Practical leakage risk assessment for CO2 assisted enhanced oil recovery and geologic storage in Ohio's depleted oil fields

A method for risk assessments of geological carbon capture, utilization and storage (CCUS) projects was created and the results of three risk assessments for potential CCUS projects at depleted oil fields in Ohio are presented. The risk framework described uses the bow-tie method with features, events, and processes (FEPs) to identify and assess risk posed by potential loss of integrity of legacy wells. Field-scale well integrity studies have had to rely largely on historical data to assess the potential for fluid leakage related to CCUS projects. This study uses categories of known information to develop a proxy for likelihood of leakage. Proxy categories were: Spud Date, Treatment, Well Status, Plugging and Abandonment Date, Well Type, Plug, Surface Cement, and Primary Cement. Separate risks were developed for each well and each scenario. The consequence of a leakage event was estimated based on costs to businesses and property owners for each leakage scenario. Cost categories in this framework include finding and fixing the leak, environmental remediation, CO2 injection interruption, technical remedies for damages, and legal costs. Using the likelihood of leakage calculated for each field and the cost of potential consequences, the risks for each field were estimated to be between $13 million to $63 million for the three fields of interest. The use of the bow-tie method allows easy visualization and identification of barriers that may reduce the likelihood of the top event in a risk scenario.

Automated summary

A risk assessment method for geological carbon capture, utilization, and storage (CCUS) projects was developed and applied to three CCUS projects in depleted oil fields in Ohio. The study used historical data and proxy categories to assess the likelihood of fluid leakage, and estimated the cost of potential consequences for each field based on leakage scenarios. The use of the bow-tie method allowed for easy visualization and identification of barriers to reduce risks in the scenarios.