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Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 2Harding, Benjamin E
- 2Martin, Ryan
- 1Acorn, Tyler
- 1Amihere, Norris
- 1Barnett, Ryan M.
- 1Barros Ortiz, Rafael
- 16Deutsch, Clayton (Civil and Environmental Engineering)
- 3Deutsch, Clayton V. (Civil and Environmental Engineering)
- 2Deutsch, Clayton (Mining Engineering)
- 2Jeff Boisvert (Civil and Environmental Engineering)
- 1Askari-Nasab, Hooman (Civil and Environmental Engineering)
- 1Askari-Nasab,Hooman (School of Mining and Petroleum Engineering)
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Spring 2013
A common problem in naturally fractured reservoirs (NFRs) is a lack of data caused by few wells; or at least, few wells with core or borehole images. Secondary data (such as seismic) can be used to improve predictions of fracture intensity in between the wells. Common geostatistical techniques...
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Fall 2024
Geostatistical models are often generated with widely spaced data configurations. Data collection costs prohibit exhaustive sampling and necessitate statistical inference from limited samples. Spatial prediction with sparse data in the presence of extreme values is an enduring challenge in the...
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Spring 2010
Many geological deposits contain nonlinear anisotropic features such as veins, channels, folds or local changes in orientation; numerical property modeling must account for these features to be reliable and predictive. This work incorporates locally varying anisotropy into inverse distance...
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Fall 2010
In Geostatistical modelling of the spatial distribution of rock attributes, the multivariate distribution of a Random Function defines the range of possible values and the spatial relationships among them. Under a decision of stationarity, the Random Function distribution and its statistics are...
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Fall 2013
The McMurray Formation contains complex geological features that were partially formed in a fluvial-estuarine depositional environment. These geological features that are interrelated to each other exist with different shapes, patterns, and sizes. The inclined heterolithic strata (IHS) formed as...
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Heterogeneity Consideration and Upscaling of elastic properties in coupled geomechanical flow simulation of SAGD
DownloadFall 2013
Geomechanical processes occurring during steam assisted gravity drainage (SAGD) thermal recovery influence petrophysical and rock mechanical properties of both reservoir and caprock formations. While geostatistical techniques provide multiple equi probable geological realizations for...
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Fall 2011
This dissertation proposes an improved facies modelling methodology that involves a new geological spatial characterization tool, a geological based spatial distance calculation, and a theoretically sound conditional probability calculation. The full set of bivariate probabilities are proposed...
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Spring 2024
Multiple data types should be used simultaneously to improve resource estimation models. The multivariate relationship between the data is required. One common approach involves using decorrelation transformation techniques to simplify complex relationships, but this method relies on having...
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Fall 2020
Multivariate techniques aim to integrate multiple variables and/or data in the same framework to improve uncertainty assessment in high resolution geostatistical models. The necessity to build models that better quantify the uncertainty with limited data that are often collected with different...
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Fall 2014
Considering nonstationary features in geostatistical modeling is important. Recent developments in nonlinear estimation provide a practical way to infuse geological realism into numerical modeling by incorporating complex spatial features. Second order nonstationarity when present must be...