Abstract: A gas field in Xinjiang has seen a rise in the ethane fraction of its natural gas, creating a control challenge. Boosting ethane recovery is therefore a top priority. Using an existing HYSYS model of the ethane-recovery unit and real plant data, we optimized the key variables with response-surface methodology and then applied a multi-objective particle-swarm algorithm to find the best compromise between ethane yield and overall profit. When the optimum set-points were rerun in HYSYS, the deviation was only 0.44% for ethane recovery and 0.19% for economic return, confirming the reliability of the solution. After plant implementation, ethane recovery rose from 95.07% to 99.55%, adding 6.3 t of extra ethane per day and about 8 million CNY per year. The study gives a robust, easy-to-apply method for optimizing natural-gas ethane-recovery parameters, offering both higher revenue and a steadier feedstock supply for the downstream chemical chain.