(471c) Optimization of a Spatially-Resolved Petrochemicals Manufacturing and Supply Chain Network

The increase in oil and gas production from shale formations has resulted in significant increases in the production of Natural Gas Liquids (NGLs), including predominantly ethane, propane, n-butane and isobutane, with smaller amounts of pentane and less volatile hydrocarbons. The abundance of these hydrocarbons is an opportunity to boost chemical manufacturing because NGLs can be used as feedstocks for chemicals and fuel production [1]. The availability of NGLs has driven investments in chemical manufacturing and supply chains, in the form of new plants, expansions of existing plants, improvements in technologies, as well as the development of new technologies, aimed at harnessing the newly available resources. However, if this sort of infrastructure is not available, wasteful and environmentally unsound practices such as gas venting and flaring may result.

In this work, we develop an optimized, spatially-resolved network of petrochemical manufacturing technologies and supply chain transportation resources in order to best take advantage of the supply of NGLs, with a focus on determining an optimal product slate and the optimal placement of new manufacturing facilities based on new technology. As a starting point, we use a framework developed by DeRosa et al. [2], which involves a geographically detailed network model of the U.S. petrochemicals industry, with supply, demand, plant production capacity and trade data from the ICIS Supply and Demand Database [3]. In our work, we are adapting this model for use in specific regions, and incorporate the capability to expand the network by adding new manufacturing nodes in unspecified locations (to be identified via economic optimization).

The new model is formulated as a mixed-integer optimization problem with the objective of minimizing the cost of the manufacturing and supply chain network through choices of old and new technologies used and placement of new manufacturing facilities. Optimal placement of the new plants will contribute to lowering transportation costs, as well as establishing a more sustainable supply chain, reducing the distances required for transport of raw materials, intermediates and products. Various scenarios involving the introduction of new technologies [e.g, 4] are studied, focusing on the Marcellus/Utica region in the Northeast U.S. Sensitivity analyses are performed to study the impact of different supply, demand and capacity constraints. It is expected that this work will define targets for the development of more cost-effective and sustainable manufacturing and supply chain networks to take advantage of newly available light hydrocarbon resources, as well as provide guidance for the development of new technologies that utilize these feedstocks.

References

[1] U.S. Energy Information Administration (EIA), “What are natural gas liquids and how are they used?” [Online]. Available: http://www.eia.gov/todayinenergy/detail.cfm?id=5930. [Accessed: 02-Feb-2020].

[2] S. E. DeRosa, Y. Kimura, M. A. Stadtherr, G. McGaughey, E. McDonald-Buller, and D. T. Allen, “Network Modeling of the U.S. Petrochemical Industry under Raw Material and Hurricane Harvey Disruptions,” Ind. Eng. Chem. Res., 58, 12801–12815, 2019.

[3] ICIS Supply and Demand Database, 2017; http://www.icis.com/explore/services/analytics/supply-demand-data/suppl… [Accessed: 28 April 2020]

[4] T. Ridha, Y. Li, E. Gençer, J. J. Siirola, J. T. Miller, F. H. Ribeiro, and R. Agrawal, “Valorization of Shale Gas Condensate to Liquid Hydrocarbons through Catalytic Dehydrogenation and Oligomerization,” Processes, 6, 139, 2018.

Acknowledgement

This work is supported in part by the National Science Foundation under Cooperative Agreement No. EEC-1647722 (CISTAR – NSF Engineering Research Center for Innovative and Strategic Transformation of Alkane Resources, http://cistar.us). Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.