Numerical Simulation of CO₂ Huff and Puff Feasibility for Light Oil Reservoirs in the Appalachian Basin: Sensitivity Study and History Match of a CO₂ Pilot Test

CO₂ cyclic stimulation (huff and puff) is a method for increasing well productivity after primary and secondary production. In this work, we study the feasibility and estimated enhanced oil recovery of CO₂ huff and puff for light oil low-pressure and low-permeability reservoirs using numerical simulation supported by experimental and field test data. We performed CO₂ huff and puff numerical modeling to (1) understand the effect of operational and geological parameters on incremental oil recovery and (2) also history match a huff and puff pilot test. The reservoir model is based on available geologic data and experimental PVT data in depleted oil reservoirs similar to those in the Appalachian Basin. The previous huff and puff operations in the Appalachian basin have been used in a wide range of operational parameters such as CO₂ injected mass and CO₂ cycles. Simulation results in this study, using a pseudomiscible approach in a black oil model, show that the injection rate and the mixing parameter are the main parameters affecting incremental oil recovery. There is a nonlinear relationship between CO₂ injected mass (beyond 200 MT) and incremental recovery. Also, permeability heterogeneity can significantly affect CO₂ huff and puff performance and should be accounted in the model. In addition to the parametric study, numerical simulations focusing on matching primary production data and pressure data from the CO₂ injection period during a huff and puff pilot test in a depleted oil reservoir were performed with sensitivity to uncertain parameters. Homogenous and composite single wellbore models were built for the history match. Uncertain parameters include the permeability of each zone and relative permeability relationships. Simulation results of the matched model show the importance of considering bottom hole pressure during huff and puff as a matching parameter to evaluate the model’s uncertain parameters (such as permeability) accurately. A comparison of the oil–water relative permeability of the matched model with the core-flood experimental data, using a Clinton sandstone core, is also discussed.