Search
Skip to Search Results- 52Department of Civil and Environmental Engineering
- 4Department of Chemical and Materials Engineering
- 4Department of Electrical and Computer Engineering
- 2Department of Renewable Resources
- 1Department of Educational Policy Studies
- 1Department of Mathematical and Statistical Sciences
- 17Deutsch, Clayton (Civil and Environmental Engineering)
- 3Deutsch, Clayton V. (Civil and Environmental Engineering)
- 2Deutsch, Clayton (Mining Engineering)
- 2Jeff Boisvert (Civil and Environmental Engineering)
- 2Jing, Yindi (Electrical and Computer Engineering)
- 2Stevan Dubljevic (Department of Chemical and Materials Engineering)
-
Data Driven Decisions of Stationarity for Improved Numerical Modeling in Geological Environments
DownloadSpring 2019
Generating representative models of geological domains is critical for decision making and process optimization in natural resource exploitation. Partitioning geological datasets is an important step undertaken early in geostatistical analysis to ensure that subsequent modeling stages consider...
-
Data Driven Decisions of Stationarity for Improved Numerical Modeling in Geological Environments
DownloadSpring 2019
Generating representative models of geological domains is critical for decision making and process optimization in natural resource exploitation. Partitioning geological datasets is an important step undertaken early in geostatistical analysis to ensure that subsequent modeling stages consider...
-
Spring 2021
Different quantities of information are available at various stages of the development of a mining project. Consequential decisions are made given the data available at the time. Geological uncertainty due to sparse data presents economic risks. The collection of additional information reduces...
-
Enhanced Geologic Modeling with Data-Driven Training Images for Improved Resources and Recoverable Reserves
DownloadFall 2015
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...
-
Fall 2019
A numerical reservoir model is the result of studies whose main objective is to describe the dynamic behaviour of a hydrocarbon reservoir for predicting its future performance under different development and production strategies. Reservoir models are built with uncertain parameters. The...
-
Enhancing space modeling and mobile resources planning in construction operations through a simulation driven visualization framework
DownloadFall 2011
Simulation modeling is a strong tool that has not been utilized to its expected potential in day to day construction industry activities. One of the reasons contributing to that is the inability of simulation models to depict changes in site space in an intuitive way. This research tries to...
-
Estimation, Soft Sensing and Servo-control of Linear Distributed and Lumped Parameter Systems
DownloadFall 2021
State-of-the-art advancements in the realm of industrial process control and monitoring often require accurate descriptions of complex processes and their dynamical behaviours. Usually, many industrial processes are described by partial differential equations (PDE) or ordinary differential...
-
Spring 2020
Geostatistical modeling used to focus on the grade of the main commodity or metal being mined and sold for profit. As mining has developed, the metallurgical characteristics of the rock have become important. Geometallurgy tests are developed to understand the processing characteristics of the...
-
Fall 2023
In general, less than one billionth of the volume of a deposit is sampled before production decisions. The grades and other rock properties are estimated in the unsampled volume. The success of a mine is dependent on accurate grade control. The grade control process establishes the final planned...
-
Fall 2010
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...