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Asphaltene Onset Prediction Using CEOS

Keihani Hakavani, Ali | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 51484 (66)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Ghotbi, Cyrous; Jafari Behbahani, Taraneh
  7. Abstract:
  8. One of the main problems associated with the oil production is asphaltene precipitate in the reservoirs. In order to plan for the EOR methods, production scenario, and selection of completion technology, it is necessary to study the initiation of asphaltene precipitation called onset. Since the experimental methods is not only is so expensive and time consuming, the required materials are not available. Consequently, modeling approaches as new methods are proper substitutes for laboratory procedure. These methods need less costs and time and higher accuracy compared to the experimental investigations which are the advantages of these methods. Computational operations for onset determination were implemented using computer programming which needs very short elapsed time. In this project by appropriate equations of state selection, (EOS) it was tried to predict the onset of asphaltene formation in the oil reservoir. The EOS was selected based on the specifications of available crude oil samples. For this purpose, the required parameter for the EOS and also modeling process was determined according to the published experimental data and the onset of asphaltene was predicted. Moreover, the effects of system pressure and temperature have been analyzed in the defined system
  9. Keywords:
  10. Precipitation ; Pressure ; Temperature ; Asphaltene Precipitation ; Cubic State Equations ; Onset Detection

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