Correlation of the data from automated core characterization, including mineralogical characterization, with geoenvironmental laboratory tests using artificial intelligence (AI) methods

The main objective of this project is a comprehensive methodology that combines automated core characterization and AI methods to accurately forecast the geoenvironmental parameters of a deposit. By developing predictive models, this approach will enable the creation of a 3D geoenvironmental block model for the targeted deposit. This model will facilitate the prediction and optimization of future plant performance and the management of mine waste. Therefore, It will not only improve the efficiency and environmental performance of the industrial partner but will also be cost saving. In addition, the canadian community will be benefit from this research in term of economic development, environmental protection, innovation and education.

Faculty Supervisor:

BenoÎt Plante

Student:

Partner:

Agnico Eagle Mines Limited

Discipline:

Engineering

Sector:

Mining

University:

Université du Québec en Abitibi-Témiscamingue

Program: