HAN Qingyun, CHEN Wei, ZHENG Zhimei, XIE Ningning, LI Shuangjiang, HAN Zibo, ZHANG Xuelin
According to the actual geological structure of the Kendong oil reservoir, a geometric model of the reservoir aquifer and caprock was established. Using the COMSOL simulation platform, a large-scale subsurface physical model of the compressed air energy storage in aquifers (CAESA) system in oil reservoirs was constructed by integrating interfaces such as porous media two-phase flow, Darcy’s law, and solid heat transfer to enable dynamic simulation of the full cycle from gas injection for reservoir construction to cyclic injection production. Under baseline conditions, the temporal variations of gas saturation, temperature field, and pressure field within the reservoir during the full cycle were simulated. A sensitivity analysis was conducted for the steady injection-production stage to investigate the impacts of permeability, injection-production rate, horizontal well length, and well location on the average wellbore temperature and pressure. The results reveal that increased permeability, reduced injection-production rates, and extended horizontal wells decrease the thermal and pressure differences between the wellbore and reservoir during cyclic injection production. The impact of horizontal well location depends on its average distance from the caprock: a greater distance results in a larger temperature difference but a smaller pressure difference during injection production. Comparative analysis reveals that permeability and the injection-production rate have more substantial impacts on wellbore pressure. In particular, when permeability increased from 600 to 1 400 mD and the injection rate from 12 to 20 kg/s, the pressure amplitude decreased by approximately 28.9% and 24.1%, respectively, substantially exceeding those of equivalent variations in horizontal well length and location. This study provides theoretical guidance for the design and energy efficiency evaluation of the CAESA systems in oil reservoirs, specifically regarding well configuration and operational parameter optimization.