Research and Development



3-D Visualization and Modelling of Subsurface Contaminants Using an Integrated Geophysical Approach

            Project Summary

Geophysical imaging tools have become a regular and valuable part of environmental monitoring throughout Western Canada’s oil/gas sector. Increasingly it is noticed that as the near-surface is better described through geophysical methods, questions of the deeper subsurface are raised.  For instance, in an area which has experienced an oil/gas pipeline break, geophysics has made it a relatively simple task to map out the extent of the contaminated area to depths of a few meters (less than 5 meters) of the surface. However, monitoring wells completed to greater depths frequently suggest that, through a complicated network of non-linear pathways, contaminants have migrated downward and have now impacted the groundwater. Environmental scientists have struggled to explain monitoring well data for lack of information which better describe the subsurface conditions.  Through a combination of geophysical tools and imaging software, AKS proposes to more fully describe the subsurface to meet the needs of the environmental monitoring community, and assist in the protection of natural resources such as ground-water.
Geophysical tools will be used to map detailed stratigraphy/fractures of the shallow subsurface and its effect on contaminant flow. Conductivity, acoustic impedence, and dielectric constant measurements of the subsurface will be mapped using a variety of geophysical methods and studied to create a 3D geological model. Intrusive data such as chemical analysis, hydrogeological parameters, and lithology from boreholes, will be employed in creating a final model depicting stratigraphy, contaminant, presence, and forward modelling of contaminant flow. The resultant 3D geological/contaminant model will help in precise future planning, making the remediation process more efficient both technically and financially.


IRAP2014 Team Results Participants Schedule


This project is partially funded by National Research Council Canada.