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Skip to Search Results- 73Graduate and Postdoctoral Studies (GPS), Faculty of
- 73Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 3Renewable Resources, Department of
- 3Renewable Resources, Department of/Journal Articles (Renewable Resources)
- 1Law, Faculty of
- 1Law, Faculty of/Journal Articles (Law)
- 55Department of Civil and Environmental Engineering
- 3Department of Mechanical Engineering
- 3Department of Renewable Resources
- 3Faculty of Nursing
- 2Department of Chemical and Materials Engineering
- 2Department of Computing Science
- 17Deutsch, Clayton (Civil and Environmental Engineering)
- 3Deutsch, Clayton V. (Civil and Environmental Engineering)
- 2Deutsch, Clayton (Mining Engineering)
- 2Jeff Boisvert (Civil and Environmental Engineering)
- 2Li, Zukui (Chemical and Materials Engineering)
- 1 Gan, Thian Yew (Department of Civil and Environmental Engineering)
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Fall 2010
After the scientific problem of interest is defined, collecting data is the first stage of any statistical analyses. The question of how large the sample should be is thus of great interest. In this thesis we demonstrate that in a geostatistical experiment determining the minimum sample size to...
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Accounting for non-stationarity via hyper-dimensional translation of the domain in geostatistical modeling
DownloadFall 2009
Medium and short term mine planning require models of mineral deposits that account for internal geological structures that permit scheduling of mine production at a weekly and monthly production periods. Modified kriging estimation techniques are used for accounting for such geologic structures....
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Addressing Order Relation Issues with Constrained Radial Basis Functions and Consistent Indicator Variograms
DownloadFall 2023
Quantifying uncertainty is a critical task of resource delineation in the mining industry. Uncertainty is used to assess risk in economic evaluation and for classification in resource reporting. The inference of local distributions from conditioning data is key to quantifying uncertainty....
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Fall 2016
Collecting information is of vital importance for the development of a mineral project. The capital costs of mining projects are high and there is significant risk due to the available data. At all stages of a project, from exploration to mine closure, decisions need to be made that are based off...
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Advances in Kriging-Based Modelling Approaches of Winter Weather Vehicular Collisions – A Region-Wide Geostatistical Investigation
DownloadFall 2021
The winter season is known for brisk cold weather and beautiful snowfalls, but it is also known for deteriorated driving conditions to where the risk of collisions becomes a major issue that plagues many municipalities around the world. As such, agencies are tasked with and strive to prioritize...
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2009-09-03
Broadband technology has captured the attention of many stakeholders throughout the world and is recognized as a “nation building” infrastructure enabling the future economic prosperity and improved living standards for many communities. In 2005, the Alberta government completed a significant...
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An overview of soil heterogeneity: quantification and implications on geotechnical field problems
Download2003
Elkateb, T., Chalaturnyk, R., Robertson, P. K.
Abstract: Engineering judgment and reliance on factors of safety have been the conventional tools for dealing with soil heterogeneity in geotechnical practice. This paper presents a review of recent advances in treating soil variability. It presents the implications of geostatistical techniques...
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Analyzing Scaling Characteristics of Transport Properties Using Particle-Tracking Based Techniques
DownloadFall 2017
Appropriate scale-up provides a critical link between fine-scale heterogeneity descriptions and coarse-scale models used for transport modeling, which is essential for planning and management of subsurface reservoirs. A significant challenge in subsurface flow and transport modeling is to develop...
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Fall 2023
Calculating and modeling a variogram from sparsely sampled data can be complex and time-consuming due to the need for expertise in selecting the appropriate parameters and fitting functions to the experimental variogram. To assist with variogram modeling, a novel approach based on Convolutional...