The long-term planning of the shale gas supply chain is a relevant problem that has not been addressed before in the literature. This article presents a mixed-integer nonlinear programming (MINLP) model to optimally determine the number of wells to drill at every location, the size of gas processing plants, the section and length of pipelines for gathering raw gas and delivering processed gas and by-products, the power of gas compressors, and the amount of freshwater required from reservoirs for drilling and hydraulic fracturing so as to maximize the net present value of the project. Because the proposed model is a large-scale nonconvex MINLP, we develop a decomposition approach based on successively refining a piecewise linear approximation of the objective function. Results on realistic instances show the importance of heavier hydrocarbons to the economics of the project, as well as the optimal usage of the infrastructure by properly planning the drilling strategy. (c) 2014 American Institute of Chemical Engineers AIChE J, 60: 2122-2142, 2014