A Quick-Look Model to Predict Gas Hydrate Formation in Gas Pipelines using Modified Navier-Stokes Correlation

Akinsete O. Oluwatoyin *

Department of Petroleum Engineering, Faculty of Technology, University of Ibadan, Ibadan, Oyo State, Nigeria.

Oladipo O. Olatunji

Department of Petroleum Engineering, Faculty of Technology, University of Ibadan, Ibadan, Oyo State, Nigeria.

Isehunwa O. Sunday

Department of Petroleum Engineering, Faculty of Technology, University of Ibadan, Ibadan, Oyo State, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

Major challenges associated with the smooth production operations in the oil and gas industry that has raised technical curiosity are formation of natural gas hydrates in production facilities and flow lines which introduces significant cost to operators. Accurate modeling is therefore paramount; most existing models are based on constitutive conservation laws neglecting other dissipative energy types.

To predict “if” and “where” gas hydrate would be formed in gas pipeline, the Navier-Stokes equation was modified by incorporating dissipative forces of viscosity and gravity; the equation that emerged was solved analytically to determine the hydrate formation pressure (HFP) and the position of hydrate formation along gas pipelines.

The developed model, used as a quick-look tool for where and if hydrates will form revealed that when the predicted HFP is positive hydrates was formed but when it is negative hydrates were not formed. The model also showed that HFP is a function fluid composition, mass flowrate, changes in fluid and surrounding conditions and changes in elevation and direction confirming the results of earlier work done.

Keywords: Analytical model, navier-stokes equation, gas hydrate, dissipative force, production facilities.


How to Cite

Oluwatoyin, Akinsete O., Oladipo O. Olatunji, and Isehunwa O. Sunday. 2020. “A Quick-Look Model to Predict Gas Hydrate Formation in Gas Pipelines Using Modified Navier-Stokes Correlation”. Current Journal of Applied Science and Technology 39 (36):1-11. https://doi.org/10.9734/cjast/2020/v39i3631067.

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