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Energy consumption and greenhouse gas emissions in upgrading and refining of Canada's oil sands products

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  • Nimana, Balwinder
  • Canter, Christina
  • Kumar, Amit

Abstract

A model-FUNNEL-GHG-OS (FUNdamental ENgineering PrinciplEs- based ModeL for Estimation of GreenHouse Gases in the Oil Sands) based on fundamental engineering principles was developed to estimate the specific energy consumption and GHGs (greenhouse gas emissions) for upgrading bitumen to produce SCO (synthetic crude oil). The model estimates quantity of SCO produced, the consumption of hydrogen, steam, natural gas and power in two different upgrading operations, namely delayed coking and hydroconversion. Hydroconversion upgrading is more energy and GHG (433.4 kgCO2eq/m3 of bitumen) intensive than delayed coker upgrading (240.3 kgCO2eq/m3 of bitumen) but obtains a higher yield of SCO. This research explores bitumen pathways in oil sands – upgrading bitumen to SCO, followed by transporting and refining SCO as compared to transporting and refining dilbit. The energy consumption, GHG emissions and volume of transportation fuels obtained from refining of different oil sands feeds has been investigated. Refining of oil sands products produce 7.9 to 15.72 gCO2eq per MJ of refined product. Refining of SCO to transportation fuels produces 41% and 49% less emissions than dilbit and bitumen respectively.

Suggested Citation

  • Nimana, Balwinder & Canter, Christina & Kumar, Amit, 2015. "Energy consumption and greenhouse gas emissions in upgrading and refining of Canada's oil sands products," Energy, Elsevier, vol. 83(C), pages 65-79.
    • Handle: RePEc:eee:energy:v:83:y:2015:i:c:p:65-79
    DOI: 10.1016/j.energy.2015.01.085
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    References listed on IDEAS

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    1. Chen, Q.L. & Yin, Q.H. & Wang, S.P. & Hua, B., 2004. "Energy-use analysis and improvement for delayed coking units," Energy, Elsevier, vol. 29(12), pages 2225-2237.
    2. Rahman, Md Mustafizur & Canter, Christina & Kumar, Amit, 2014. "Greenhouse gas emissions from recovery of various North American conventional crudes," Energy, Elsevier, vol. 74(C), pages 607-617.
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    6. Olateju, Babatunde & Kumar, Amit, 2011. "Hydrogen production from wind energy in Western Canada for upgrading bitumen from oil sands," Energy, Elsevier, vol. 36(11), pages 6326-6339.
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    1. Sapkota, Krishna & Gemechu, Eskinder & Oni, Abayomi Olufemi & Ma, Linwei & Kumar, Amit, 2022. "Greenhouse gas emissions from Canadian oil sands supply chains to China," Energy, Elsevier, vol. 251(C).
    2. Rui Xing & Diego V. Chiappori & Evan J. Arbuckle & Matthew T. Binsted & Evan G. R. Davies, 2021. "Canadian Oil Sands Extraction and Upgrading: A Synthesis of the Data on Energy Consumption, CO 2 Emissions, and Supply Costs," Energies, MDPI, vol. 14(19), pages 1-14, October.
    3. Di Lullo, Giovanni & Zhang, Hao & Kumar, Amit, 2017. "Uncertainty in well-to-tank with combustion greenhouse gas emissions of transportation fuels derived from North American crudes," Energy, Elsevier, vol. 128(C), pages 475-486.
    4. Zhu, Y. & Li, Y.P. & Huang, G.H. & Fan, Y.R. & Nie, S., 2015. "A dynamic model to optimize municipal electric power systems by considering carbon emission trading under uncertainty," Energy, Elsevier, vol. 88(C), pages 636-649.
    5. Guo, John & Orellana, Andrea & Sleep, Sylvia & Laurenzi, Ian J. & MacLean, Heather L. & Bergerson, Joule A., 2020. "Statistically enhanced model of oil sands operations: Well-to-wheel comparison of in situ oil sands pathways," Energy, Elsevier, vol. 208(C).
    6. Rahman, Md. Mustafizur & Canter, Christina & Kumar, Amit, 2015. "Well-to-wheel life cycle assessment of transportation fuels derived from different North American conventional crudes," Applied Energy, Elsevier, vol. 156(C), pages 159-173.
    7. Soiket, Md.I.H. & Oni, A.O. & Gemechu, E.D. & Kumar, A., 2019. "Life cycle assessment of greenhouse gas emissions of upgrading and refining bitumen from the solvent extraction process," Applied Energy, Elsevier, vol. 240(C), pages 236-250.
    8. Di Lullo, G. & Oni, A.O. & Kumar, A., 2023. "The development of complex engineering models using artificial neural network-based proxy models for life cycle assessments of energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    9. Dai, Zhenxue & Zhang, Ye & Bielicki, Jeffrey & Amooie, Mohammad Amin & Zhang, Mingkan & Yang, Changbing & Zou, Youqin & Ampomah, William & Xiao, Ting & Jia, Wei & Middleton, Richard & Zhang, Wen & Sun, 2018. "Heterogeneity-assisted carbon dioxide storage in marine sediments," Applied Energy, Elsevier, vol. 225(C), pages 876-883.
    10. Nimana, Balwinder & Canter, Christina & Kumar, Amit, 2015. "Life cycle assessment of greenhouse gas emissions from Canada's oil sands-derived transportation fuels," Energy, Elsevier, vol. 88(C), pages 544-554.
    11. Sapkota, Krishna & Oni, Abayomi Olufemi & Kumar, Amit & Linwei, Ma, 2018. "The development of a techno-economic model for the extraction, transportation, upgrading, and shipping of Canadian oil sands products to the Asia-Pacific region," Applied Energy, Elsevier, vol. 223(C), pages 273-292.

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