Uncertainty effect of CO2 molecular diffusion on oil recovery and gas storage in underground formations

CO2 molecular diffusion in underground reservoir fluids, quantified by diffusion (D) coefficient, is of great importance for CO2 storage and enhanced oil recovery (EOR) projects. The reported CO2 D coefficients values are uncertain due to difficulty of accurately measuring this parameter specifically at high pressure-high temperature conditions. Hence, this study aims to investigate the impact of the uncertainty in the value of CO2 D coefficient on both oil recovery and CO2 storage during intermittent CO2 assisted gravity drainage (CO2-GAGD) injection in oil reservoirs. The impact of the CO2 diffusion on oil compositional changes and fluid distribution in porous medium was also investigated here. To do so, using data from a Malaysian oil field, a tuned equation of state along with a composition simulation model were used to emphasis on the effect of diffusion during the intermittent CO2-GAGD process. The effects of reservoir permeability, reservoir porosity, injection rate, and soaking time on oil recovery and gas storage were tested across different values of CO2 D coefficient. Including the gas diffusion in the simulation resulted in enhancement of the gas penetration though the porous medium leading to the enhanced oil recovery especially at the final soaking-injection/production cycles of the intermitted CO2 injection. The lowest impact of the uncertainty in the CO2 D coefficient on the oil recovery and gas storage efficiency was found in the high permeability case. Additionally, decreasing the gas injection rate or increasing the soaking time magnified the impact of the uncertainty of the CO2 D coefficient. Furthermore, the CO2 storage efficiency was found to be highly sensitive to the changes in the D coefficient in the high porosity case. To verify the results, the obtained simulation results were compared and found to be consistent with previous findings reported in the literature. This study adds accuracy to predicting CO2 EOR and storage projects through understanding the uncertainty of molecular diffusivity. © 2022 The Author(s)