Modeling of Gas Hydrate Formation in Presence of Inhibitors Using the Fuzzy Logic

Falahati, Mojtaba | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46693 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Taghikhani, Vahid; Ghotbi, Cyrus
  7. Abstract:
  8. Nowadays oil and gas industry has taken the pulse of world energy. Different countries of the world are trying more and more to explore and produce this black gold. To do so these countries has gained many experiences and even gone to seas and oceans to find oil and gas. In the process, they has faced with a new phenomenon called gas hydrate. The phenomenon which was unknown and destructive at first after excessive research, today is even called as the future energy source of the world. But what we discussed in this study is hydrate as a problem in oil and gas industry. Gas hydrates are formed in favorable temperature and pressure condition (low temperature and high pressure) in the presence of water and since it is like a solid mass of ice, it blocks the flow of oil and gas and even drilling mud. For this scientists started to research on the nature and the way of dealing with gas hydrates in operational systems. To date, many components were used in this field and has been useful including alcohols, salts and glycols. In this study, we tried to model the gas hydrate formation in the presence of inhibitor with a new approach which is Fuzzy Logic. Advantage of fuzzy logic is in describing the natural phenomena which hydrate is of this kind. In this work a Field inference engine with Gaussian membership functions is used to describe the fuzzy system. This system contains 10 inputs including methane, ethane and propane as gas composition and 6 common thermodynamic inhibitors in industry and temperature and output is the hydrate formation pressure in inputs condition. Outputs of the CSMGem software are used to describe the fuzzy system which has better accuracy compared to other software. Fuzzy system does not need experimental data for training. Advantages of this system are high speed, continuous outputs and wider coverage range compared to previous works. Error of this method is also acceptable compared software and experimental data
  9. Keywords:
  10. Gas Hydrate ; Fuzzy Logic ; Modeling ; Thermodynamic Inhibitors

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