Sensitivity analysis of operating parameters affecting CO2 wellbore transient flow at the CaMI Field Research Station, Alberta, Canada.

• A non-isothermal transient behavior of CO 2 wellbore flow is investigated. • A sensitivity analysis on the wellbore and reservoir parameters is presented. • Dominant parameters affecting CO 2 wellbore flow are characterized. • Injection rate and target layer permeability show highest non-linearity effects. • Permeability of the underlying layer represents the minimum interaction effects. In this study, we report comprehensive sensitivity analysis using artificial intelligence (AI) and machine learning techniques to determine the dominant operating and formation statistical parameters affecting the transient behavior of CO 2 injection wellbore (i.e., wellbore pressure and temperature). This study focuses on the CO 2 injection tests undertaken at the Field Research Station (FRS) injection site in Alberta, Canada. The CO 2 wellbore transient behavior is simulated using a fully coupled nonisothermal transient multiphase wellbore-reservoir flow model (Jafari Raad et al., 2021). Radial Basis Function (RBF) Neutral Network and Polynomial Regressions are employed to characterize the dependency of the monitoring functions to the model parameters. The results show that the bottom-hole pressure (BHP) shows maximum sensitivity to the injection rate and minimum sensitivity to the injection pressure. The injection rate and the permeability of the target layer show the highest non-linearity effects. For a constant injection rate, the permeability of the target layer plays the most important controlling effect on the wellbore pressure. The results show that the injection pressure and permeability of the formation layer below the target formation represent the minimum non-linearity and interaction effects. This study provides an improved understanding of operating and reservoir parameters controlling the CO 2 wellbore monitoring practices in CO 2 injections. [ABSTRACT FROM AUTHOR]