Helium is a critical strategic resource, and China currently exhibits high dependency on imports, necessitating urgent research into strategic helium reserve technologies. Helium storages (HSs) offers distinct advantages, including substantial storage capacity, operational integrity, and stability, establishing them as a preferred option for national helium reserves. Efficient operation of the ground pipeline network (GPN) within these facilities is essential to ensure stable performance. The study focuses on concentration variations across multiple injection-production wells. A mixed-integer nonlinear programming (MINLP) optimization model for the helium storage ground pipeline network (HSGPN) was developed to minimize total costs, including pipeline transportation costs, compressor energy consumption costs, and purification costs. The model determines optimal injection-production strategies under multiperiod gas demand scenarios, incorporating constraints such as injection-production volume (IPV) constraints, compressor constraints, node flow balance constraints, pipeline pressure drop constraints, node pressure constraint and reservoir pressure constraints. Implemented via the GAMS platform and solved with the ANTIGONE solver, the model was validated through a HS case with multiwell helium concentration differences. Simulation results indicated a hydraulic relative error range of 0–1.6%. Analysis revealed that a 50% and 100% increase in injection volume escalated costs by 69.52% and 108.22%, respectively, while a 100% production increase surged costs by 274.84%.
Peng et al. (Tue,) studied this question.