Nashrieh Shimi va Mohandesi Shimi Iran

Nashrieh Shimi va Mohandesi Shimi Iran

Development of Applicable and Suitable Methods for Control and Monitoring of Wax Formation by Determination of WAT for Crude Oil Transport in Pipelines

Document Type : Research Article

Authors
Ali Asghar Pasban
Sorood Zahedi Abghari
َAliakbar Miranbeigi
Petroleum Refining Division, Research Institute of Petroleum Industry, Tehran, I.R. IRAN
Abstract
Determination of wax appearance temperature is a crucial specification in the transportation and storage of crude oil or heavy refinery products same as fuel oils. In this work, to determine wax appearance temperature different applicable methods were tested and developed. At first, the microscopic experiments were applied to different samples. Then the variation of viscosity versus temperature was monitored. To determine a feasible method to be applied in the fields, the variation of viscosity versus temperature was monitored. It was declared that at the wax appearance temperature a deep change in viscosity happened. Eventually, the wax appearance temperature of different crude oil including Iranian or heavy crude oil can be determined by the viscosimetry method. In the related experiments, the negative effect of water sediments and wax crystals was eliminated. It was also declared that the wax appearance temperature could be varied by variation of density, wax content, pour point, and asphaltenes of the samples. To correlate between input and output variables three different modeling methods were tested and implemented. The Artificial neural networks, Neuro-fuzzy, and regression models were tested to derive the most accurate correlation. The statistical studies approved that the regression models have suitable accuracy. The results of the regression model declared that the interaction effect of density and pour point and the effect of asphaltenes as one of the main input variables have the greatest impact on the wax appearance temperature.
Keywords
Crude oil
Wax appearance temperature
Viscometry method
Artificial neural network model
ANFIS model
Regression model

Subjects

[1] Bagai R., Singh N., Kumar R., Chopra A., Chopra A., Saxena J., Understanding Wax Appearance Temperature in Light Crude Oils by DSC, NMR, and HT-GC,  Petroleum Science and Technology, 35(15): 1595-1600 (2017)
[2] Musser B.J., Kilpatrick P.K.,  Molecular Characterization of Wax Isolated from a Variety of Crude Oils, Energy & Fuels., 12( 4): 715-725 (1998)
[3] Kok M.V., Letoffe J.M., Claudy P., Volle J.L., Comparison of Wax Appearance Temperatures of Crude Oils by Differential Scanning Calorimetry, Thermomicroscopy and Viscometry, Fuel, 75(7): 787-790 (1996)
[4] Behbahani T.J., Beigi A.A.M, Taheri Z., Ghanbari B., Investigation of Wax Precipitation in Crude Oil: Experimental and Modelling, Petroleum., 1(3): 223-230 (2015)
[5] محمدرضا احسانی، سجاد فرازمند، محمد مهدی شادمانی ،  بررسی آزمایشگاهی تأثیر افزودنی­ های پلیمری بر نقطه ریزش دیزل و نفت کوره تولیدی شرکت پالایش نفت اصفهان، نشریه شیمی و مهندسی شیمی ایران، (3)35: 115تا 126 (1395)
[6] Taherishakib J., Rajabikochi M., Kazemzadeh E., Shekarifard A.," A Modified Investigation of WAT of Crude Oil Based on Wax Properties: Experimental Study", Saint Petersburg 2018.Cong, 09 April 2018, Saint Petersburg (2018).
[7] Taherishakib J., Rajabikochi M., Kazemzadeh E., Shekarifard A., A Comprehensive Study of the Impact of Wax Compositions on the Wax Appearance Temperature (WAT) of Some Iranian Crude Oils: An Experimental Investigation, Journal of Petroleum Science and Engineering,  165: 67-80 (2018)
[8] Chiu V.Y.G., Modified Test Method Measures Wax Deposition Qualities of Opaque Crude, Oil & Gas Journal, 113(111): (2015)
[9] Dantas Neto. A.A., Gomes E.A.S., Barros Neto., E.L., Dantas T.N.C., Moura C.P.A.M., Determination of Wax Appearance Temperature (WAT) in Paraffin/Solvent Systems by Photoelectric and Viscosimetry, Brazilian Journal of  Petroleum and Gas, 3(4): 149-157 (2009)
[10] Jiang Z., Hutchinson J.M., Imrie C.T., Measurement of the Wax Appearance Temperatures of Crude Oils by Temperature Modulated Differential Scanning Calorimetry, Fuel, 80: 367-371 (2001)
[11] Verson Kok M., Mikhail A., Varfolomeev D., Nurgaliev K., Wax Appearance Temperature(WAT) Determination of Different Origin Crude Oils by Differential Scanning  Calorimetry, Petroleum Science and Technology, 168: (2018)
[12] Taheri-Shakib J., Shekarifard A., Naderi H., Characterization of the Wax Precipitation in Iranian Crude Oil Based on WAT: The Influence of Electromagnetic Waves, Petroleum Science and Technology, 161: 530 (2018)
[13] خشایار یعقوبی، ندا گیلانی، سرود زاهدی عبقری، مروری بر مدل­ سازی و بهینه سازی واحد شکست کاتالیستی بستر سیال، نشریه شیمی و مهندسی شیمی ایران، (1)38: 125تا156 (1398)
[14] Zahedi Abghari S., Shokri S., Baloochi B., Marvast M.A., Analysis of Sulfur Removal in Gasoil Hydrodesulfurization Process by Application of Response Surface Methodology,  Korean J. Chem. Eng., 28( 1): 93-98 (2011)
[15] Mohammadikhah R., Zahedi Abghari S., Marvast M.A, Improvement of Hydrodynamics Performance of Naphtha Catalytic Reforming Reactors using CFD, Iran J. Chem. Chem. Eng. (IJCCE), 33(3): 63-76 (2014)
[16] ASTM D4007, "Standard Test Method for Water and Sediment in Crude Oil by the Centrifuge Method (Laboratory Procedure)", Annual Book of ASTM Standards, USA, 5(2): (2017)
[17] ASTM D5002, " Standard Test Method for Density and Relative Density of Crude Oils by Digital Density Analyzer" Annual Book of ASTM Standards, USA, 5(2): (2017)
[18] ASTM D2500, " Standard Test Method for Cloud Point of Petroleum Products" Annual Book of ASTM Standards, USA, 5(2): (2017)
[19] ASTM D97, "Standard Test Method for Pour Point of Petroleum Products" Annual Book of ASTM Standards, USA, 5(2): (2017)
[20] ASTM D5853, "Standard Test Method for Pour Point of Crude Oils" Annual Book of ASTM Standards, USA, 5(3): (2017)
[21] ASTM D4057, "Standard Practice for Manual Sampling of Petroleum and Petroleum Products" Annual Book of ASTM Standards, USA, 5(2): (2017)
[22] ASTM D445, "Standard Test Method for Kinematic Viscosity of Transparent and Opaque Liquids and Calculation of Dynamic Viscosity”, Annual Book of ASTM Standards, USA, 5(1): (2017)
[23] Zahedi Abghari S., Imani A., Determination of Suitable Operating Conditions of Fluid Catalytic Cracking Process by Application of Artificial Neural Network and Firefly Algorithm, Iran J. Chem. Chem. Eng. (IJCCE), 37(6): 157-168 (2018)
[24] Zahedi Abghari S., Sadi M., Application of Adaptive Neuro-Fuzzy Inference System for the Prediction of the Yield Distribution of the Main Products in the Steam Cracking of Atmospheric Gasoil, J. Taiwan Inst. Chem. E; (44): 365-376 (2013)