Development of Optimal Energy Infrastructures for the Oil Sands Industry in a CO₂-constrained World

Western Canadian bitumen is becoming a predominant source of energy for North American markets. The bitumen extraction and upgrading processes in the oil sands industry require vast quantities of energy, in the form of power, H2, steam, hot water, diesel fuel, and natural gas. These energy commodities are almost entirely produced using fossil feedstocks/fuels, which results in significant CO2 atmospheric emissions. CO2 capture and storage (CCS) technologies are recognized as viable means to mitigate CO2 emissions. Coupling CCS technologies to H2 and power plants can drastically reduce the CO2 emissions intensity of the oil sands industry. The CO2 streams from such plants can be used in Enhanced Oil Recovery, Enhanced Coal Bed Methane, and underground CO2 storage. The above CO2 sinks currently exist in Alberta and roughly half of its territory is deemed suitable for geological storage of CO2. This study investigates the relationship between energy demands, energy costs and CO2 emissions associated with current and proposed oil sands operations using various energy production technologies. Accordingly, two computer models have been developed to serve as energy planning and economic optimization tools for the public and private sectors. The first model is an industry-wide mathematical model, called the Oil Sands Operations Model (OSOM). It serves to quantify the demands for power, H2, steam, hot water, process fuel, and diesel fuel of the oil sands industry for given production levels of bitumen and synthetic crude oil (SCO), by mining and/or thermal extraction techniques. The second model is an optimal economic planning model for large-scale energy production featuring CCS technologies to reduce CO2 emissions in the oil sands industry. Its goal is to feasibly answer the question: What is the optimal combination of energy production technologies, feedstocks, and CO2 capture processes to use in the oil sands industry that will satisfy energy demands at minimal cost while attaining CO2 reduction targets for given SCO and bitumen production levels? In 2003, steam, H2, and power production are the leading sources of CO2 emissions, accounting for approximately 80% of the total emissions of the oil sands industry. The CO2 intensities calculated by the OSOM range from 0.080 to 0.087 tonne CO2 eq/bbl for SCO and 0.037 tonne CO2 eq/bbl for bitumen. The energy costs in 2003 are $13.63/bbl and$5.37/bbl for SCO and bitumen, respectively. The results from the OSOM indicate that demands for steam, H2, and power will catapult between 2003 and 2030. Steam demands for thermal bitumen extraction will triple between 2003-2012 and triple again between 2012-2030. The H2 demands of the oil sands industry will triple by 2012 and grow by a factor of 2.7 thereafter. Power demands will roughly double between 2003 and 2012 and increase by a factor of 2.4 by 2030. The optimal energy infrastructures featured in this work reveal that natural gas oxyfuel and combined-cycle power plants plus coal gasification H2 plants with CO2 capture hold the greatest promise for optimal CO2-constrained oil sands operations. In 2012, the maximum CO2 reduction level attainable with the optimal infrastructure is 25% while in 2030 this figure is 39% with respect to “business as usual” emissions. The optimal energy costs at maximum CO2 reduction in 2012 are $21.43/bbl (mined SCO),$22.48/bbl (thermal SCO) and $7.86/bbl (bitumen). In 2030, these costs are$29.49/bbl (mined SCO), $31.03/bbl (thermal SCO), and$10.32/bbl (bitumen). CO2 transport and storage costs account for between 2-5% of the total energy costs of SCO and are negligible in the case of bitumen. The optimal energy infrastructures are mostly insensitive to variations in H2 and power plant capital costs. The energy costs are sensitive to changes in natural gas prices and insensitive to changes in coal prices. Variations in CO2 transport and storage costs have little impact on SCO energy costs and a null impact on bitumen energy costs. Likewise, all energy costs are insensitive to changes in the length of the CO2 pipeline for transport

The techno-economics of alternative CO2 transport systems and their application in the Canadian oil sands industry

AbstractThe rise in GHG emissions from the oil sands industry has prompted government and industry to seek ways to reduce its CO2 output. CCS is currently the leading option in Alberta. A key to making it viable is a system that allows multiple emitters to gather, capture, and transport their CO2 to the best sinks, efficiently and economically. The oil sands are located in Northern Alberta. Geological formations suitable for CO2 storage exist in the South-West region, ∼400 km from the sources. Implementing CCS will necessitate transporting roughly 30 megatonnes of CO2 to suitable sinks. One of the best sinks is the underground aquifer in the Redwater Reef near Ft. Saskatchewan, with an estimated preliminary capacity of one gigatonne of CO2, or 37 years of CO2 emissions from oil sands, at 2007 rates. In this study, we compare two schemes to transport CO2 from oil sands operations by capturing CO2 and: (1) transporting it in its supercritical state to storage in the Redwater Reef and (2) transporting it in solution to Redwater, regenerating the solvent on-site and storing the CO2 in the Redwater Reef.The fugitive emissions of Case 1 are consistently higher than those of Case 2. This is due to the former’s electricity demands and the fact that the emissions associated with energy for solvent regeneration are not captured. Case 1 is more susceptible to electricity cost fluctuations than Case 2, but the latter is more susceptible to changes in the price of fuel. Although the CAPEX is similar for both, Case 2 benefits more from economies of scale than Case 1; the OPEX for Case 1 is 3.5% higher. The avoidance costs of Case 2 are lower on a gross basis (111 vs. 114 $/tonne CO2) and on a net basis (327 vs. 851$/tonne CO2)

Optimizing energy production with integrated CCS technology for CO2 emissions mitigation in the Canadian oil sands industry

AbstractThe forecasted energy production of oil sands operations in Alberta in the year 2030 were optimised under CO2 emissions constraints, using a mixed integer linear optimisation model. The model features a variety of technologies (with and without CO2 capture), including coal and natural gas power plants, IGCC, and oxyfuel plants. Hydrogen production technologies are steam methane reforming and coal gasification. The optimization is executed at increasing CO2 emissions reduction levels, yielding unique infrastructures that satisfy the energy demands of the oil sands industry at minimal cost. The economic and environmental impacts of the optimally chosen technologies on the forecasted operations of the oil sands industry in 2030 are thus determined.The maximum CO2 emissions reduction attainable by using CCS in the oil sands industry in 2030 is 39% with respect to a business-as-usual baseline. This CO2 reduction results in an energy cost increase of roughly 20% for synthetic crude and 2% for bitumen production. CO2 reductions ranging from 0–35% can be attained by optimising the energy infrastructures, yielding energy production cost reductions between 9%–18%. The maximum CO2 intensity reduction is 46% for synthetic crude and less than 3% for bitumen. Energy conversion and CO2 capture account for the bulk of the energy costs for synthetic crude whereas transport and storage combined contribute between 2.6% and 5% over the entire range of CO2 reductions.The optimal energy production technologies are strongly dependent on the CO2 reduction targets. Power production without capture, predominantly NGCC and supercritical coal technology, is optimal at CO2 reduction levels of up to 30%. At higher CO2 reductions, only NGCC with capture and Oxyfuel plants are optimal. H2 production via coal gasification is optimal for CO2 reduction levels of 35% and lower. Above 35% reduction, steam methane reforming with capture is the dominant technology

Algae-dewatering using rotary drum vacuum filters: Process modeling, simulation and techno-economics

Clean and energy-efficient rotary drum vacuum filtration was selected to conduct algae-dewatering. The dynamic formation of an algal cake-layer on the filter surface was modeled by correlating the cake-layer permeability to the physical parameters of algae and cake-layer. The compressibility of algal cake-layer was taken into consideration in the modeling, and its effect on the algae-dewatering is discussed.The dewatering process was simulated to determine the process energy demand. Process economics were assessed considering the dewatering cost, which includes capital investment and energy cost and also labor, installation, maintenance and infrastructure. Optimal operating conditions and minimum dewatering cost were achieved by process optimization, and two cost-sensitive zones in operating the filtration were identified. The techno-economics showed that the dewatering cost can be further reduced by scaling up the process.Peer reviewed: YesNRC publication: Ye