Optimal shale oil and gas investments in the United States

被引:24
|
作者
Tan, Siah Hong [1 ]
Barton, Paul I. [1 ]
机构
[1] MIT, Proc Syst Engn Lab, 77 Massachusetts Ave, Cambridge, MA 02139 USA
关键词
Shale oil and gas; Infrastructure investments; Supply chain optimization; Stochastic programming; Mixed-integer linear programming; OPTIMAL DYNAMIC ALLOCATION; SUPPLY CHAIN OPTIMIZATION; STRANDED NATURAL-GAS; FACILITY LOCATION; HYBRID FEEDSTOCK; WATER MANAGEMENT; MOBILE PLANTS; LNG EXPORTS; UNCERTAINTY; SYSTEMS;
D O I
10.1016/j.energy.2017.09.092
中图分类号
O414.1 [热力学];
学科分类号
摘要
We present a comprehensive supply chain optimization model to determine optimal shale oil and gas infrastructure investments in the United States. The model encompasses multiple shale plays, commodities, plant locations, conversion technologies, transportation modes and both local and foreign markets. The dynamic evolution of supply, demand and price parameters and the uncertainty in parameter realizations are fully taken into account. Imposing two different scenario sets over a time horizon of twenty-five years, the model maximizes the expected net present value of the entire undertaking. We analyze the features of the optimal infrastructure investments and associated operating decisions, perform case studies which highlight the importance of incorporating uncertainty into the model and analyze the stability of the stochastic solutions as the degree of uncertainty changes. The overall opportunity set of investments is sparse, and there is a tendency for over-investment in new liquefied natural gas capacity when the uncertainties in future oil prices are not taken fully into account. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:398 / 422
页数:25
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