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Fall 2010
Modeling spatial variables involves uncertainty. Uncertainty is affected by the degree to which a spatial variable has been sampled: decreased spacing between samples leads to decreased uncertainty. The reduction in uncertainty due to increased sampling is dependent on the properties of the...
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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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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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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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Spring 2016
Uncertainty in resource estimation affects long-term development, planning, and investment decisions. Therefore, there is a need to make the best decisions considering all available data and different modeling approaches. This thesis develops a conceptual framework for resource modeling with...
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Spring 2010
A reliable estimate of the amount of oil or gas in a reservoir is required for development decisions. Uncertainty in reserve estimates affects resource/reserve classification, investment decisions, and development decisions. There is a need to make the best decisions with an appropriate level...