Developing tools for determination of parameters involved in CO₂ based EOR methods

Ahmadi, Mohammad Ali (2017) Developing tools for determination of parameters involved in CO₂ based EOR methods. Masters thesis, Memorial University of Newfoundland.

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To mitigate the effects of climate change, CO₂ reduction strategies are suggested to lower anthropogenic emissions of greenhouse gasses owing to the use of fossil fuels. Consequently, the application of CO₂ based enhanced oil recovery methods (EORs) through petroleum reservoirs turn into the hot topic among the oil and gas researchers. This thesis includes two sections. In the first section, we developed deterministic tools for determination of three parameters which are important in CO₂ injection performance including minimum miscible pressure (MMP), equilibrium ratio (Kᵢ), and a swelling factor of oil in the presence of CO₂. For this purposes, we employed two inverse based methods including gene expression programming (GEP), and least square support vector machine (LSSVM). In the second part, we developed an easy-to-use, cheap, and robust data-driven based proxy model to determine the performance of CO₂ based EOR methods. In this section, we have to determine the input parameters and perform sensitivity analysis on them. Next step is designing the simulation runs and determining the performance of CO₂ injection in terms of technical viewpoint (recovery factor, RF). Finally, using the outputs gained from reservoir simulators and applying LSSVM method, we are going to develop the data-driven based proxy model. The proxy model can be considered as an alternative model to determine the efficiency of CO₂ based EOR methods in oil reservoir when the required experimental data are not available or accessible.

Item Type: Thesis (Masters)
Item ID: 13105
Additional Information: Includes bibliographical references.
Keywords: CO2 Injection, Connectionist Modeling, Enhanced Oil Recovery, Proxy Model, CO2 Sequestration, Recovery Factor
Department(s): Engineering and Applied Science, Faculty of
Date: September 2017
Date Type: Submission
Library of Congress Subject Heading: Carbon dioxide enhanced oil recovery--Simulation methods.

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