Using Machine Learning to locate geological deposits

Saskatchewan Polytechnic (SP)’s Digital Integration Centre of Excellence (DICE) and geological experts at Peter Lucas Project Management Inc. (PL) will collaborate on the development of a digital system to locate aggregate sources with a large gravel content. Gravel is a non-renewable resource that is used in almost every aspect of construction. The identification of sources of gravel and the corresponding management of it is important to many different industries. The project will examine the use of machine learning (ML) and or neural network algorithms to determine the probability of a location on a map containing gravel. This resulting technology can help find more sources, will increase supply, save costs, and reduce greenhouse gases due to minimized hauling. The work done in this project expands on previous collaborations between SP DICE and PL that have shown promise.

Faculty Supervisor:

Terry Peckham;Lizeanne St. Pierre

Student:

Partner:

Peter Lucas Project Management

Discipline:

Computer science

Sector:

Mining

University:

Saskatchewan Polytechnic

Program: