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Skip to Search Results- 16Deutsch, 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)
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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Geostatistical Reservoir Modeling with Parameter Uncertainty in Presence of Limited Well Data
DownloadSpring 2017
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...