Natural gas production and processing covers from gas reservoir to processing facility. The former is the upstream of natural gas and it involves subsurface activities of the natural gas production. The latter is the downstream of natural gas and it involves surface processing of the natural gas. Natural gas hydrate formation occurs at the subsurface, but much concern is on the downstream of natural gas processing. In fact, the processing of the natural gas is to reduce the concentration of unwanted component in the gas stream, to avoid flow assurance issues when transporting the gas through pipelines. Hydrate formations affect gas flow rate and increase operating cost. Predicting hydrate formation condition, will enable gas pipeline operators to operate the facility to avoid hydrate formation. In this study, an empirical model was developed to predict hydrate formation temperature in gas pipeline. The independent variable for the model were pressure, gas specific gravity and methane composition (which existing models does not consider) and the target variable is temperature. Different functions (logarithmic, polynomial, exponential etc) were tested for the model and the best fit for the model were logarithmic and polynomial functions. This agreed with existing models which has either only logarithmic or polynomial functions. The results obtained from the developed nonlinear empirical model shows that the R-squared was 0.94 and the errors (residuals) between the observed and predicted temperature were scattered around zero. The model compares well with existing models, especially with model that contains logarithmic and polynomial function. The nonlinear empirical model has the capability to predict very low temperature of hydrate formation. It can be used as a first check in predicting gas hydrate formation temperature in pipeline, given the pressure, gas specific gravity and composition of the gas.
| Published in | Petroleum Science and Engineering (Volume 7, Issue 2) |
| DOI | 10.11648/j.pse.20230702.11 |
| Page(s) | 22-34 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Gas Hydrate, Empirical, Pipeline, Formation, Reservoir
| [1] | Abdulaga G. Ijabika S. Javida D. (2022), Building a Mathematical Model to Prevent Hydrate Formation in Gas Pipelines. Physics and Engineering. DOI: 10.21303/2461-4262.2022.002541. |
| [2] | Amir H. Mohammadi, Dominique Richon (2010). “Gas Hydrate phase Equation in the presence of Ethylene Glycol or Methanol Aqueous solution, Industrial and Engineering Chemistry Research, Vol 49, No. 18, pp. 8865-8869. |
| [3] | Ahmed A. E., & Ali M. E., (1998), A New Correlation for Predicting Hydrate Formation Conditions For Various Gas Mixtures and Inhibitors, College of Engineering and Petroleum, University of Kuwait, Kuwait. |
| [4] | Balakin B. V., Lo S., Kosinski P., Hoffman A. C., (2016), Modelling Agglomeration and Deposition of Gas Hydrate in Industrial Pipelines with Combined CFD-PBM Technique, Chemical Engineering Science, 153, 45-57. |
| [5] | Carson, D. B. Katz, D. L. (1942), Natural Gas Hydrates, Trans., AIME 146 150. |
| [6] | Chen, G. J., & Guo, T. M. (1996). A new approach to gas hydrate modelling. Chemical Engineering Journal, 71 (2), 145-151. |
| [7] | Dharmawardhana, P. B. Parrish, W. R. Sloan, E. D. (1980), Experimental thermodynamic parameters for the prediction of natural gas hydrate dissociation conditions, Ind. Eng. Chem. Fundamentals 19 (4), 410 – 414. |
| [8] | Englezos, P. (1992), Computation of the incipient equilibrium carbon dioxide hydrate formation conditions in aqueous electrolyte solutions, Ind. Eng. Chem. Res. 31, 2232–2237. |
| [9] | Frank J., Mark C. and Mark G. (2008), Hydrocarbon Exploration and production. Second Edition, Elsevier UK. |
| [10] | Hammerschmidt, E. G. (1934). Formation of gas hydrates in natural gas transmission lines. Industrial & Engineering Chemistry, 26 (8), 851-855. |
| [11] | Holder G. D., Zetts S. P., Pradhan N. (1988) Rev Chem Eng 5: 1–70. |
| [12] | Inkong K., Rangsunvigit P., Kulprathipanja S., (2016), Effects of Mixed Surfactants on Methane Hydrate Formation and Dissociations, Chemical Engineering Transaction, 52, 151-156, DOI: 10.3303/CET1652026. |
| [13] | Jianwei L. (2021), Research on Formation Prediction Model of Gas Hydrate, 3rd International Conference on Green Energy and Sustainable Development IOP Conf. Series: Earth and Environmental Science 651 (2021) 032088, doi: 10.1088/1755-1315/651/3/032088. |
| [14] | John V T, Papadopoulos K D, Holder K D. A (1985), generalized model forpredicting equilibrium conditions for gas hydrates. AIChE Journal, 31 (2): 252-259. |
| [15] | Katz, D. L. (1945). Prediction of conditions for hydrate formation in natural gases. Trans. AIME, 160 1945 140–144. |
| [16] | Kobayashi, R., Song, K. Y., & Sloan, E. D. (1987). Phase behavior of water/hydrocarbon systems. Petroleum Engineering Handbook. |
| [17] | Lee J. W., Kang S. P., (2013), Formation Behaviours of Mixed Gas Hydrate Including Olefin Compounds, Chemical Engineering Transaction, 32, 1921-1926, DOI: 10.3303/CET13332321. |
| [18] | Lee, M. J. Chen, J. T. (1993), Fluid property prediction with the aid of neural networks, Ind. Eng. Chem. Res. 32, 995–997. |
| [19] | Li, D. Q. Ai, M. Y. Wang Y. B. (2012), Hydrate Accident and Prevention in Sebei-Xining-Lanzhou Gas Pipeline,” Oil and Gas Storage and Transportation, vol. 31, no. 4, pp. 267–269, 2012. |
| [20] | Lili Z. Sirui Z. Yaxin M. Fangmei J. and Yue Z. (2021), Natural Gas Hydrate Prediction and Prevention Methods of City Gate Stations. Hindawi Mathematical Problems in Engineering Volume, https://doi.org/10.1155/2021/5977460. |
| [21] | Lorenzo M. D., Aman Z. M., Kozielski K., Norris B. W. E., Johns M. L., May E. F., (2018), Modelling Hydrate Deposition and Sloughing in Gas-Dominant Pipelines, Journal of Chemical Thermodynamics, 117, 81-90. |
| [22] | Makogon, Y. F. (1981), Hydrates of Natural Gas, PennWell, pp. 12–13. |
| [23] | Mann, S. L. McClure, L. M. Poettmann, F. H. Sloan, E. D. (1989), Vapor–Solid Equilibrium Ratios for Structure I and II Natural Gas Hydrates, Proc. 68th Ann. Gas Proc. Assoc. Conv., San Antonio, TX, March 13–14, pp. 60–74. |
| [24] | Mesbah, M. Habibnia, S. Ahmadi S. (2020), Developing a Robust Correlation for Prediction of Sweet and Sour Gas Hydrate Formation Temperature,” Petroleum. |
| [25] | Mohammad, R. T. and Ayoub R. K. (2018), Study of Different Models of Prediction of the Simple Gas Hydrates Formation Induction Time and Effect of Different Equations of State on them. Heat and Mass Transfer, Springer-Verlag GmbH Germany, part of Springer Nature. https://doi.org/10.1007/s00231-018-2508-y. |
| [26] | Motiee, M. (1991). Hydrocarbon Process, Int Ed, 70 (7), 98. |
| [27] | Musakaev N. G., Khasanov M. K., Borodin S. L., (2018), The Mathematical Model of Gas Hydrate Deposit Development in Permafrost, International Journal of Heat and Mass Transfer, 118, 455-461. |
| [28] | Nagata, I. Kobayashi, R. (1966), Predictions of Dissociation Pressures of Mixed Gas Hydrates from Data for Hydrates of Pure Gases with Water, Ind. and Eng. Chem. Fundamentals 5 (6), 466 – 469. |
| [29] | Nasser M., Brandstatter W., (2011), Hydrate Formation in Natural Gas Pipelines, Computational Methods in Multiphase Flow VI, WIT PRESS, 261-270. |
| [30] | Heng-Joo, and Donald B. Robinson. (1976) The Measurement and Prediction of Hydrate Formation in Liquid Hydrocarbon-Water Systems. AIChE Vol. 15, 293-298. |
| [31] | Omidi M., Shahsavand A., Share Mohammadi H., (2016), Modelling and Simulation of Hydrate Thermal Dissociation Around Gas Production Pipe from Sub-Oceanic Sediment, Journal of Natural Gas Science and Engineering, 32, 48-58. |
| [32] | Ostergaard, K. K. Tohidi, B. and Danesh, A. (2000), A General Correlation for Predicting the Hydrate-Free Zone of Reservoir Fluids,” SPE Production and Facilities, vol. 15, no. 4, pp. 228–233. |
| [33] | Parrish W. R, and Prausnitz J. M. (1972) Ind Eng Chem Des Dev 11: 26–35. |
| [34] | Saeedi Dehghani A. H., Badizad M., (2016), Thermodynamic Modelling of Gas Hydrate Formation in Presence of Thermodynamic Inhibitors with a New Association Equation of State, Fluid Phase Equilibria, 427, 328-339. |
| [35] | Sajjad J. and Leila, V. (2018), Mathematical Modeling of the Gas Hydrate Formation in a 90o Elbow Utilizing CFD Technique. Chemical Engineering Transactions, 70, 2167-2172 DOI: 10.3303/CET1870362. |
| [36] | Shin, W. Park, S. Ro, H. Koh, D. Y. Seol, J. Lee, H (2012), Phase equilibrium measurements and the tuning behavior of new sII clathrate hydrates, J. Chem. Thermodynamics. 44; 20–25. |
| [37] | Sloan, E. D. (1984), Phase Equilibrium of Natural Gas Hydrates, Proceedings of 63rd GPA Convention, 163–169. |
| [38] | Sun, C. Y. Huang, Q. and Chen, G. J. (2006), Progress of Thermodynamics and Kinetics of Gas Hydrate Formation, Journal of Chemical Industry and Engineering (China), no. 5, pp. 1031–1039. |
| [39] | Tarek A. (2006), Reservoir Engineering Handbook, Third Edition. Elsevier Gulf Publishing House Linacre House, Jordan Hill, Oxford OX2 8DP, UK. |
| [40] | Towler B. F. and Mokhatab S. (2005), Quickly Estimate Hydrate Formation Conditions in Natural Gases. Journal of Hydrocarbon Processing. 84 (4): 61–62. |
| [41] | Jwaals J. V. D. and Platteeuw, J. (1958), Clathrate solutions. Advances in chemical physics, 1-57. |
APA Style
Lesor, I., Kingdom Onyemuche, C., Victory, O. (2023). Empirical Model for Predicting Gas Hydrate Formation in Gas Pipelines. Petroleum Science and Engineering, 7(2), 22-34. https://doi.org/10.11648/j.pse.20230702.11
ACS Style
Lesor, I.; Kingdom Onyemuche, C.; Victory, O. Empirical Model for Predicting Gas Hydrate Formation in Gas Pipelines. Pet. Sci. Eng. 2023, 7(2), 22-34. doi: 10.11648/j.pse.20230702.11
AMA Style
Lesor I, Kingdom Onyemuche C, Victory O. Empirical Model for Predicting Gas Hydrate Formation in Gas Pipelines. Pet Sci Eng. 2023;7(2):22-34. doi: 10.11648/j.pse.20230702.11
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.pse.20230702.11,
author = {Ikeh Lesor and Choko, Kingdom Onyemuche and Oghale Victory},
title = {Empirical Model for Predicting Gas Hydrate Formation in Gas Pipelines},
journal = {Petroleum Science and Engineering},
volume = {7},
number = {2},
pages = {22-34},
doi = {10.11648/j.pse.20230702.11},
url = {https://doi.org/10.11648/j.pse.20230702.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.pse.20230702.11},
abstract = {Natural gas production and processing covers from gas reservoir to processing facility. The former is the upstream of natural gas and it involves subsurface activities of the natural gas production. The latter is the downstream of natural gas and it involves surface processing of the natural gas. Natural gas hydrate formation occurs at the subsurface, but much concern is on the downstream of natural gas processing. In fact, the processing of the natural gas is to reduce the concentration of unwanted component in the gas stream, to avoid flow assurance issues when transporting the gas through pipelines. Hydrate formations affect gas flow rate and increase operating cost. Predicting hydrate formation condition, will enable gas pipeline operators to operate the facility to avoid hydrate formation. In this study, an empirical model was developed to predict hydrate formation temperature in gas pipeline. The independent variable for the model were pressure, gas specific gravity and methane composition (which existing models does not consider) and the target variable is temperature. Different functions (logarithmic, polynomial, exponential etc) were tested for the model and the best fit for the model were logarithmic and polynomial functions. This agreed with existing models which has either only logarithmic or polynomial functions. The results obtained from the developed nonlinear empirical model shows that the R-squared was 0.94 and the errors (residuals) between the observed and predicted temperature were scattered around zero. The model compares well with existing models, especially with model that contains logarithmic and polynomial function. The nonlinear empirical model has the capability to predict very low temperature of hydrate formation. It can be used as a first check in predicting gas hydrate formation temperature in pipeline, given the pressure, gas specific gravity and composition of the gas.
},
year = {2023}
}
TY - JOUR T1 - Empirical Model for Predicting Gas Hydrate Formation in Gas Pipelines AU - Ikeh Lesor AU - Choko, Kingdom Onyemuche AU - Oghale Victory Y1 - 2023/11/29 PY - 2023 N1 - https://doi.org/10.11648/j.pse.20230702.11 DO - 10.11648/j.pse.20230702.11 T2 - Petroleum Science and Engineering JF - Petroleum Science and Engineering JO - Petroleum Science and Engineering SP - 22 EP - 34 PB - Science Publishing Group SN - 2640-4516 UR - https://doi.org/10.11648/j.pse.20230702.11 AB - Natural gas production and processing covers from gas reservoir to processing facility. The former is the upstream of natural gas and it involves subsurface activities of the natural gas production. The latter is the downstream of natural gas and it involves surface processing of the natural gas. Natural gas hydrate formation occurs at the subsurface, but much concern is on the downstream of natural gas processing. In fact, the processing of the natural gas is to reduce the concentration of unwanted component in the gas stream, to avoid flow assurance issues when transporting the gas through pipelines. Hydrate formations affect gas flow rate and increase operating cost. Predicting hydrate formation condition, will enable gas pipeline operators to operate the facility to avoid hydrate formation. In this study, an empirical model was developed to predict hydrate formation temperature in gas pipeline. The independent variable for the model were pressure, gas specific gravity and methane composition (which existing models does not consider) and the target variable is temperature. Different functions (logarithmic, polynomial, exponential etc) were tested for the model and the best fit for the model were logarithmic and polynomial functions. This agreed with existing models which has either only logarithmic or polynomial functions. The results obtained from the developed nonlinear empirical model shows that the R-squared was 0.94 and the errors (residuals) between the observed and predicted temperature were scattered around zero. The model compares well with existing models, especially with model that contains logarithmic and polynomial function. The nonlinear empirical model has the capability to predict very low temperature of hydrate formation. It can be used as a first check in predicting gas hydrate formation temperature in pipeline, given the pressure, gas specific gravity and composition of the gas. VL - 7 IS - 2 ER -
Department of Petroleum and Gas Engineering, Faculty of Engineering, University of Port Harcourt, Port Harcourt, Nigeria
Information