Developing a Multivariate Geostatistical Simulation Approach based on Point Cloud Morphing

The demand for minerals, precious metals, and non-ferrous metals will increase in the next decades to satisfy the demand from the energy, automobile, technology, and construction sectors. To meet that demand, mining companies are mandated to extend the life of current projects while exploring for new deposits. This is faced with new challenges: lower-grade deposits, and more complex mineral/metal recovery performances. This requires new methods to simulate ore deposits that can capture and reproduce complex relationships between the rock properties, since these are important in downstream processes. In this context, this project will research a new multivariate modelling technique to capture complex relationships, allowing geostatisticians to handle high-dimensional datasets for resource modelling purposes. This has positive impacts in the mine plans and plant performances. The partner organization will be benefited by pioneering applications of this new method, along with guiding and supporting its development.

Intern: 
Sebastian Alejandro Avalos Sotomayor
Faculty Supervisor: 
Julian Maximiliano Ortiz Cabrera
Province: 
Ontario
University: 
Partner University: