Performance Evaluation of Solvent Co-Injection Scenarios in Steam Assisted Gravity Drainage (SAGD)-Based Bitumen Recovery

ConocoPhillips Canada (CPC) is evaluating transformational technologies to reduce GHGs by up to 90% allowing for efficient Alberta resource development on a per barrel and supply cost basis in a carbon-constrained, globally competitive market. Warm applied solvent process refers to pre-heated solvents that are injected/co-injected with steam as an elimination/evolution of the current Steam Assisted Gravity Drainage (SAGD) process for bitumen mobilization which provides potential for absolute emission reductions.

Development of Adaptive Fault and Anomaly Detection for Industrial Processes and the Application of Reinforcement Learning (RL) for Automatic Fault Recovery

The Operational Excellence (OpEx) team at Spartan Controls is actively involved in several initiatives for developing advanced process control (APC) solutions to the oil sands industry. The OpEx team collaborates with Professor Biao Huang’s research group through the NSERC Industrial Research Chair (IRC) in the Control of Oil Sands Processes program for solutions that require extensive research and development. This proposed project will complement the on-going joint research efforts with the development of new data analysis techniques to address the APC problems.

Investigation of CO2 phase behavior in flowlines for CCS processes

Carbon capture and sequestration (CCS) is a practical solution for reducing the overall green house gas (GHG) emission and environmental footprint of the civilization. The CoFlow simulation software developed by CMG is one of the only tools available for predicting the performance of the CCS applications. Generally, there are technical challenges and prediction deficiencies associated with processes involving injection of high-pressure CO2.

Stationary methanol steam reforming to hydrogen fuel for fuel-cell filling stations

Renewable hydrogen (H2) carriers such as methanol (MeOH) can be reformed back into H2 and is a fundamental chemical conversion for the long-term viability of the H2 economy due to its high density and ease of transportability compared to H2. MeOH is an especially important carrier as it is a simple C1 chemical that can be produced from solar-PV-generated H2 and direct-air-captured CO2 with a current commercially practical solar-to-fuel efficiency of 10% from renewable solar energy.

Understanding Energy Use in Comminution

This project will be used to assist the mining industry in predicting the best possible practices for designing and operating mines. By developing an understand of how comminution tests represent the machinery we can predict what is required to breakdown the raw rocks from the ground into valuable products we can make mining both more economical and more environmentally sustainable.

Methane Assisted Catalytic Upgrading of Extra Heavy Crudes under Moderate Conditions

Vacuum residue (VR) is the heaviest part of crude oil accounting for a large proportion in modern refineries, while its utilization routes are generally of low efficiency and high energy intensity, and thus economically and environmentally unfavorable. Similarly, bitumen recovered from Steam-assisted gravity drainage (SAGD) process experiences high viscosity and density as well as high content of impurities and thus diluent is often needed for its transportation with additional cost and environmental concerns.

Development of an eco-friendly adsorbent for selective removal of selenium in uranium mining wastewater

While the benefits of uranium production bring economic and strategic advantages for Saskatchewan and Canada, the legacy of its tailings, waste rocks, flooded mines, and industrial wastewaters are the drawbacks. To safeguard both human and environmental health, the mining waste streams need to be treated prior to their release to the environment. The current research project aims to use agricultural residue-based materials (e.g., wheat and canola straws) as a cost-effective and eco-friendly alternative to the more expensive commercial adsorbents for removal of selenium from mining wastewater.

Trash Is Cash: Applying machine learning to optimize the utilization of crop and forest residues in rural communities

Around 4 billion tonnes per year of crop and forest residues (biomass) are burned in open air, because they are often loose, wet, bulky, and too expensive to collect and centralize for subsequent conversion into useful products. This results in air pollution, and in some cases, exacerbated wildfires. In this project, we are applying machine learning and optimization techniques to coordinate a new class of small-scale, low-cost, decentralized bioconversion systems capable of rural, decentralized deployment.

Fabrication of Smart Clothing: From Machine Learning Approach to Fashion Design Concepts

Nowadays, wearable devices attract a lot of attention, especially in the healthcare field. But translating all devices to wearable devices always comes with challenges. Some of the challenges are lack of knowledge about the application of different materials in smart textiles, limitation of developed smart textiles in practical application, no significant dedication in designing clothing by considering the limits, etc. So, this proposal is trying to address those gaps.

Microporous polymeric coatings for Li-ion battery electrodes

Lithium-ion batteries (LIBs) are commonly used for electric cars and portable electronic devices. In order to make these devices cheaper, lighter and more accessible, high capacity LIBs are needed. Lithium or silicon are ideal materials for LIBs due to their high specific capacity. However, they cannot be used to substitute the graphite anode in the current commercial LIBs due to the stability issue related to the lithium dendrites growth and the extreme volume change.

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