Critical Minerals Geoscience and Data Initiative’s federal research and development
Geoscience to unlock Canada’s critical minerals potential
Led by the Geological Survey of Canada, the federal research and development (R&D) component of the Critical Minerals Geoscience and Data (CMGD) Initiative is securing Canada’s future as a trusted, sustainable, and globally competitive producer of critical minerals. By fostering innovation, leveraging modern technologies and aligning with policy and industry needs, we are providing industry with modern tools, models and knowledge to de-risk exploration and shape the next era of responsible mineral resource development in Canada.
The CMGD Initiative’s federal R&D component focuses on 4 research solutions to define Canada’s critical minerals potential:
Solution 1: Critical minerals knowledge base
This is a comprehensive sampling and analysis program to identify and define critical minerals contents and associations within Canada’s mineral deposits and derivative products – including ores, concentrates, minerals, tailings, and waste materials. This free, publicly available knowledge base will be used to:
- explore new critical minerals sources in existing mines, wastes and deposit types
- inform potential value and supply options from new or emerging sources
- provide new geoscience data and refine analytical methods to trace critical minerals through supply chains
- support robust mineral potential mapping under solution 3
Solution 2: Critical minerals system studies
The purpose of this solution is to conduct thematic geoscience research focused on both conventional as well as new, emerging, or unconventional sources of critical minerals. This research aims to deepen our understanding of Canada’s critical minerals potential and optimize value from new and existing resource streams. Specifically, it will:
- generate predictive models for Canada’s mineral deposit types to inform mineral potential mapping under solution 3
- study potential critical minerals co-products or by-products that could enhance feasibility of Canada’s current mines and accelerate production timelines for new sources
- examine new, emerging or unconventional critical minerals sources with the greatest potential for rapid development
Solution 3: Advanced predictive geoscience
This solution aims to use advanced analytics to develop the next generation of mineral potential models and maps to support “green” critical minerals exploration, production, and decision-making. It will evaluate geological potential, coupled with infrastructure and environmental, social, and governance (ESG) factors, early in the exploration cycle to reduce exploration risks or conflicts and accelerate project development. These free and publicly available datasets will:
- develop mineral intelligence by combining geology, geochemistry, and geophysics data, with production metrics, capital and operating costs, infrastructure access (roads, rail, power, shipping) and ESG factors
- leverage datasets and insights gained from solutions 1 and 2 to develop national-scale critical minerals potential maps
One of the projects developed in support of solution 3 is the Geospatial environmental, social and governance (ESG) ratings tool. This tool helps identify regions where ESG factors may be the most favourable for exploration – factors that increasingly impact critical minerals supply chains. Explore our interactive Application Programming Interface and learn more about ESG ratings and uncertainty values that can guide informed decision-making in critical minerals development.
Solution 4: Market assessments
Building on the outcomes of solutions 1 to 3, this research will strengthen Canada’s future potential in the global critical minerals economy by developing mineral criticality assessments from both consumer and supplier perspectives. These assessments will:
- compile data on exploration, production, exports, imports, consumption, and dependency on foreign sources for critical minerals
- be robust, updatable, and reflect the needs of Canadian consumers and suppliers
- integrate market intelligence and commodity forecasts
- guide updates to Canada’s critical minerals list
Under Canada’s CMGD Initiative, there is also a contribution funding stream to support critical minerals research led by provincial and territorial governments and agencies. Visit the CMGD Initiative page for more information.
Objectives
Short term objectives
- Deliver public geoscience data on Canada’s critical minerals potential, focusing on both conventional sources (e.g., established base and precious metal deposits) and unconventional sources (e.g., waste rock, tailings, and oil field brines)
- Develop innovative applications of artificial intelligence and machine learning to support national-scale models and assessments of critical minerals potential
Medium term objectives
- Enhance data assets and modelling of Canada’s critical minerals sources to identify prospective regions that align with positive ESG factors while strengthening value chains
- De-risk exploration activities by providing access to accurate, up-to-date data and models for informed decision-making
- Conduct national-scale geoscientific characterizations of critical minerals potential, inclusive of ESG factors
- Increase awareness among mineral processors about Canada’s critical minerals opportunities
- Improve understanding of the value of critical minerals in mine waste as a potential source of critical minerals
Long term objectives
- Develop robust critical minerals expertise within Canada to reduce reliance on foreign supply chains
- Accelerate access to national and international markets for Canada’s key critical minerals
- Promote responsible critical minerals exploration in Canada by ensuring access to accurate, up-to-date data and models for informed decision-making
- Deliver world-class geoscience for the public good, reducing risks for both public and private sector investments and enhancing Canada’s critical minerals resource competitiveness
Research and data
Mineral potential maps
- A new open-source workflow in R for prospectivity modelling using public geoscience of magmatic nickel–copper–platinum group element deposits
- Integration of public geoscience datasets using a discrete global grid system to model the mineral potential for Mississippi Valley–type zinc-lead deposits
- Integration of public geoscience datasets using a discrete global grid system to model the mineral potential for clastic-type zinc-lead deposits
- National-scale prospectivity models for Initiative carbonatite-hosted rare earth elements +/- niobium deposits generated through machine learning techniques; the models reduce the search area by 80%, while predicting all known occurrences
- Applications of generative adversarial networks, natural language processing, and convolutional neural networks to generate national mineral prospectivity models for lithium in pegmatites
- National-scale mineral potential model of graphite deposits and occurrences in Canada, constructed using a deep ensemble method with robust uncertainty propagation using geodata science
- A new compilation of the best available maps across Canada to support applications of artificial intelligence and machine learning for mineral potential modelling
Additional research
- An Implicit Neural Network Approach to Three-Dimensional Geological Modelling
- Applications of Natural Language Processing to Geoscience Text Data and Prospectivity Modeling
- Mapping Canada’s Green Economic Pathways for Battery Minerals: Balancing Prospectivity Modelling With Conservation and Biodiversity Values
- Geoscience Language Models and Their Intrinsic Evaluation
- Spatial Interpolation Using Machine Learning: From Patterns and Regularities to Block Models
- Workflow-Induced Uncertainty in Data-Driven Mineral Prospectivity Mapping
- A Deep Learning Benchmark for First Break Detection from Hardrock Seismic Reflection Data
- A Data-Driven Approach for Exploring Unconventional Lithium Resources in Devonian Sedimentary Brines, Alberta, Canada
- Denoising of Geochemical Data using Deep Learning–Implications for Regional Surveys
- Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium
- Prospectivity Modeling of Devonian Intrusion-Related W–Mo–Sb–Au Deposits in the Pokiok Plutonic Suite, West-Central New Brunswick, Canada, Using a Monte Carlo-Based Framework
- Class Label Representativeness in Machine Learning-Based Mineral Prospectivity Mapping
- Checking the Consistency of 3D Geological Models
For a complete list of internal CMGD Initiative research activities, please refer to the list of proposed sub-activities for 2023–2024.
A complete list of 2024–2025 research activities will be published soon.
Contact us
For further information, please send an email to the CMGD Initiative Coordination Office, at cmgd-gdmc@nrcan-rncan.gc.ca.