Jeff Boisvert, PhD, PEng
Contact
Professor, Faculty of Engineering - Civil and Environmental Engineering Dept
- jbb@ualberta.ca
Overview
Area of Study / Keywords
Professor Mining Engineering Wildland Fire Management
About
Research
Research Interests
- Geostatistical modeling of nonstationary domains.
- Geostatistical models for environmental applications including CO2 sequestration and storage.
- Geostatistical models for temporal data.
- Use of numerical models in mine planning.
- Integration of multivariate data sets in numerical modeling.
- Spatial modeling of variables that impact wildland fires and help in prediction.
- Automated wildland fire hazard and triage assessments.
- Fire growth modeling.
Research Currently in Progress
- Reproduction of non-linear geological features such as channels, veins, complex folding, etc. This research uses the shortest path distance to integrate non-stationary anisotropy.
- Generation of anisotropy fields from available data such as point measurements, surfaces, interpreted volumes or geological analogues.
- Selection and use of training images with multiple point simulation algorithms.
- Assessment of variable importance with geometallurgical data (often >100 variables).
- Wildland fire management using remotely collected data from drones, observers, and satellites to improve decision making.
Courses
MIN E 295 - Introduction to Mining Engineering
Mining concepts and terminology, company operations, stages of mining, unit mining operations, surface and underground mine development and methods, feasibility studies and mine costs, ethics, equity, sustainable development and environmental stewardship, public and worker safety and health considerations including the context of the Alberta Occupational Health and Safety Act.
MIN E 612 - Principles of Geostatistics
Geostatistical methods are presented for characterizing the spatial distribution of regionalized variables. The theory of random variables and multivariate spatial distributions is developed. This class focuses on the quantification of spatial variability with variograms, estimation with kriging, and simulation with Gaussian techniques.