Objective Underground gas storage (UGS) facilities are crucial infrastructures in the "production-supply-storage-sale-consumption" industry chain for natural gas. They play a significant role in stabilizing supply, balancing fluctuations in both supply and demand, and ensuring emergency gas supply. However, traditional operational strategies often lead to high energy consumption during gas injection, primarily due to their reliance on subjective decision-making, which fails to fully utilize historical data and lacks intelligent decision support. Therefore, optimizing gas injection into these underground storages is essential for maintaining their efficient and safe operation.

Methods The correlations among reservoir pressures, storage capacities, and single-well gas injection capacities were established through fitting, with the utilization of geological development data and injection-production operational data collected over repeated cycles. An integrated dynamic pressure calculation method for the gas injection process in UGS facilities was developed, incorporating these established relationships. This method subsequently enabled the dynamic updating of pressure calculation results for each link of the gas injection process. For gas injection optimization, the updated pressure levels serve as key input parameters and dynamic boundary conditions for objective function calculation and constraints establishment. Then a gas injection optimization method was formulated, taking the time of open gas injection wells as the decision variable and the energy consumption for gas injection and wellhead oil pressure stability as the optimization objectives, while defining constraints such as the planned total gas injection volume and gas injection period. The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was employed to solve the Pareto frontier solution set. The economic efficiency and safety of various solutions were comprehensively evaluated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to identify the optimal open well schemes and gas injection volumes.

Results The proposed method was utilized to formulate a gas injection scheme for an established gas storage facility, with the gas injection period and planned total gas injection volume set at 30 days and 1,300×10⁴ m³, respectively. The corresponding total energy consumption for gas injection was 8.002×10⁴ kW, while the standard deviation of wellhead oil pressure was 1.712 MPa. These results reflect reductions of 51.6％ and 81.6％, respectively, compared to the initial scheme, underscoring the effectiveness of the optimization.

Conclusion The integrated dynamic pressure calculation method for the gas injection process in UGS facilities allows for the comprehensive coordination of dynamically changing pressure relationships among reservoirs, wellbores, and surface pipeline networks. This approach effectively addresses the shortcomings of traditional methods that often overlook dynamic fluctuations in reservoir pressure and provides reliable support for enhancing the scientific rigor and practicality of gas injection optimization. Future research should focus on examining the dynamic coupling relationships among reservoir pressures, storage capacities, and single-well gas injection capacities, aiming for further improvement and optimization to address complex geological conditions or incomplete on-site data. Such efforts will promote advancements in underground gas storage facilities, leading to increased efficiency, safety, and intelligence.