Light Hydrocarbon Capture and Helium Enrichment from Nitrogen-Rich Natural Gas via a Two-Stage Hydrate Process: Multiobjective Optimization and Performance Analysis

The valorization of nitrogen-rich low-grade natural gas (N 2 -lgNG) presents a dual challenge of mitigating greenhouse gas emissions and securing strategic helium resources. This study demonstrates the technical feasibility and optimization of a two-stage hydrate-based gas separation (HBGS) process for the simultaneous capture of light hydrocarbons (methane and ethane) and enrichment of low-abundance helium (0.52 mol %) as a crucial industrial pretreatment step. A systematic methodology integrating response surface methodology (RSM) and multiobjective optimization was employed. RSM was used to develop accurate proxy models that quantify the effects of the gas–liquid ratio (GLR), temperature ( T ), and pressure ( P ) on three key separation performance metrics: light hydrocarbon capture rate (CR LH ), helium concentration in the residual gas (cHe res ), and helium recovery rate (RR He ). The analysis identified temperature as the most sensitive parameter for separation performance. The nondominated sorting genetic algorithm II (NSGA-II) was applied to proxy models to generate a Pareto-optimal frontier of solutions. The entropy-weighted technique for order of preference by similarity to ideal solution (TOPSIS) was then utilized to impartially select the single best-compromise operating condition: GLR of 90 N m 3 /m 3, T of 279.15 K, and P of 5.00 MPa. Experimental validation under the optimal conditions achieved a CR LH of 91.05%, a 6.3-fold increase in cHe res (reaching 3.27 mol %), and an RR He of 78.25%. This work not only proves the efficacy of the two-stage HBGS process for integrated resource recovery from challenging gas streams but also establishes a model-driven optimization framework for the design of HBGS technology.