Estimation of the Life Cycle Greenhouse Gas Emissions of Bitumen-Derived Petroleum Fuels using Enhanced Solvent Extraction Incorporating Electromagnetic Heating (ESEIEH) and Toe-to-Heel Air Injection (THAI) Extraction Technologies

  • Author / Creator
    Mohsen Safaei
  • There is increased focus on reduction of greenhouse gas (GHG) emissions to reduce global warming. Combustion of fossil fuels are a key contributor to emissions of GHG. Alberta is the largest hydrocarbon base in North America due to its oil sands deposit. Bitumen from oil sands is refined to produce transportation fuels. Current process of extraction of bitumen through surface mining and steam assisted gravity drainage (SAGD) methods are GHG intensive. National and global initiatives for GHG reduction have triggered the focus on development of cleaner and more efficient bitumen extraction technologies. Toe-to-heel air injection (THAI) and enhanced solvent extraction incorporating electromagnetic heating (ESEIEH) are two emerging bitumen extraction technologies and are expected to emit lower GHG emissions than current recovery methods. THAI uses compressed air, while in ESEIEH, radio frequency (RF) energy along with solvent is used to recover bitumen. Since these methods are at the early stages of development, a detailed investigation and quantification of their GHG footprints over life cycle are necessary for decision making and policy formulation.The goal of this research is to develop bottom-up models to quantify the energy use and GHG emissions in these two recovery methods in various production pathways and energy scenarios. The developed model for THAI is used to assess the energy and GHG emission intensity from bitumen extraction, upgrading, transportation, refinery, and final use in vehicles, while the ESEIEH model, because of the lack of data on the properties of the produced bitumen, examines only the recovery process. The impacts of cogeneration, renewable electricity sources, and alternative configurations of surface facilities on ESEIEH emissions are explored. Sub-process mass-based allocation is usediiito allocate the refinery emissions to the transportation fuels. A Monte Carlo simulation was used to perform the uncertainty analysis on the models to arrive at the most realistic range of GHG emissions.The GHG emissions in ESEIEH range from 10 to 88 kg CO2eq/bbl of bitumen. The wide range is mainly due to the electricity source, as electricity comprises 77% of the total energy required. Antenna efficiency and the reservoir’s cumulative electricity-to-oil ratio (cEOR) had the greatest effect on overall GHG emissions in ESEIEH. Well-to-combustion (WTC) emissions in THAI range from 111-116 gCO2eq/MJ of gasoline, 114-117 gCO2eq/MJ of diesel, and 106-112 gCO2eq/MJ of jet fuel depending on the pathway and input range considered for the uncertainty analysis. The combustion of transportation fuels in the vehicle engine shows the highest WTC emissions with a share of 63-69% followed by the extraction stage with 22-25%. The air-to-oil ratio (AOR) and CO2 content of the produced gas have the largest effect on GHG emissions results in THAI. The SAGD GHG emissions from various studies were compared with this study’s results and revealed that GHG emissions from THAI are in the same range as from SAGD.The results of this study can help both government and the oil sands industry make emissions-reduction decisions. The results highlight which additional data is required from industry to increase the accuracy of GHG emissions estimates.

  • Subjects / Keywords
  • Graduation date
    Spring 2019
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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