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Permanent link (DOI): https://doi.org/10.7939/R33P46

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Quantification of reservoir uncertainty for optimal decision making Open Access

Descriptions

Other title
Subject/Keyword
resource
finite
uncertainty
bootstrap
conditional
spatial
model
parameter
HIIP
reserve
hydrocarbon
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Alshehri, Naeem S.
Supervisor and department
Cunha, Jose Carlos (Petrobras America Inc.)
Deutsch, Clayton (Civil and Environmental Engineering)
Examining committee member and department
Leuangthong, Oy (Civil and Environmental Engineering)
Lipsett, Michael (Mechanical Engineering)
Askari-Nasab, Hooman (Civil and Environmental Engineering)
Shirif, Ezeddin (University of Regina)
Department
Department of Civil and Environmental Engineering
Specialization

Date accepted
2009-11-19T21:13:24Z
Graduation date
2010-06
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
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 of technical analysis considering all available data. Current methods of estimating resource uncertainty use spreadsheets or Monte Carlo simulation software with specified probability distributions for each variable. 3-D models may be constructed, but they rarely consider uncertainty in all variables. This research develops an appropriate 2-D model of heterogeneity and uncertainty by integrating 2-D model methodology to account for parameter uncertainty in the mean, which is of primary importance in the input histograms. This research improves reserve evaluation in the presence of geologic uncertainty. Guidelines are developed to: a) select the best modeling scale for making decisions by comparing 2-D vs. 0-D and 3-D models, b) understand parameters that play a key role in reserve estimates, c) investigate how to reduce uncertainties, and d) show the importance of accounting for parameter uncertainty in reserves assessment to get fair global uncertainty by comparing results of Hydrocarbon Initially-in-Place (HIIP) with/without parameter uncertainty. The parameters addressed in this research are those required in the assessment of uncertainty including statistical and geological parameters. This research shows that fixed parameters seriously underestimate the actual uncertainty in resources. A complete setup of methodology for the assessment of uncertainty in the structural surfaces of a reservoir, fluid contacts levels, and petrophysical properties is developed with accounting for parameter uncertainty in order to get fair global uncertainty. Parameter uncertainty can be quantified by several approaches such as the conventional bootstrap (BS), spatial bootstrap (SBS), and conditional-finite-domain (CFD). Real data from a large North Sea reservoir dataset is used to compare those approaches. The CFD approach produced more realistic uncertainty in distributions of the HIIP than those obtained from the BS or SBS approaches. 0-D modeling was used for estimating uncertainty in HIIP with different source of thickness. 2-D is based on geological mapping and can be presented in 2-D maps and checked locally.
Language
English
DOI
doi:10.7939/R33P46
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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