Many depleted oil and gas reservoirs are targets for CO 2 enhanced oil recovery, resulting in CO 2 storage as part of the commercial enhanced oil recovery process. These oil fields have legacy wellbores that may contain a leakage pathway. Corrosion or degradation can occur anywhere along the wellbore through or along the cement, casing, tubing, or plugs and is a challenging issue facing the oil and gas industry. Two case studies presented here evaluate legacy wells in the Weyburn oil field. One well has injected over 263 million cubic meters of CO 2 , and the second well has not been exposed to CO 2. These case studies aim to help understand casing corrosion in CO 2-rich environments. Both wellbores exhibited signs of corrosion, with corrosion ranging from small pits to complete penetration through the casing. Contributing factors to corrosion in these wells range from exposure to injected fluids, injected CO 2 , packer placements, formation fluid exposure, and the corrosive environment that is present in the perforated area of the well.

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This work uses probabilistic methods to simulate a hypothetical geologic CO2 storage site in a depleted oil and gas field, where the large number of legacy wells would make it cost-prohibitive to sample all wells for all measurements as part of the postinjection site care. Deep well leakage potential scores were assigned to the wells using a random subsample of 100 wells from a detailed study of 826 legacy wells that penetrate the basal Cambrian formation on the U.S. side of the U.S./Canadian border. Analytical solutions and Monte Carlo simulations were used to quantify the statistical power of selecting a leaking well. Power curves were developed as a function of (1) the number of leaking wells within the Area of Review; (2) the sampling design (random or judgmental, choosing first the wells with the highest deep leakage potential scores); (3) the number of wells included in the monitoring sampling plan; and (4) the relationship between a well’s leakage potential score and its relative probability of leakage. Cases where the deep well leakage potential scores are fully or partially informative of the relative leakage probability are compared to a noninformative base case in which leakage is equiprobable across all wells in the Area of Review. The results show that accurate prior knowledge about the probability of well leakage adds measurable value to the ability to detect a leaking well during the monitoring program, and that the loss in detection ability due to imperfect knowledge of the leakage probability can be quantified. This work underscores the importance of a data-driven, risk-based monitoring program that incorporates uncertainty quantification into long-term monitoring sampling plans at geologic CO2 storage sites.

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