Abstract
Selection of CO2 as an injection gas for enhanced oil recovery (EOR), is more desired as it could be employed for the aims of CO2 sequestration resulting in the greenhouse gas reduction as well. Thermal conductivity of supercritical CO2 is one of the most important thermophysical properties in designing CO2 injection into the reservoir. In detail, thermal conductivity of supercritical CO2 can highly affect the transport and fluid properties of supercritical CO2 like I FT, density, viscosity, solubility in crude oil and oil swelling factor through temperature variations in both transportation lines and reservoir systems. In this study, a dominant soft computation model called, least square support vector machine optimized by coupled simulating annealing (LSSVM-CSA), was developed and validated as a powerful tool for accurate estimation of supercritical CO2 thermal conductivity. This model is based on a function of temperature and pressure. In continuum, by the several statistical parameters and visual tools the superiority of the suggested model was verified in comparison with other commonly applied correlations in the literature. As a result of this study, the proposed tool can be of great significance for engineers in designing any CO2 process for enhanced oil recovery and CO2 sequestration.
Original language | English |
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Title of host publication | 79th EAGE Conference and Exhibition 2017 |
Publisher | European Association of Geoscientists and Engineers, EAGE |
ISBN (Electronic) | 9789462822177 |
Publication status | Published - 1 Jan 2017 |
Event | 79th EAGE Conference and Exhibition 2017: Energy, Technology, Sustainability - Time to Open a New Chapter - Paris, France Duration: 12 Jun 2017 → 15 Jun 2017 |
Conference
Conference | 79th EAGE Conference and Exhibition 2017: Energy, Technology, Sustainability - Time to Open a New Chapter |
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Country/Territory | France |
City | Paris |
Period | 12/06/17 → 15/06/17 |