Natural gas processing

Natural Gas Hydrate Formation Temperature in the presence of Ethylene Glycol

The formation of hydrates in natural gas processing facilities and pipelines is a critical problem since it could eventually lead to blocked pipelines and shutdowns and even to the destruction of valuable equipment. Because of these potential devastating and costly consequences, the investigation on an effective method for preventing the formation of gas hydrates has aroused significant interest. 


One of the methods to suppress hydrate formation in the free water phase is to inject hydrate inhibitors.  The most common inhibitors are methanol and ethylene glycol (EG). These chemical additives thermodynamically destabilize hydrates and effectively lower the temperature of hydrate formation. EG is generally the preferred choice as a hydrate inhibitor for continuous injection as it can be effectively regenerated and recycled. The amount of EG required as an inhibitor and hence the regenerator reboiler duty (if regenerated in a gas processing facility) depend on the depression of hydrate formation temperature caused by adding EG to the gas. The accurate calculation of gas hydrate formation temperature in the presence of EG is essential to avoid operating problems and to optimize energy use in gas processing facilities.

 

The objective of this article is to compare the accuracy of several correlations for the prediction of gas hydrate formation temperature in the presence of EG as inhibitor (Thg,I ). The gas hydrate temperature with inhibitors can be directly calculated using a correlation or can be estimated using Equation 1:           Thg,I= Th- DT

where Thg  is the hydrate formation of gas without inhibitor and DT is the hydrate temperature depression. The following correlations have been reviewed in this study:

  • A correlation proposed by Ameripour and Barrufet [1] to predict hydrate temperature for systems including inhibitors (Thg,I ).
  • Process Ecology Hydrate (HYSYS Extension) methods (van der Waals-Platteeuw (vdW) [2], Fugacity [3], and GPSA [4]) to calculate hydrate temperature of gas without inhibitor (Thg ).
  • Hammerschmidt correlation (HS34) [2] to predict the formation of gas hydrates in natural gas without inhibitor ( Thg ). 
  • Bahadori and Vuthaluru correlation [3] (Bahadori) to estimate the hydrate formation temperature of natural gas without inhibitor ( Thg ). 

The correlation of Ameripour and Barrufet (Ameripour) directly predicts the hydrate temperature for systems with inhibitors (Thg,I). The other listed methods calculate the hydrate temperature without inhibitor (Thg), and therefore require a further calculation to estimate the hydrate temperature depression.

  • Hammerschmidt (HS39) [4] is used to estimate the hydrate temperature depression due to the presence of inhibitor (DT).
  • Mazlum et al. activity correlation [5] (Activity) is used to calculate the hydrate suppression temperature due to the presence of inhibitor (DT). 


The hydrate formation temperatures with inhibitor for nine natural gas samples with specific gravities in the range of 0.55 to 0.67 were calculated using the above-mentioned correlations and the results were compared with experimental data. The experimental data specifications including EG concentration, gas specific gravity, number of data points, and pressure range are listed in Table 1



Table 1. Experimental Data Specifications


Deviations of the calculated hydrate temperature formation in the systems including EG as an inhibitor from the experimental data are shown in Figure 1. As shown in this figure, deviations of the Ameripour correlation increase with increasing EG concentration. This correlation predicts the hydrate temperature in the presence of up to 50 wt% EG with less than 3% error. Although this correlation is a simple method to evaluate the hydrate formation temperature, at 65 wt% EG it provides results with 7.3% error which is the largest deviation from experimental data among the correlations studied in this work. In refrigeration plants the rich glycol concentration is usually in the range of 65-70 wt%; correlations with lower deviations from experimental data in this range are preferable.

 


Figure 1. Deviations of the Calculated Hydrate Formation Temperatures from the Corresponding Experimental Data (click to see larger version)


Figure 2 shows the results of those correlations predicting the hydrate formation temperature for systems including EG with less than 3% error. Among these correlations, the Bahadori-Activity and the Bahadori-Hammerschmidt (1939) correlations are the simplest models for the hydrate temperature evaluation and they don’t need complex computer codes for the calculations. The average error for the Bahadori-Activity and Bahadori-Hammerschmidt correlations (1939) are 0.86% and 1.1%, respectively, showing the performance of these correlations for predicting the gas hydrate formation temperature with EG is acceptable. It should be noted that these correlations are not appropriate for acid gases with molecular weights greater than 29.


Figure 2. Correlations with less than 3% Deviation from Experimental Data (click to see larger version)


Conclusions

The objective of this article is to provide the reader with a quantitative understanding of the accuracy of hydrate formation temperature estimation in the presence of inhibitors for methods ranging from simple correlations to computer codes used in simulators. An accurate hydrate formation temperature calculation helps to evaluate the amount of EG required in pipelines or refrigeration plants and hence to the optimization of reboiler duty. Typically EG refrigeration plants are over-circulating causing unnecessary emissions (e.g. BTEX) and increasing fuel gas consumption. Reducing the EG circulation rate is one of the methods used for optimizing these plants. The results obtained from this article show that an accurate estimation of hydrate formation temperature in the presence of inhibitors for sweet natural gas can be obtained from simple models such as Bahadori-Activity and Bahadori-Hammerschmidt which can be easily solved and used for optimization purposes.


References

[1] S. Ameripour, M. Barrufet, Journal of Canadian Petroleum Technology, 2009, 48, 45

[2] J.H. van der Waals, J.C. Platteeuw, Advances in Chemical Physics, 1959, 2, 1.

[3] G-J. Chen, T-M. Guo, Chemical Engineering Journal, 1998, 71, 145.

[4] Gas Processors Suppliers Association (GPSA), Engineering Data Book.[5]E.G. Hammerschmidt, Industrial and Engineering Chemistry, 1934, 26, 851.

[6] A. Bahadori, H.B. Vuthaluru, Journal of Natural Gas Chemistry, 2009, 18, 1.

[7] E.G. HammerSchmidt, Gas, 1939, 15, 30.

[8] S. Mazlum, A. Chapoy, J. Yang, and B. Tohidi, Proceedings of the 7th International Conference on Gas Hydrates (ICGH), 2011, July 17-21.  


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