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- 1Alshehri, Naeem S.
- 1Babakhani, Mahshid
- 1Barnett, Ryan M.
- 1Black, Warren E
- 1Boisvert, Jeff
- 1Chiquini, Ana P
Results for "supervisors_tesim:"Deutsch, Clayton (Civil and Environmental Engineering)""
Constraining 3D Petroleum Reservoir Models to Petrophysical Data, Local Temperature Observations, and Gridded Seismic Attributes with the Ensemble Kalman Filter (EnKF)Download
A methodology based on the Ensemble Kalman Filter (EnKF) is proposed for petroleum reservoir characterization, using continuous integration of petrophysical core data, reservoir temperature observations, and gridded time-lapse acoustic impedances. The localization of updating and covariance...
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...
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...
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...
Long term mineral resources modeling is done to predict tonnage and grade of ore that may be mined and represents a key feature in the development of any mining project. The most common approach used in the mining industry is to estimate the grades using ordinary kriging and report the...
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...
Geostatistical techniques are used to estimate recoverable reserves at unsampled locations and to quantify uncertainty. Several variables are often measured and important for reserve evaluation. Using more variables improves the quality of modeling, but quantifying the relationships between the...
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...
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...
Improved numerical reservoir models are constructed when all available diverse data sources are accounted for to the maximum extent possible. Integrating various diverse data is not a simple problem because data show different precision and relevance to the primary variables being modeled,...