期刊
APPLIED ENERGY
卷 143, 期 -, 页码 189-199出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2015.01.024
关键词
Life cycle assessment; Energy consumption; GHG emissions; Oil sands; Surface mining; SAGD
资金
- NSERC/Cenovus/Alberta Innovates Associate Industrial Research Chair in Energy and Environmental Systems Engineering
- Cenovus Energy Endowed Chair in Environmental Engineering
A model - FUNNEL-GHG-OS (FUNdamental ENgineering PrinciplEs-based ModeL for Estimation of Green-House Gases in the Oil Sands) was developed to estimate project-specific energy consumption and greenhouse gas emissions (GHGs) in major recovery and extraction processes in the oil sands, namely surface mining and in situ production. This model estimates consumption of diesel (4.4-7.1 MJ/GJ of bitumen), natural gas (52.7-86.4 MJ/GJ of bitumen) and electricity (1.8-2.1 kW h/GJ of bitumen) as fuels in surface mining. The model also estimates the consumption of natural gas (123-462.7 MJ/GJ of bitumen) and electricity (1.2-3.5 kW h/GJ of bitumen) in steam assisted gravity drainage (SAGD), based on fundamental engineering principles. Cogeneration in the oil sands, with excess electricity exported to Alberta's grid, was also explored. Natural gas consumption forms a major portion of the total energy consumption in surface mining and SAGD and thus is a main contributor to GHG emissions. Emissions in surface mining and SAGD range from 4.4 to 7.4 gCO(2)eq/MJ of bitumen and 8.0 to 34.0 gCO(2)eq/MJ of bitumen, respectively, representing a wide range of variability in oil sands projects. Depending upon the cogeneration technology and the efficiency of the process, emissions in oil sands recovery and extraction can be reduced by 16-25% in surface mining and 33-48% in SAGE). Further, a sensitivity analysis was performed to determine the effects of key parameters on the GHG emissions in surface mining and SAGD. Temperature and the consumption of warm water in surface mining and the steam-to-oil ratio (SOR) in SAGD are major parameters affecting GHG emissions. The developed model can predict the energy consumption and emissions for surface mining and SAGD for oil sands. (C) 2015 Elsevier Ltd. All rights reserved.
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