Keywords and Phrases
Conventional screening guidelines; Dashboards; EOR technologies; Hierarchical clustering; Machine learning; Random forest
"Successful implementation of enhanced oil recovery (EOR) technology requires comprehensive knowledge and experiences based on existing EOR projects. EOR screening guidelines and EOR reservoir analog are served as such knowledge which are considered as the first step for a reservoir engineer to determine the next step techniques to improve the ultimate oil recovery from their assets. The objective of this research work is to provide better assistance for EOR selection by using fundamental statistics methods and machine learning techniques.
In this dissertation, a total of 977 worldwide EOR projects with the most uniformed, high-quality, and comprehensive information were collected from scattered publications and sources, which lays the foundation for further analysis and reasoning. Conventional screening guidelines for 12 EOR technologies were updated with the augment of critical parameters (e.g. MMP, net thickness) compared with previous studies. Hierarchical clustering and principal component analysis are applied for the construction of advanced EOR screening models. Furthermore, a hybrid EOR screening system was established with the combination of conventional and advanced screening technology. Finally, reservoir analog technology was applied to the steam flooding projects to detect the most similar case to assist the decision-making process with limited data information. The results show wider applicability from conventional guidelines; an advanced EOR selection model with discriminative screening results; a hybrid model which combines the advantages of conventional and advanced screening technologies; and an accurate reservoir analog results for steam flooding projects"--Abstract, page iv.
Flori, Ralph E.
Wunsch, Donald C.
Geosciences and Geological and Petroleum Engineering
Ph. D. in Petroleum Engineering
Missouri University of Science and Technology
Journal article titles appearing in thesis/dissertation
- Identification of CO₂ sequestration opportunities: CO₂ miscible flooding guidelines
- Statistical and analytical review of worldwide CO₂ immiscible field applications
- A novel EOR scoring system based on conventional screening guidelines and random forest
- Pattern recognition and analogue reservoir for steam flooding field applications
xiv, 143 pages
© 2019 Na Zhang, All rights reserved.
Dissertation - Open Access
Electronic OCLC #
Zhang, Na, "Building shared knowledge for EOR technologies: Screening guideline constructions, dashboards, and advanced data analysis" (2019). Doctoral Dissertations. 2799.