Development of an agent-based model to assess the industry-induced impacts on woodland caribou habitat selection and use in Alberta.

The objective of this project is to develop a computational simulation model designed to determine how the resource-extraction industries of oil, gas and forestry influence woodland caribou (Rangifer tarandus) habitat selection and use in west central Alberta. Specifically, an agent-based model will simulate caribou as individual agents that 1) are capable of making trade-off decisions to maximize their reproductive success and survival, 2) are spatially aware of their surrounding environment, and 3) can learn where to forage, while concurrently avoiding predators and habitat disturbance.

Reliability Based Design Framework for High Strength Linepipe

The internship objective is to establish a reliability based design framework for high strength linepipe subject to internal pressure, axial force and end moment for monotonic loading conditions. Linepipe grade material with specified minimum yield strength (SMYS) equal to or greater than Grade 550 (X80) is defined as high strength linepipe. The mechanical performance design criteria will be established through the development, calibration and validation of numerical modeling procedures such as finite element.

Full Waveform Tomography for Time-Lapse Monitoring

Oil and gas resources are hidden deep within the earth in geological structures which form reservoirs for these fluids. Finding these reservoirs, and monitoring the flow of fluids within these structures requires advanced imaging technologies and algorithms for the successful recovery of these valuable resources. This project will develop a newly proposed mathematical approach to imaging these structures, known as full wavefield tomography (Brenders and Pratt, 2007).

Optimal Landfarming Strategy for Treating Oil Refinery Sludge

In this project, a comprehensive review of relevant literature and case studies regarding landfarming of oily sludge will be conducted, and the optimal landfarming operation strategies will be proposed. A number of field experiments will be implemented to examine the impacts of different environmental factors on microbial activity. Specifically, the impacts of bulking agents and nutrients on bioremediation efficiency will be investigated through sludge landfarming at various experimental plots, while the method of factorial design will be used to design such experiments.

Development of a Temperature-dependant Elastoplastic Constitutive Model for Metals and Alloys

The test characterization of the stress-strain relationship and the fatigue/failure behaviour under combined mechanical-thermal cyclic loadings for pressure vessels in the petrochemical industry is quite expensive and time consuming. An alternative approach is the finite element numerical analysis which requires an accurate and reliable mathematical constitutive model for the metallic materials. In this project, a temperature-dependent elastoplastic material model will be developed.

FOCI and its Implementation in Industry

Geo-X Processing, Divestco Inc., a Canadian seismic processing contractor, is seeking to enter a new segment of the market, the so-called “depth imaging” market, by Q3 2007. The company is currently developing a comprehensive suite of depth imaging algorithms aimed at competing in the above market, but currently lacks a certain sophisticated tool. Such a tool has been recently developed at the University of Calgary, called the “FOCI algorithm”.

Geostatistical Modelling of Variability and Uncertainty for Natural Attenuation at Upstream Oil & Gas Contaminated Sites

The intern will work on quantifying inherent uncertainties associated with natural attenuation of organic contaminants at upstream oil and gas contaminated sites. Uncertainty and variability in parameters such as hydraulic conductivity, biodegradation rate constant and spatial distribution of the source of contaminants may lead to highly uncertain results to be obtained from routine fate and transport models. Thus, there is a need to quantify these uncertainties and study their impact on the predicted plume size and clean up time.

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