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Permanent link (DOI): https://doi.org/10.7939/R3TB0Z36K

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Characterizing the Impacts of Shale Barriers and Lean Zones on SAGD Performance with Data-Driven Modeling Techniques Open Access

Descriptions

Other title
Subject/Keyword
Shale Barriers
SAGD
ANN
Lean zones
Heterogeneities
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Wang,Cui
Supervisor and department
Leung,Juliana (Civil and Environmental Engineering)
Examining committee member and department
Kuru,Ergun (Civil and Environmental Engineering)
Leung,Juliana (Civil and Environmental Engineering)
Li,Huazhou (Civil and Environmental Engineering)
Department
Department of Civil and Environmental Engineering
Specialization
Petroleum Engineering
Date accepted
2015-11-30T13:51:37Z
Graduation date
2016-06
Degree
Master of Science
Degree level
Master's
Abstract
Performance of steam-assisted gravity drainage (SAGD) is influenced significantly by the distributions of shale barriers and lean zones, which tend to impede the vertical growth and lateral spread of a steam chamber. Reliable appraisal and prediction of SAGD require a comprehensive understanding of the effects of shale barriers and lean zones on SAGD performance. However, a comprehensive and systematic investigation of the heterogeneous distribution (location, continuity, size, proportion and saturation) of shale barriers and lean zones is still lacking. In this study, numerical simulations are used to model the SAGD process. First, a detailed sensitivity analysis is performed by varying the location, continuity, size, proportion, and saturation of these heterogeneous features. Shale barriers (imbedded in a region of degraded rock properties) and lean zones with different sizes and degrees of continuity are placed in areas above the injector, below the producer, or in between the well pair. Then, the distribution of shale barriers and lean zones is stochastically modeled by nested sequential indicator simulation. A set of attributes, such as facie proportions and dimensionless correlation lengths, which represent the characteristics of reservoir heterogeneities are identified on the basis of the knowledge learned from preceding sensitivity analysis. Finally, neural network modeling is used for constructing data-driven models to correlate the pertinent attributes to SAGD performance measures. This work provides a guideline for assessing the impacts of shale barrier and lean zone heterogeneities on SAGD performance. A set of input variables and parameters that have significant impacts on the ensuing recovery response is identified. One can define readily the proposed set of variables from well logs and apply immediately in data-driven models with field data and scale-up analysis of experimental models to assist field-operation design and evaluation. One can also extend the approach presented in this thesis to analyze other solvent-assisted SAGD processes.
Language
English
DOI
doi:10.7939/R3TB0Z36K
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Wang,Cui and Leung,Juliana Y. (2015).SPE Reservoir Evaluation & Engineeering, 18(03). SPE-170101-PA.

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