An optimal design strategy for spiral-wound membrane networks based on an approximate permeator model and a mixed-integer nonlinear programming (MINLP) solution strategy is proposed. A general permeator system superstructure is used to embed a very large number of possible network configurations. The superstructure allows the development of a MINLP design strategy which simultaneously optimizes the permeator configuration and operating conditions to minimize an objective function which approximates the total annual process cost. Case studies for the separation of CO2/CH4 mixtures in natural gas treatment and enhanced oil recovery are presented. Permeator configurations are derived for different number of separation stages for both continuous and discrete membrane areas. The propose approach provides an efficient methodology for preliminary design of multi-stage membrane separation systems for binary gas mixtures.