Well control diagnosis model of underground gas storage in multi-cycle operation

Underground gas storage（UGS） plays a crucial role in ensuring national energy security. Predicting multi-cycle well control parameters is key to the efficient operation of UGS facilities. Due to the complexities involved in understanding the operation patterns of W23 UGS and the challenges in developing effective schemes, a prediction model for well control parameters in multi-cycle operations has been developed using the rate-transient analysis method, and the change pattern of well control parameters with the development of UGS is analyzed. The process begins with preprocessing the dynamic production data from W23 UGS, which is then inputted into RTA software along with the reservoir parameters. The Dranchuk-Abu-Kassem model calculates the high-pressure physical properties of natural gas. Following this, the seepage characteristics of W23 UGS are examined, and the optimal wellbore conduit flow model is selected to determine the bottomhole pressure in the gas wells. The Blasingame pattern analysis method is then applied to fit the well control parameters and establish a basic model, such as the well control radius. By adjusting the model with production data, a refined prediction model for multi-cycle operation is developed. This model is utilized to categorize the wells of W23 UGS based on their production performance and control characteristics. The results categorize the wells into three types, with distribution ratios of 39%, 34%, and 27%, respectively. The predictive model reveals that during UGS operation, the well control radius of the gas wells initially increases significantly, then stabilizes. Similarly, the average well control volume of the gas reservoir continues to rise, and the effective permeability of the reservoir influenced by the three categories of wells initially increases before stabilizing.