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Ghodarzi, Abbas | 2010

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 40904 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Ghodarznia, Iraj; Soltanieh, Mohammad
  7. Abstract:
  8. In this study the kinetics of extraction of various hydrocarbons from crude oil using supercritical CO2 has been studied experimentally. The effect of parameters such as temperature (35, 45, 55, 65 °C), pressure (90, 110, 130, 150 bar), initial volume of crude oil (16, 19, 22, 25 mL) were investigated. Flow rate of gas has been recorded dynamically. QUALITECH 4 and MATLAB neural network softwares have been used for designing the experiments and modeling the final results, respectively. Pressure has a direct effect on extraction yield and by increasing it, heavier fractions could be obtained. On the other hand, the effect of temperature is more complicated, by increasing the temperature, the solubility power of CO2 decreases but the volatility of crude oil components increases. As a result, the heavier fractions would be extracted much easier at the higher temperatures. The experimental results show that at low temperatures, the effect of lower solubility power is dominant, but at high temperatures, the effect of higher volatility could be considered as dominant. As a result, increasing temperature above 55 °C could lead to higher extraction yield of heavier fractions, depending on operating pressure. The flow rate of gas and the initial crude oil volume have diverse effects on extraction efficiency. By decreasing the flow rates and also increasing the initial crude oil volume higher residence time between the gas and crude oil will be obtained and consequently the extraction yield will be higher. The higher residence time would be resulted at the higher extraction efficiency for heavier components.
  9. Keywords:
  10. Crude Oil ; Carbon Dioxide ; Neural Network ; Kinetics Study ; Supercritical Fluid

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