Abstract

Transmission of natural gas with methane as the main constituent has been a subject of interest to industrial companies. Predicting hydrate formation conditions is important to prevent formation of methane hydrate in gas pipeline. Also, attention has been taken to account for capture and storage of pure methane. In this paper, a comprehensive comparison is performed between empirical correlations and different equation of state in van der Waals Platteeuw (VdW-P) thermodynamic model to determine the most accurate method of hydrate formation condition of methane. In addition, a novel, simple and accurate correlation is developed to predict methane hydrate formation temperature using genetic programming. Error analysis on a wide range of experimental data indicates that the new proposed correlation is superior over existing correlations and all VdW-P models with R2 = 0.999.

Highlights

  • The gas hydrates are pseudo-ice structured compounds which consist of water molecules and natural gas components

  • Zhong et al investigated separating methane from a coal mine methane gas using gas hydrate crystallization method (2016). This was due to large gas storage capacity of methane hydrate and finding average formation conditions

  • Methane hydrate formation as a huge source of energy was the aim of study indifferent researches especially to evaluate enhancement of methane hydrate growth and its density

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Summary

Introduction

The gas hydrates are pseudo-ice structured compounds which consist of water molecules and natural gas components. In the case of empirical correlations, the input parameters include temperature, pressure and gas gravity These methods are useful for rapid estimation of the hydrate formation conditions. The simplicity of Hammerschmidt (HSCH) correlation may cause deviation from experimental data Another example is Holder et al.’s (1988) correlation developed for predicting hydrate formation pressure which was simple and easy to use. Their correlation depends on two coefficients which are function of temperature range for each gas. Other example in the same category is the presented correlation by Amin et al (2015) which was developed based on leverage approach or Ghiasi (2012) who offered a correlation as a function of molecular weight and pressure to predict hydrate formation temperature (HFT). Heat capacity can be calculated as: Fig. 1 Typical algorithm of VdW-P model

Results and discussion
10 Virial
Evaluation of new correlation
(40) References
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