Parallel Computing Solutions for Modelling Large Volume Geoelectrical Data Utilizing Unstructured Meshes

This project will develop computer modelling methods for geoelectrical data that are collected in geophysical surveys. Such data can be used to infer information about electrical properties in the Earth’s subsurface, and subsequently provide information about mineralization, groundwater pollution pathways, water intrusion through flood barriers, and various other important processes. It is ever more common that large volume geoelectrical datasets are collected. Although these have the potential to provide improved information about the subsurface, they pose particular challenges for computer modelling. The general objective of this project is to develop new computationally feasible computer modelling approaches for working with large volume geoelectrical data. To reach that objective, we will investigate use of unstructured meshes, parallel programming and data sampling/compression methods, among others. This project will develop powerful and sophisticated geoelectrical modelling software that will have the potential to benefit Canada though its use in resource exploration and many other applications.

Faculty Supervisor:

Peter Lelièvre;Colin Farquharson

Student:

Hormoz Jahandari

Partner:

DIAS Geophysical

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Program: