This paper examines the application of Bayes’ theorem to evaluate risk of induced seismicity associated with CO2 sequestration in the Arbuckle Group, which extends across the southern Mid-Continent of the US. Geological storage can effectively contribute to reducing emission of CO2, otherwise released into the atmosphere, achieving the climate goals committed in the 2021 United Nations Climate Change Conference (COP26) however, concerns about risks associated with CO2 injection along with economic challenges of infrastructure required to execute the Carbon Capture Utilization and Storage projects stand against full realization of remarkable potentials. The main goal is usually for CO2 to be stored over geologic time; hence, geomechanical risks such as the seismicity in the field or potential CO2 leakage through seals cannot be ignored and is considered as one of the requirements to determine success of the project.

This paper elaborates the risk of potential seismic events that can impact the longevity and success of projects. Accurate risk estimation is key for environmental, economic, and safety concerns and is also one of the requirements to get class VI permits from the US Environmental Protection Agency. We utilized the Bayesian approach, a statistical model where a random probability distribution is used to represent uncertainties within the model, including both input/output parameters. Using the Arbuckle Group as a case study we utilized data from established physics-based models of the system and the details from past observed/monitored failures to evaluate future risk potential for the area. In our approach, we establish the current probability for the state of stress for the area under investigation, then monitor how the state of stress evolves. The stress state probability distribution is calculated to evaluate the probability of activating a critically oriented fault over a range of specified pore pressures.

The results suggest that we can estimate the probability of inducing seismicity in the formation. Based on our modelling results, at initial injection pressures there is a 30% risk of introducing seismicity in the Arbuckle Group when a critically oriented fault exists. Based on these results, we went further to conduct a sensitivity analysis to determine the features with multiple predictor dependency on the risk level. In most cases analyzed the risk of induced seismicity by injection is still greater than 30% due to the stress state being very poorly constrained. Introducing the stress state constraints from the Arbuckle Group in Kansas State, the risk of seismicity reduced to 10%.

Considering the results from our work, operators can optimize the site screening and collect additional data to constrain inherent uncertainties in geomechanical risk evaluation and make informed decisions during operations. The result from this work shows that geological storage of CO2 at reduced rates in the Arbuckle Group can be a feasible safe strategy towards achieving climate goals in selected areas based on obtaining information in stress state, and there is value of information in obtaining stress data in these areas.

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