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New correlations for predicting pure and impure natural gas viscosity

Izadmehr, M ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1016/j.jngse.2016.02.026
  3. Publisher: Elsevier , 2016
  4. Abstract:
  5. Accurate determination of natural gas viscosity is important for successful design of production, transportation, and gas storage systems. However, most of available models/correlations suffer from complexity, robustness, and inadequate accuracy especially when wide range of pressure and temperature is applied. Present study illustrates development of two novel models for predicting natural gas viscosity for pure natural gas (CH4) as well as natural gas containing impurities. For this purpose, 6484 data points have been gathered and analyzed from the open literature covering wide range of pressure, temperature, and specific gravity levels, temperature ranges from -262.39 to 620.33 °F (109.6 to 600 K), pressure ranges from 1.4508 to 29,000 psi (0.0100-199.94801 MPa), and gas specific gravity ranges from 0.553 to 1.5741. Sensitivity analysis on the collected data points through design of experiments algorithm showed that pseudo reduced pressure and pseudo reduced temperature are the most effective parameters as the inputs of the models. The Leverage Value Statistics is applied and doubtful data points are determined.The average absolute relative error and the coefficient of determination of the proposed models for predicting pure/impure natural gas viscosity on a wide range of conditions are 5.67% and 1.87%, 0.9826 and 0.9953, respectively. Reliable accuracy of proposed models in comparison to eight commonly used correlations makes them attractive for possible implementing in natural gas simulation/modeling applications. © 2016 Elsevier B.V
  6. Keywords:
  7. Design of experiments ; Empirical models ; Leverage value statistics ; New correlations ; Pure/impure natural gas viscosity ; Density (specific gravity) ; Digital storage ; Error statistics ; Forecasting ; Gases ; Genetic algorithms ; Genetic programming ; Natural gas ; Sensitivity analysis ; Coefficient of determination ; Effective parameters ; Empirical model ; Gas viscosity ; Pressure and temperature ; Pseudo-reduced pressure ; Value statistics ; Natural gas transportation
  8. Source: Journal of Natural Gas Science and Engineering ; Volume 30 , 2016 , Pages 364-378 ; 18755100 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S1875510016300713