Prediction of Natural Gas Viscosity using Artificial Neural Network Approach

Authors: E. Nemati Lay, M. Peymani, E. Sanjari

Abstract:

Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of ANN is used. The designed neural network can predict the natural gas viscosity using pseudo-reduced pressure and pseudo-reduced temperature with AARD% of 0.221. The accuracy of designed ANN has been compared to other published empirical models. The comparison indicates that the proposed method can provide accurate results.

Keywords: Artificial neural network, Empirical correlation, Natural gas, Viscosity

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1333845

References:

[1] V. Vesovic, "Predicting the Viscosity of Natural Gas," Int. J. Thermophysics, vol. 2, pp. 415-426, 2001.
[2] M. R. Riazi, and G. N. Al-Otaibi, "Estimation of viscosity of liquid hydrocarbon systems," Fuel, vol. 80, pp. 27-32, 2001.
[3] A. Danesh, "PVT and Phase Behaviour of Petroleum Reservoir Fluids", Elsevier Science & Technology Books, Edinburgh, Scotland, (1998).
[4] J. Millat, J. H. Dymond, C. A. Nieto de Castro, "Transport Properties of Fluids-Their Correlation, Prediction and Estimation", Cambridge, Cambridge University Press, 1996.
[5] N. L. Carr, R. Kobayashi, and D. B. Burrows,"Viscosity of Hydrocarbon Gases under Pressure,", Trans. AIME, 201, 264-272, 1954.
[6] D. E. Dean, and L. I. Stiel, "Volumetric properties of nonpolar gaseous mixtures", AICHE Journal, vol. 4, pp. 430-435, 1958.
[7] A. L. Lee, M. H. Gonzalez, and B. E. Eakin, "The viscosity of natural gases," J. Petrol. Tech, vol. 37, pp. 997-1000, 1966.
[8] X. Q. Guo, L. S. Wang, S. X. Rong, T. M Guo, "Viscosity model based on equations of state for hydrocarbon liquids and gases", Fluid Phase Equilibria, 139, vol. 405-421, 1997.
[9] M. L. Huber, A. Laesecke, and H. W. Xiang, "Viscosity correlations for minor constituent fluids in natural gas: n-octane, n-nonane and n¬decane," Fluid Phase Equilibria, vol. 228, pp. 401-408, 2005.
[10] A. Xuan, Y. Wu, C. Peng, P. Ma, C. Wang, and L. Zhang, "Correlation of Viscosities for Alkane, Aromatic and Alcohol Family at High Pressure by Modified Tait Equation", Chin. J. Chem. Eng, vol. 14, pp. 364-370, 2006.
[11] E. Heidaryan, A. Salarabadi, and J. Moghadasi, "A new and reliable model for predicting methane viscosity at high pressures and high temperatures", J. Nat. Gas Chem, vol. 19, pp. 552-556, 2010.
[12] E. Heidaryan, Salarabadi, A., Moghadasi, J, "A novel correlation approach for prediction of natural gas compressibility factor", J. Nat. Gas. Chem, vol. 19, pp. 189-192, 2010.
[13] E. Sanjari, E. Nemati Lay, M. Peymani, "An accurate empirical correlation for predicting natural gas viscosity," J. Nat. Gas. Chem, vol. 20, pp. 654-658, 2011.
[14] A. A. AlQuraishi, and E. M. Shokir, "Artificial neural networks modeling for hydrocarbon gas viscosity and density estimation," J. King. Saud. Uni, vol. 23, 123-129, 2011.
[15] M. Atilhan, S. Aparicio, R. Alcalde, G. A. Iglesias-Silva, M. El¬Halwagi, and K. R. Hall, "Viscosity Measurements and Data Correlation for Two Synthetic Natural Gas Mixtures," J. Chem. Eng. Data, vol. 55, pp. 2498-2504, 2010.
[16] M. Atilhan, S. Aparicio, G. A. Iglesias-Silva, M. El-Halwagi, K. R. Hall, "On the Viscosity of Natural Gases from Qatari North Field Reservoir," J. Chem. Eng. Data, vol. 55, pp. 5117-5123, 2010.
[17] M. J. Assael, N. K. Dalaouti, V. Vesovic,"Viscosity of Natural-Gas Mixtures: Measurements and Prediction," Int. J. Thermophysics, 28, 61-71, 2001.
[18] L. I. Langelandsvik, S. Solvang, M. Rousselet, I. N. Mextaxa, M. J Assael, "Dynamic Viscosity Measurements of Three Natural Gas Mixtures—Comparison against Prediction Models," Int. J. Thermophysics, vol. 22, pp. 1120-1130, 2007.
[19] Schley, P., Jaeschke, M., Kuchenmeister, C., E. Vogel, "Viscosity Measurements and Predictions for Natural Gas," Int. J. Thermophysics, vol. 22, pp. 1623-1652, 2004.
[20] A. R. H. Goodwin, "A MEMS Vibrating Edge Supported Plate for the Simultaneous Measurement of Density and Viscosity: Results for Argon, Nitrogen, and Methane at Temperatures from (297 to 373) K and Pressures between (1 and 62) MPa," J. Chem. Eng. Data, vol. 54, pp. 536-541, 2009.
[21] B. A. Younglove, and J. F. Ely, "Thermophysical Properties of Fluids.11. Methane, Ethane, Propane, Isobutane, and Normal Butane," J. Phys. Chem. Ref. Data, vol.16, pp. 577-798, 1987.
[22] T. Ahmed, Hydrocarbon Phase Behavior, Contributions in Petroleum Geology & Engineering. Vol. 7. Houston, Gulf Publishing Company, 1989.
[23] A. M. Elsharkawy, "Efficient methods for calculations of compressibility, density and viscosity of natural gases," Fluid Phase Equilibria, vol. 218, pp.1-13, 2004.
[24] M. T. Hagan, H. B. Demuth, M. Beal, "Neural Network Design," Boston, PWS Publishing Company, 1996.
[25] S. N. Sivanandam, S. Sumathi, and S. N. Deepa, "Introduction to Neural Networks Using Matlab 6.0.," New Delhi, pp.1-29. McGraw-Hill Publishing. 2006.
[26] R. Gharbi, "Estimating the Isothermal Compressibility Coefficient of Undersaturated Middle East Crudes Using Neural Networks", Energy & Fuels, vol. 11, pp. 372-378, 1997.
[27] A. B. Bulsari, `Neural Networks for Chemical Engineers," Amsterdam, Elsevier, 1995.
[28] H. Eden, and M. Inalli, "Modelling of a vertical ground coupled heat pump system by using artificial neural networks," Exp. Syst. Appl, vol. 37, pp. 10229-10238, 2009.
[29] P. J. McElroy, J. Fang, and C. J. Williamson, "Second and third virial coefficients for (methane + ethane + carbon dioxide)," J. Chem. Therm, vol. 33, pp. 155-163, 2001.
[30] H. J. Achtermann, J. Hong, W. Wanger, A. Pruss, "Refractive index and density isotherms for methane from 273 to 373 K and at pressures up to 34 MPa," J. Chem. Eng. Data, vol. 37, pp. 414-418, 1992.