(489g) Novel Shale Gas-Derived Liquid Fuel Systems Design Using an Open-Source Equation-Oriented Framework and Life-Cycle Emissions Analysis

The US shale gas sector has expanded its production in recent years. Dry natural gas (NG) and natural gas liquids (NGL) production has surged notoriously, demanding adequate handling of these unique resources. An efficient and strategic utilization is crucial for the energy transition towards net-zero emissions. The 2015 Paris Agreement [1] goal of limiting global warming to well below 2°C and pursuing efforts to limit the same to 1.5°C above pre-industrial levels requires rethinking and adaptation of clean energy systems. Such a goal demands a sustainable use of shale gas resources for reducing greenhouse gas (GHG) emissions while satisfying the energy demand. The combination of process development along with environmental assessment can provide crucial guidance during conceptual development stages. Multiscale modeling plays a critical role in modernizing the energy economy including the responsible use of shale gas. The incorporation of detailed kinetic information in process design facilitates confident and meaningful product portfolio estimations. Adding environmental impact metrics capable of observing the evolution of GHG emissions from different process configurations, operating conditions, and designs facilitates decision making towards sustainable processing schemes.

State-of-the-art processes have studied the feasibility of producing liquid fuels from different shale gas feedstocks [2-4] including its associated environmental impacts [5]. At the heart of the catalytic shale gas upgrading process [2] is the oligomerization reactor which dictates the transformation of NG and NGLs to heavier alkenes that can be used as fuel additives. Considerable effort has been focused on studying and modeling the kinetics of catalytic oligomerization, resulting in the development of complex (O(1000) reaction rates) microkinetic (MK) models [6]. Due to numerical tractability concerns, there are limitations to adopting MK models for detailed reactor modeling, optimization, and design. Engineers often use conversion or equilibrium models (e.g., Gibbs free energy minimization) for process design and optimization [2, 7]. For complex reaction networks, including oligomerization in NG upgrading, such simplified models may lead to inaccurate conclusions by not considering chemical kinetics.

In this work, we develop a multiscale modeling framework to tractably incorporate microkinetic detail [6] in process design using validated reduced-order kinetic models [8] combined with a tailor-made emissions assessment tool. We embed the multiscale model in the shale gas upgrading process design [2] using the equation-oriented framework IDAES [9]. The IDAES modeling framework facilitates simultaneous process optimization, which helps to recognize optimal design decisions that remain unrealized when using conventional sequential process simulation tools. The framework is capable of handling uncertainty and sensitivity analyses as well as process optimization considering yields, process configurations, and GHG emissions simultaneously.

References

[1] United Nations (2015). Paris Agreement. URL: https://unfccc.int/sites/default/files/english_paris_agreement.pdf

[2] Ridha, T., Li, Y., Gençer, E., Siirola, J. J., Miller, J. T., Ribeiro, F. H., & Agrawal, R. (2018). Valorization of shale gas condensate to liquid hydrocarbons through catalytic dehydrogenation and oligomerization. Processes, 6(9), 139.

[3] Chen, Z., Li, Y., Oladipupo, W. P., Gil, E. A. R., Sawyer, G., & Agrawal, R. (2021). Alternative ordering of process hierarchy for more efficient and cost-effective valorization of shale resources. Cell Reports Physical Science, 2(10), 100581.

[4] Chen, Z., Rodriguez, E., & Agrawal, R. (2022). Toward Carbon Neutrality for Natural Gas Liquids Valorization from Shale Gas. Industrial & Engineering Chemistry Research.

[5] Chen, Q., Dunn, J. B., & Allen, D. T. (2019). Greenhouse Gas Emissions of Transportation Fuels from Shale Gas-Derived Natural Gas Liquids. Procedia CIRP, 80, 346-351.

[6] Vernuccio, S., Bickel, E. E., Gounder, R., & Broadbelt, L. J. (2019). Microkinetic model of propylene oligomerization on Brønsted acidic zeolites at low conversion. ACS Catalysis, 9(10), 8996-9008.

[7] Yang, M., & You, F. (2018). Modular methanol manufacturing from shale gas: Techno‐economic and environmental analyses of conventional large‐scale production versus small‐scale distributed, modular processing. AIChE Journal, 64(2), 495-510.

[8] Ghosh, K., Vernuccio, S., & Dowling, A. W. (2022). Nonlinear reactor design optimization with embedded microkinetic model information. Frontiers in Chemical Engineering, 4, 898685.

[9] Lee, A., Ghouse, J. H., Eslick, J. C., Laird, C. D., Siirola, J. D., Zamarripa, M. A., ... & Miller, D. C. (2021). The IDAES process modeling framework and model library—Flexibility for process simulation and optimization. Journal of Advanced Manufacturing and Processing, 3(3), e10095.