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- 1Acorn, Tyler
- 1Barnett, Ryan M.
- 1Black, Warren E
- 1Boisvert, Jeff
- 1Cabral Pinto, Felipe A
- 1Chaikowsky, C.L.A.
- 32Graduate Studies and Research, Faculty of
- 32Graduate Studies and Research, Faculty of/Theses and Dissertations
- 1Helmholtz-Alberta Initiative
- 1Helmholtz-Alberta Initiative/Journal Articles & Research Abstracts (Helmholtz-Alberta Initiative)
- 1Geotechnical and Geoenvironmental Engineering Program
- 1Geotechnical and Geoenvironmental Engineering Program/Journal Articles (Geotechnical & Geoenvironmental Engineering)
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...
Accounting for non-stationarity via hyper-dimensional translation of the domain in geostatistical modelingDownload
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....
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...
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...
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...
Enhanced Geologic Modeling with Data-Driven Training Images for Improved Resources and Recoverable ReservesDownload
Deterministic geologic modeling methods accurately characterize large-scale continuous features of geological phenomena, but often fail in reproducing their inherent short-scale variability. The opposite is the case with stochastic methods that lack large-scale continuity yet contain reasonable...
An important challenge in reservoir management is establishing reliable numerical geological models of all required flow parameters including facies, porosity and permeability. These numerical models are driven by conceptual geology, seismic, production and well data that are widely spaced early...
A challenge in petroleum geostatistics is the application of modeling algorithms such as Gaussian simulation to unstructured grids that are being used for flow simulation. Geostatistical modeling is typically applied on a fine scale regular grid and then upscaled to the unstructured grid. This...
This thesis addresses challenges in geostatistical analyses of multivariate geochemical data that commonly contain complexities that have a significant influence on geostatistical modeling and cluster analysis. For geostatistical modeling, the effect of the most common despiking methods is...
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...