AI & Natural Resources

The natural resource sector is witnessing a major transformation from being data-poor to data-rich, creating a new mining research frontier. The mining sector has traditionally been risk-averse and slow to adopt new technologies. The challenges faced from the scarcity of high-grade mineral deposits, declining productivity and tightened regulatory conditions have created an impetus for change and innovation in this sector. Embedding data analytics, decision making support and autonomous operations into mining operations creates an opportunity for a transformation across the mining value chain. Artificial intelligence and its diverse sub-fields are swiftly integrating into all phases of mine lifecycle, from mineral exploration and discovery, to mine development and production and finally mine reclamation.

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Shared Interests:

The strength of this group is together they represent a new strategic mining research paradigm at UBC by shifting focus from traditional areas of communication, rock mechanics and mineral processing to new frontiers in data analytics, automation and robotics, advanced process modelling, AI-supported decision making and automation. Our current/prospective portfolio of work blends research and knowledge mobilization using generalized and applied AI.

Exploration & estimation – ML-assisted Target Generation, Visual Computing and AI Classification for Rock Sampling, New Predictive Tools: Matching Historic Exploration Data to Actual, Mine Performance.

Subsurface modelling – ML and Multiple-point Stochastic Simulation for Modeling Geological Heterogeneity, Coupled ML-Geostatistics for Real-Time 4D Data Assimilation, AI-assisted Geometallurgy.

Mine design – Sentiment Analysis for Establishing and Maintaining a Social License to Operate, AI-Assisted Optimization of Resource-Constrained Project Scheduling, Data-enabled Blasting Design and Implementation.

Mine operations - Edge ML, Autonomous Haulage Systems, ML for Adaptive Process Control, Predictive Maintenance.

Mine waste management - Improved Predictive Models of Contaminants and Mitigation Strategies.

Digital readiness of graduates and mining professionals – New AI & Data science courses and Professional Program in Digital Tech and Data Science in Mineral Resource Engineering, Entrepreneurship/ knowledge mobilization, Graduate student scholarships.