Comparison of Separation Efficiency of Oil In The Presence Of Alkali Surfactant Polymer (Asp) Produced Fluid Using Packed Bed and Floatation Models
Separation of oil that is recovered from the reservoir is very important for the downstream processes. The alkali surfactant polymer (ASP) flooding used in enhanced oil recovery produces a fluid that contains large residual chemicals which inhibits an efficient separation of oil and water. This caus...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
IRC
2014
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| Subjects: | |
| Online Access: | http://utpedia.utp.edu.my/14491/1/Dissertation_Arvin_14391_Comparison%20of%20Separation%20Efficiency%20of%20Oil%20In%20The%20Presence%20Of%20Alkali%20Surfactant%20Polymer%20%28ASP%29%20Produced%20Fluid%20Using%20Packed%20Bed%20and%20Floatation%20Models.pdf http://utpedia.utp.edu.my/14491/ |
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| Summary: | Separation of oil that is recovered from the reservoir is very important for the downstream processes. The alkali surfactant polymer (ASP) flooding used in enhanced oil recovery produces a fluid that contains large residual chemicals which inhibits an efficient separation of oil and water. This causes corrosion of pipes and other problems in downstream process which needs attention. Thus optimum parameters have to be identified to predict the separation efficiency in order to determine both operational safety and economic performance. In this project, several important factors that influence the separation such as operating temperature, retention time, and surfactant and polymer concentration are investigated using packed bed and floatation models found in literature to identify the best model that can predict the effect on separation when a standard set of parameters used. Based on the results obtained, the floatation model is selected as best model (76% of efficiency) and analyzed further to optimize the parameters using function value based method to enhance the separation. The key parameter values were varied and optimum values obtained was used to predict the separation efficiency. It was found that after optimizing, the performance of model is increased by 32% where 99.90% of separation efficiency is obtained. A trade-off between the parameters is discussed for each parameters in this project that enhances the separation efficiency. |
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