCS) sites is a primary concern for storage integrity. The focus of this study is on the estimation of the probability of leakage along faults or fractures. This leakage probability is controlled by the probability of a connected network of conduits existing at a given site, the probability of this network encountering the CO2 plume, and the probability of this network intersecting environmental resources that may be impacted by leakage. This work is designed to fit into a risk assessment and certification framework that uses compartments to represent vulnerable resources such as potable groundwater, health and safety, and the near-surface environment. The method we propose includes using percolation theory to estimate the connectivity of the faults, and generating fuzzy rules from discrete fracture network simulations to estimate leakage probability. By this approach, the probability of CO2 escaping into a compartment for a given system can be inferred from the fuzzy rules. The proposed method provides a quick way of estimating the probability of CO2 or brine leaking into a compartment. In addition, it provides the uncertainty range of the estimated probability.
- University of North Texas United States
- Lawrence Berkeley National Laboratory United States
- NASA Earth Science United States
- Lawrence Berkeley National Laboratory United States
- University of North Texas United States
Compartments, Carbon Sequestration, Leakage risk, Brines, Storage, 58, Connectivity of faults and fractures, 54, Risk Assessment, Probabilitly estimation, Energy(all), Safety, Fractures, Probability
Compartments, Carbon Sequestration, Leakage risk, Brines, Storage, 58, Connectivity of faults and fractures, 54, Risk Assessment, Probabilitly estimation, Energy(all), Safety, Fractures, Probability
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).23 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
