Statistically enhanced model of oil sands operations: Well-to-wheel comparison of in situ oil sands pathways

John Guo, Andrea Orellana, Sylvia Sleep, Ian J. Laurenzi, Heather L. MacLean and Joule A. Bergerson

Energy, 2020, vol. 208, issue C

Abstract: Although the life cycle greenhouse gas (GHG) emissions associated with Canadian oil sands have been investigated in recent years, questions remain regarding the source and impact of variability in emissions in this industry over time. This study combines publicly-available data from the fifteen largest operating in situ extraction projects, i.e., cyclic steam stimulation (CSS) and steam assisted gravity drainage (SAGD) with a statistically-enhanced life cycle model to investigate variability in well-to-wheel (WTW) GHG emissions. We estimate that the WTW GHG emissions from CSS-derived gasoline range from 99 to 114 g CO2eq/MJ (80% confidence interval), 6–22% higher than the RFS2 baseline. The corresponding range for SAGD-derived gasoline is 98–133 g CO2eq/MJ, 5–42% higher than the RFS2 baseline. SAGD-derived gasoline has more variability as some operators “upgrade” their crudes, emitting GHGs, whereas no CSS operator employs upgrading. Without upgrading, the 90th percentile for SAGD emissions would be 114 g CO2eq/MJ. Upstream variability in GHG emissions drives the positively skewed WTW GHG distributions. This demonstrates the importance of understanding the nature and magnitude of variability and uncertainty in decision making.

Keywords: Variability; Oil sands; Life cycle assessment (LCA); Petroleum refining; Greenhouse gas (GHG) emissions (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:208:y:2020:i:c:s0360544220313578

DOI: 10.1016/j.energy.2020.118250

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