This paper addresses the risk management for optimal design and operations of shale gas supply chains under uncertainty of estimated ultimate recovery (EUR). A multiobjective two-stage stochastic mixed-integer linear programming model is proposed to optimize the expected total cost and the financial risk. The latter criterion is measured by conditional value-at-risk (CVaR) and downside risk. In this model, both design and planning decisions are considered with respect to shale well drilling, shale gas production, processing, multiple end-uses, and transportation. In order to solve this computationally challenging problem, we integrate both the sample average approximation method and the L-shaped method. The proposed model and solution methods are illustrated through a case study based on the Marcellus shale play. According to the optimization results, the stochastic model provides a feasible design for all the scenarios with the lowest expected total cost. Moreover, after risk management, total expected cost increases but the risk of high-cost scenarios is reduced effectively, and the CVaR management shows its advantage over downside risk management in this specific case study.