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Permanent link (DOI): https://doi.org/10.7939/R3563M

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Geostatistical modeling of unstructured grids for flow simulation Open Access

Descriptions

Other title
Subject/Keyword
unstructured
geostatistics
flow
uncertainty
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Manchuk, Johnathan Gregory
Supervisor and department
Deutsch, Clayton (Civil and Environmental Engineering)
Examining committee member and department
Boisvert, Jeff (Civil and Environmental Engineering)
Szymanski, Jozef (Civil and Environmental Engineering)
Caumon, Guillaume (Nancy School of Geology)
Mendoza, Carl (Earth and Atmospheric Science)
Department
Department of Civil and Environmental Engineering
Specialization

Date accepted
2010-09-24T16:24:03Z
Graduation date
2010-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
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 work proposes a fine scale unstructured grid. The grid is designed so that its elements align with the flow simulation grid elements, eliminating the occurrence of intersections between the two grids. Triangular and tetrahedral grids are used for the fine scale grid; however, they introduce a variety of element scales. The approach developed in this work populates the fine scale grid based on the scale of conditioning data. The resulting error due to scale discrepancy is quantified and mitigated though the upscaling process. A methodology to assess the error in upscaled properties is developed and used to control the design of the fine scale grid. Populating the fine scale grid with reservoir properties requires modification of existing geostatistical algorithms. The set of spatial locations for modeling is irregular and three differences that result from this are addressed: random path generation; spatial search; and the covariance lookup table. Results are compiled into an algorithm for sequential indicator and sequential Gaussian simulation on irregular point sets. Checking variogram reproduction on large irregular point sets is a challenge. An algorithm that efficiently computes the experimental variogram for these cases is developed. A flow based upscaling method based on the multipoint flux approximation is developed to upscale permeability models from the fine scale unstructured grid to the flow simulation grid. Triangular grids are assumed for the fine scale. Flow simulation results using the upscaled transmissibilities are very similar to results obtained using traditional flow simulation on high resolution regular grids.
Language
English
DOI
doi:10.7939/R3563M
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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