کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6687677 501882 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Energy consumption and greenhouse gas emissions in the recovery and extraction of crude bitumen from Canada's oil sands
ترجمه فارسی عنوان
مصرف انرژی و انتشار گازهای گلخانه ای در بازیابی و استخراج قیر خام از ماسه های نفتی کانادا
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
چکیده انگلیسی
A model - FUNNEL-GHG-OS (FUNdamental ENgineering PrinciplEs-based ModeL for Estimation of GreenHouse 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 gCO2eq/MJ of bitumen and 8.0 to 34.0 gCO2eq/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 SAGD. 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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 143, 1 April 2015, Pages 189-199
نویسندگان
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