Integration of Machine Learning with Distributed Temperature and Acoustic Sensing to Build Data-Driven Dynamic Reservoir Model

This project will develop practical workflows, algorithms and programming codes for inferring unknown reservoir properties from distributed temperature and acoustic sensing data. In-situ pressure and flow conditions can be interpreted from downhole fiber signals gathered in real time, which are used to estimate unknown heterogeneous reservoir parameters continuously. Machine learning methods will be incorporated to facilitate the handling of large amount of measured data and computations more efficiently.

Ultrasonic Power Transmission and Data Communication through Metallic Barriers for Non-Destructive Testing in Hazardous Industrial Spaces

The need to inspect harsh environments and confined spaces is present in virtually all industries. Inspecting these industrial facilities are key to optimize operation and maintenance costs. Hazardous industrial spaces (e.g., confined spaces) are among the most challenging and costly areas to inspect. In BC alone, over the last decade, WorksafeBC has reported about 18 fatalities per year as the result of operation in confined spaces. To mitigate the risks, remote monitoring and inspection is an attractive alternative to conventional methods.

Use of a deep passive source extremely low frequency (ELF) conductivity mapping system to improve the definition of ore bodies at depth - Applications to Bathurst, NB

The Bathurst Mining Camp, located in northern New Brunswick, is one of Canada's oldest mining districts. Most of the 46 known deposits were discovered in the 1950s using a combination of geological and geophysical methods.

Microfluidics Study of Three-Phase Non-Equilibrium Phase Behavior

CO2 management have been an important research theme to minimize the GHG impact on Canadian environment. Enhanced oil recovery by injecting CO2 underground is a very efficient way to minimize the CO2 environmental effect. Meanwhile, after primary and secondary production, either CHOP or CHOPS well present a high water cut in the produced liquid stream. This high water cut has a significant effect on choosing the proper post-CHO techniques.

Cave to Mill: A Multi-Disciplinary Approach Linking Orebody Knowledge, Footprint Reliability and Sensor-Based Sorting to Improve Safety and Productivity

The proposed research project aims to develop and verify new technologies and numerical tools directed at six main research focus areas: 1. Orebody Knowledge, 2. Grade Management, 3. Cave Mine Design, 4. Integrated Cave-to-Mill, 5. New Measurement Technologies, and 6. Hazard Management. This project will also see the establishment of a multidisciplinary research network, the International Caving Research Network, to be directed at maintaining Canada’s competitiveness in the international mining industry.

Arsenic solubility and its mechanism from DST glass arsenic product; an arsenic solubility study and comparison with other stable arsenic minerals (scorodite, encapsulated scorodite, and calcium arsenate)

The project focuses on the evaluation of the arsenic-containing glass material that the new Dundee Sustainable Technologies (DST) process produces. The idea is to evaluate the stability of arsenic in the material, and through a feedback process to DST improve the quality of the process for the production of arsenical materials.

Selective recovery of Ni-Co-Mn in sulfate media, and graphite from spent Lithium Ion Batteries

In recent years the lithium consumption for batteries has remarkably increased because of the extensive applications of rechargeable lithium batteries in portable electronic devices, electric tools, electric vehicles, and grid storage. The surging demand for these applications asks for innovative solutions for recycling of the spent lithium ion batteries.

Geometallurgical Simulation and Multicriteria Risk Evaluation

The evaluation of mining projects depends on modern computational techniques. There is a demand for increasingly sophisticated techniques, due to environmental considerations and the drive toward increasingly complex ores. Without these techniques, projects may be wrongfully held back or abandoned, leading to severe socioeconomic consequences in the surrounding communities. Conversely, mining projects may be wrongfully approved, causing unfortunate environmental and socioeconomic consequences.

Arctic-Nesting Bird Monitoring and the Impacts of Mining Disturbances

Agnico Eagle Mines Ltd. has proposed the Whale Tail Project, approximately 130km North of Baker Lake, NU. The project includes the construction a dyke within Whale Tail Lake that will divert water from the proposed mining pit into the surrounding lakes and tributaries, resulting in flooding that will elevate the water levels by 4 m above current levels over two years, causing approximately 157 ha of tundra to become flooded during the time of birds? nest initiation.

Development of an Autonomous Pipeline Control System

Autonomous operation of oil and gas pipelines is being introduced to the marketplace by utilizing advanced process control and Artificial Intelligence. This Project will explore the use of advanced optimization algorithms in combination with autonomous operation to further increase efficiency of pipelines by continually driving pumps, compressors and valves to achieve the lowest cost operation.
Expected benefits of these efficiencies will be to increase the effective pipeline capacity without building new pipelines, while reducing the amount of energy required in a pipeline’s operation.