ORIGINAL_ARTICLE
Use of ANFIS/Genetic Algorithm and Neural Network to Predict Inorganic Indicators of Water Quality
The present research used novel hybrid computational intelligence (CI) models to predict inorganic indicators of water quality. Two CI models i.e. artificial neural network (ANN) and a hybrid adaptive neuro-fuzzy inference system (ANFIS) trained by genetic algorithm (GA) were used to predict inorganic indicators of water quality including total dissolved solids (TDS), total hardness (TH), total alkalinity (TAlk), and electrical conductivity (σ). The study was conducted on samples collected from water wells of Kermanshah province through analyzing water parameters including pH, temperature (T), and the sum of mill equivalents of cations (SC) and anions (SA). A multilayer perceptron (MLP) structure was used to forecast inorganic indicators of water quality using the ANN approach. A MATLAB code was used for the proposed ANFIS model to adjust and optimize the ANFIS parameters during the training process using GA. The accuracy of the generated models was described using various evaluation techniques such as mean absolute error (MAE), correlation factor (R), and mean relative error percentage (MRE%). The results showed that both methods were suitable for predicting inorganic indicators of water quality. Moreover, the comparison of the two methods showed that the predicted values obtained from the ANFIS/GA model were better than those obtained from the ANN approach.
https://jchpe.ut.ac.ir/article_78104_911412662c83af011ea21ecb6fbd5ac1.pdf
2020-12-01
155
164
10.22059/jchpe.2020.264471.1244
ANFIS
ANN
Genetic Algorithm
Water quality
Majid
Mohadesi
m.mohadesi@kut.ac.ir
1
Department of Chemical Engineering, Faculty of Energy, Kermanshah University of Technology, Kermanshah, Iran
AUTHOR
Babak
Aghel
b.aghel@kut.ac.ir
2
Department of Chemical Engineering, Faculty of Energy, Kermanshah University of Technology, Kermanshah, Iran
LEAD_AUTHOR
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[5] Park SY, Choi JH, Wang S, Park SS. Design of a water quality monitoring network in a large river system using the genetic algorithm. Ecological modelling. 2006 Dec 1;199(3):289-97.
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[8] Delpla I, Benmarhnia T, Lebel A, Levallois P, Rodriguez MJ. Investigating social inequalities in exposure to drinking water contaminants in rural areas. Environmental Pollution. 2015 Dec 1;207:88-96.
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[12] Aghel B, Rezaei A, Mohadesi M. Modeling and prediction of water quality parameters using a hybrid particle swarm optimization–neural fuzzy approach. International Journal of Environmental Science and Technology. 2019 Aug 1;16(8):4823-32.
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[24] Areerachakul S. Comparison of ANFIS and ANN for estimation of biochemical oxygen demand parameter in surface water. International Journal of Chemical and Biological Engineering. 2012 Apr 26;6:286-90.
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[25] Yan H, Zou Z, Wang H. Adaptive neuro fuzzy inference system for classification of water quality status. Journal of Environmental Sciences. 2010 Dec 1;22(12):1891-6.
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30
ORIGINAL_ARTICLE
Numerical Modelling and Industrial Verification of Ethylene Dichloride Cracking Furnace
In this paper, the radiation section of ethylene dichloride (EDC) cracking furnace, considering the chemical reaction, was numerically modelled using computational fluid dynamics (CFD). This study investigated the influence of some parameters such as mass flow rate, the inlet temperature of fluid into the radiation section, and heat flux on the conversion and changes in velocity, pressure, and temperature of the fluid along the coil passes, as well as the outlet stream of the coil. Then, the modelling results were compared with a series of industrial data of an industrial EDC cracking furnace. The results showed that considering the variable heat flux boundary condition is more compatible with the industrial data rather than the constant heat flux boundary condition. Increasing the feed inlet temperature to the furnace, increased the EDC conversion due to the endothermic nature of the thermal cracking reaction. Furthermore, reducing the inlet mass flow rate led to a significant increase in the conversion, temperature, and mass fraction of the products due to an increase in residence time.
https://jchpe.ut.ac.ir/article_78118_ae98ff53932e369f5c7a986ec1108d81.pdf
2020-12-01
165
185
10.22059/jchpe.2020.286558.1291
Computational Fluid Dynamics
cracking
EDC
Numerical Modeling
Radiation
Afshin
Fahiminezhad
a.fahiminezhad@mhriau.ac.ir
1
Department of Chemical Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran
AUTHOR
Seyed Mohsen
Peyghambarzadeh
m.peyghambarzadeh@mhriau.ac.ir
2
Department of Chemical Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran
LEAD_AUTHOR
Mohsen
Rezaeimanesh
m.rezaeimanesh@mhriau.ac.ir
3
Department of Chemical Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran
AUTHOR
[1] Hu G, Yuan B, Zhang L, Li J, Du W, Qian F. Coupled simulation of convection section with dual stage steam feed mixing of an industrial ethylene cracking furnace. Chemical Engineering Journal. 2016 Feb 15;286:436-46.
1
[2] Li W, Lv Y, Sun Z, Yu W. Cause analysis of corrosion leakage in convection section of ethylene cracking furnace. Engineering Failure Analysis. 2020 Mar 4:104488.
2
[3] Rebordinos JG, Herce C, González-Espinosa A, Gil M, Cortés C, Brunet F, Ferré L, Arias A. Evaluation of retrofitting of an industrial steam cracking furnace by means of CFD simulations. Applied Thermal Engineering. 2019 Nov 5;162:114206.
3
[4] Yuan B, Zhang Y, Hu G, Zhong W, Qian F. Analytical models for heat transfer in the tube bundle of convection section in a steam cracking furnace. Applied Thermal Engineering. 2019 Dec 25;163:113947.
4
[5] Keshavarz E, Toghraie D, Haratian M. Modeling industrial scale reaction furnace using computational fluid dynamics: a case study in Ilam gas treating plant. Applied Thermal Engineering. 2017 Aug 1;123:277-89.
5
[6] Zheng S, Zhang X, Qi C, Zhou H. Modeling of heat transfer and pyrolysis reactions in ethylene cracking furnace based on 3-D combustion monitoring. International Journal of Thermal Sciences. 2015 Aug 1;94:28-36.
6
[7] Taweerojkulsri Ch, Panjapornpon Ch. Temperature Control of EDC Thermal Cracking Furnace with a Coupled ODE and 2D-PDEs Model. Chem. Eng. Sci. 2014; 31: 516–527.
7
[8] Heynderickx GJ, Oprins AJ, Marin GB, Dick E. Three‐dimensional flow patterns in cracking furnaces with long‐flame burners. AIChE journal. 2001 Feb;47(2):388-400.
8
[9] Oprins AJ, Heynderickx GJ, Marin GB. Three-dimensional asymmetric flow and temperature fields in cracking furnaces. Industrial & engineering chemistry research. 2001 Nov 14;40(23):5087-94.
9
[10] Oprins AJ, Heynderickx GJ. Calculation of three-dimensional flow and pressure fields in cracking furnaces. Chemical engineering science. 2003 Nov 1;58(21):4883-93.
10
[11] Stefanidis GD, Heynderickx GJ, Marin GB. Development of reduced combustion mechanisms for premixed flame modeling in steam cracking furnaces with emphasis on NO emission. Energy & fuels. 2006 Jan 18;20(1):103-13.
11
[12] Stefanidis GD, Merci B, Heynderickx GJ, Marin GB. CFD simulations of steam cracking furnaces using detailed combustion mechanisms. Computers & chemical engineering. 2006 Feb 15;30(4):635-49.
12
[13] Coelho PJ. Numerical simulation of radiative heat transfer from non-gray gases in three-dimensional enclosures. Journal of Quantitative Spectroscopy and Radiative Transfer. 2002 Aug 1;74(3):307-28.
13
[14] Habibi A, Merci B, Heynderickx GJ. Impact of radiation models in CFD simulations of steam cracking furnaces. Computers & Chemical Engineering. 2007 Nov 1;31(11):1389-406.
14
[15] Lan X, Gao J, Xu C, Zhang H. Numerical simulation of transfer and reaction processes in ethylene furnaces. Chemical Engineering Research and Design. 2007 Jan 1;85(12):1565-79.
15
[16] Han YL, Xiao R, Zhang MY. Combustion and pyrolysis reactions in a naphtha cracking furnace. Chemical Engineering & Technology: Industrial Chemistry‐Plant Equipment‐Process Engineering‐Biotechnology. 2007 Jan;30(1):112-20.
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[17] LIU S, WANG H, QIAN F, HU G. Coupled simulation of combustion with heat transfer and cracking reaction in SL-Ⅱ industrial ethylene pyrolyzer. CIESC Journal. 2011;62(5):1308-17.
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[18] Hu G, Wang H, Qian F, Van Geem KM, Schietekat CM, Marin GB. Coupled simulation of an industrial naphtha cracking furnace equipped with long-flame and radiation burners. Computers & chemical engineering. 2012 Mar 5;38:24-34.
18
[19] Hu G, Schietekat CM, Zhang Y, Qian F, Heynderickx G, Van Geem KM, Marin GB. Impact of radiation models in coupled simulations of steam cracking furnaces and reactors. Industrial & Engineering Chemistry Research. 2015 Mar 11;54(9):2453-65.
19
[20] Liu JJ, Guo Y, Zhang LJ. Process simulation of the convection section of cracking furnace based on Asepen Plus user model. Tianjin Chem. Ind.. 2009;23:25-9.
20
[21] Zhou Y, Yang DZ. Simulation and optimum design for convection section of ethylene cracking furnace. Chemical Engineering (China). 2010;9.
21
[22] De Schepper SC, Heynderickx GJ, Marin GB. Modeling the evaporation of a hydrocarbon feedstock in the convection section of a steam cracker. Computers & Chemical Engineering. 2009 Jan 13;33(1):122-32.
22
[23] Mahulkar AV, Heynderickx GJ, Marin GB, Varbanov P, Lam H, Klemes J, Pierucci S. Simulation of coking in convection section of steam cracker. Chemical Engineering. 2012;29: 1375–1380.
23
[24] Mahulkar AV, Heynderickx GJ, Marin GB. Simulation of the coking phenomenon in the superheater of a steam cracker. Chemical Engineering Science. 2014 May 3;110:31-43.
24
[25] De Schepper SC, Heynderickx GJ, Marin GB. Modeling the coke formation in the convection section tubes of a steam cracker. Industrial & engineering chemistry research. 2010 Jun 16;49(12):5752-64.
25
[26] Mertinger V, Benke M, Szabó S, Bánhidi O, Bollo B, Kovács Á. Examination of a failure detected in the convection zone of a cracking furnace. Engineering Failure Analysis. 2011 Oct 1;18(7):1675-82.
26
[27] De Schepper SC, Heynderickx GJ, Marin GB. Coupled simulation of the flue gas and process gas side of a steam cracker convection section. AIChE journal. 2009 Nov;55(11):2773-87.
27
[28] Pham HH, Lim YI, Ngo SI, Bang YH. Computational fluid dynamics and tar formation in a low-temperature carbonization furnace for the production of carbon fibers. Journal of Industrial and Engineering Chemistry. 2019 May 25;73:286-96.
28
[29] Herce C, González-Espinosa A, Gil A, Cortés C, González-Rebordinos J, Guégués T, Gil M, Ferré L, Brunet F, Arias A. Combustion monitoring in an industrial cracking furnace based on combined CFD and optical techniques. Fuel. 2020 Nov 15;280:118502.
29
[30] Bird RB, Stewart WE, Lightfoot EN. Transport Phenomena. 2nd ed, John Wiley & Sons, 2007.
30
[31] Schirmeister R, Kahsnitz J, Träger M. Influence of EDC cracking severity on the marginal costs of vinyl chloride production. Industrial & engineering chemistry research. 2009 Mar 18;48(6):2801-9.
31
ORIGINAL_ARTICLE
The Multivariable Control of Carbon Dioxide Absorption System using the Proportional Integral Plus (PIP) Controller
The present article investigates the implementation of non-minimal state space (NMSS) representation with proportional-integral-plus (PIP) controller for the carbon dioxide absorption process of Shiraz petrochemical ammonia unit. The PIP controller is a logical extension of conventional PI/PID controllers with additional dynamic feedback and input compensators. PIP controller is used for multivariable control without limitation on the number of controlled variables. A Multi Input - Multi Output (MIMO) square model was extracted from step response test. In this way, input water flow rate to carbon dioxide absorption system, the heat duty of input absorbent cooler to tray (1) of absorption tower and re-boiler heat duty of stripping tower are chosen as manipulated variables (inputs), while carbon dioxide mole fraction in absorption tower vapor product, the water mole fraction in absorption tower liquid product and tray temperature No. 36 of stripping tower are determined as controlled ones (outputs). The system identification is performed with three input and three output variables using step response test. As a result, continuous and discrete time transfer function matrices and suitable NMSS model for PIP controller are reported. Finally, in order to evaluate the PIP control performance, the feed flow rate increases by 2%. The results show the proper performance of designed PIP controller for both disturbance rejection and set point tracking.
https://jchpe.ut.ac.ir/article_78361_68ed2b630558aa85647b9398c8e7b03d.pdf
2020-12-01
187
204
10.22059/jchpe.2020.287075.1293
Multivariable control
Square structure
True Digital Control
MIMO System
Riccati Equation
Carbon Dioxide Absorption
Reactive Absorption
simulation
Fereshte
Tavakoli Dastjerd
frsh_tavakoli@pgs.usb.ac.ir
1
Department of Chemical Engineering, Faculty of engineering, University of Sistan and Baluchestan, Zahedan, Iran
LEAD_AUTHOR
Jafar
Sadeghi
sadeghi@eng.usb.ac.ir
2
Department of Chemical Engineering, Faculty of engineering, University of Sistan and Baluchestan, Zahedan, Iran
AUTHOR
[1] Nada AA, Shaban EM. The Development of Proportional-Integral-Plus Control Using Field Programmable Gate Array Technology Applied to Mechatronics System. American Journal of Research Communication. 2014;2(4):14-27.
1
[2] Chau, P. C., Chemical Process Control, University of California, San Diego, 2001.
2
[3] Zhang D, Cross P, Ma X, Li W. Improved control of individual blade pitch for wind turbines. Sensors and Actuators A: Physical. 2013 Aug 15;198:8-14.
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[4] Wang L, Garnier H, editors. System identification, environmental modelling, and control system design. Springer Science & Business Media; 2011 Oct 20.
4
[5] Jamali P, Sadeghi J, Tavakoli S, Khosravi MA. Weight optimal Proportional-Integral-Plus control of a gasoline engine model. In2015 European Control Conference (ECC) 2015 Jul 15 (pp. 1426-1431). IEEE.
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[6] Balaji V. Study and analysis of advanced control algorithms on a FOPDT model. Research Journal of Applied Sciences. 2014;9(6):376-81.
6
[7] Shaban EM, Nada AA. Proportional Integral Derivative versus Proportional Integral plus Control Applied to Mobile Robotic System. Journal of American Science. 2013;9(12):583-91.
7
[8] Shaban EM. Deadbeat response of nonlinear systems described by discrete-time state dependent parameter using exact linearization by local coordinate transformation. Journal of American Science. 2012;8(10):355-66.
8
[9] Abdelhamid A, Shaban EM, Zied KM, Khalil Y. Implementation of a Class of True Digital Control (TDC) in the Navigation of a Ground Vehicle. American Journal of Research Communication. 2013;1(6):99-111.
9
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[12] Taylor CJ, Young PC, Chotai A, Dixon R. Structural and predictive aspects of proportional-integral-plus (PIP) control.
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[14] Chotai A, Young P, McKenna P, Tych W. Proportional-integral-plus (PIP) design for delta (delta) operator systems Part 2. MIMO systems. International Journal of Control. 1998 Jan 1;70(1):149-68.
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[15] Aroua MK, Haji-Sulaiman MZ, Ramasamy K. Modelling of carbon dioxide absorption in aqueous solutions of AMP and MDEA and their blends using Aspenplus. Separation and purification technology. 2002 Nov 1;29(2):153-62.
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[16] Rahimpour M. R., Kashkooli A. Z., Modeling and simulation of industrial carbon dioxide absorber using amine-promoted potash solution, Iranian Journal of Science & Technology, Vol. 28, No. B6, pp. 653-666, 2004.
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[17] Maceiras R, Alvarez E, Cancela MA. Effect of temperature on carbon dioxide absorption in monoethanolamine solutions. Chemical Engineering Journal. 2008 May 1;138(1-3):295-300.
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[19] Shen MT, Chen YH, Chang H. Simulation of the Dynamics and Control Responses of the Carbon Dioxide Chemical Absorption Process using Aspen Custom Modeler. Energy Procedia. 2019 Feb 1;158:4915-20.
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[20] Taylor CJ, Young PC, Chotai A. True digital control: statistical modelling and non-minimal state space design. John Wiley & Sons; 2013 May 29.
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[22] Tavakoli Dastjerd F, Sadeghi J. The Simulation and Control of Ammonia Unit of Shiraz
22
Petrochemical Complex, Iran. Journal of Chemical and Petroleum Engineering. 2018 Dec
23
1;52(2):107-22.
24
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25
John Wiley & Sons, Inc Pub., United States of America, 2010.
26
ORIGINAL_ARTICLE
Investigation of Stability and Rheology of Produced Heavy-Oil Emulsions Formed due to Steam Injection
Water in oil emulsion is consider one of the major challenges encountered during production of heavy oil or when applying enhanced oil recovery techniques whether thermal or chemical. In this study stability and rheological properties of hot and cold produced heavy oil emulsions formed due to steam injection processes in Kuwaiti reservoirs were investigated thoroughly over a wide range of operation conditions. The effects of temperature, shear rates, and water cuts on the physical and chemical behaviors of the heavy oil emulsions were examined experimentally in detail. The results showed that cold-produced heavy oil emulsion (CP-HO) is more stable than hot produced heavy oil emulsions (HP-HO) because of its high salinity concentrations and low resin/asphaltene (R/A) ratios, and low PH value. Moreover, a new emulsion viscosity correlation was developed using the experimental data. The proposed model was validated against existed models. The results showed that the developed correlation i more applicable than the existed one in predicting the viscosity of heavy oil emulsions with a percentage of deviation almost less than 5 %.
https://jchpe.ut.ac.ir/article_78317_c47e2c89e7fae7a8ac2c4a0975019fba.pdf
2020-12-01
205
222
10.22059/jchpe.2020.283843.1295
Heavy oil emulsion
Asphaltenes
Stability
Inversion point
viscosity correlation
Abeer
Rashed
arashed@kisr.edu.kw
1
Petroleum Research Center, Kuwait Institute for Scientific Research (KISR), Safat, Kuwait
LEAD_AUTHOR
Ebtisam
Folad
efolad@kisr.edu.kw
2
Petroleum Research Center, Kuwait Institute for Scientific Research (KISR), Safat, Kuwait
AUTHOR
[1] Ersoy G, Yu M, Sarica C. Modeling of inversion point for heavy oil-water emulsion systems. SPE Projects, Facilities & Construction. 2009 Jun 1;4(02):47-52.
1
[2] Alboudwarej H, Muhammad M, Shahraki AK, Dubey S, Vreenegoor L, Saleh JM. Rheology of heavy-oil emulsions. SPE Production & Operations. 2007 Aug 1;22(03):285-93.
2
[3] CHEN YX, Chen J, Pan CS, LI G, XIAO XQ. Influence of asphaltenes and resins on the stability of heavy crude emulsions. Applied Chemical Industry. 2009;2.
3
[4] Nour AH, Yunus RM, Anwaruddin H. Water-in-crude oil emulsions: its stabilization and demulsification. JApSc. 2007 Dec;7(22):3512-7.
4
[5] Pilehvari, A.; Saadevandi, B.; Halvaci, M. Oil/Water emulsions for pipeline transport of viscous crude oils. Proceeding of SPE Annual Technical Conference and Exhibition, Houston, Texas, October 2-5.
5
[6] Wang XB, Han HS. An Experimental Study of Reducing Phase Inversion Point of Watercut Crude Oil Using Flow Improver. Oilfield Chemistry. 2008;25(2):186-8.
6
[7] Ioannou K, Nydal OJ, Angeli P. Phase inversion in dispersed liquid–liquid flows. Experimental thermal and fluid science. 2005 Mar 1;29(3):331-9.
7
[8] Duan L, Jing J, Wang J, Huang X, Qin X, Qiu Y. Study on Phase Inversion Characteristics of Heavy Oil Emulsions. InThe Twentieth International Offshore and Polar Engineering Conference 2010 Jan 1. International Society of Offshore and Polar Engineers.
8
[9] Maneeintr K, Sasaki K, Sugai Y. Investigation of the effects of parameters on viscosities and correlation of heavy oil and stability of its emulsion. Journal of the Japan Institute of Energy. 2013;92(9):900-4.
9
[10] Moradi M, Alvarado V, Huzurbazar S. Effect of salinity on water-in-crude oil emulsion: evaluation through drop-size distribution proxy. Energy & fuels. 2011 Jan 20;25(1):260-8.
10
[11] Alves DR, Carneiro JS, Oliveira IF, Façanha Jr F, Santos AF, Dariva C, Franceschi E, Fortuny M.Influence of the salinity on the interfacial properties of a Brazilian crude oil–brine systems. Fuel. 2014 Feb 15;118:21-6.
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[12] Hemmingsen PV, Silset A, Hannisdal A, Sjöblom J. Emulsions of heavy crude oils. I: Influence of viscosity, temperature, and dilution. Journal of dispersion science and technology. 2005 Sep 1;26(5):615-27.
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[13] Gafonova OV, Yarranton HW. The stabilization of water-in-hydrocarbon emulsions by asphaltenes and resins. Journal of Colloid and Interface Science. 2001 Sep 15;241(2):469-78.
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[14] Al-Sahhaf T, Elsharkawy A, Fahim M. Stability of water-in-crude oil emulsions: effect of oil aromaticity, resins to asphaltene ratio, and pH of water. Petroleum Science and Technology. 2008 Nov 3;26(17):2009-22.
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[15] Liu, RW, Chen, XL and Zhou, N. Study on Viscosity-reducing Techniques and Mechanisms for Viscous Crude Oils. Advances in Fine Petrochemicals, Vol 9, No 4, pp 20-25.
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[16] Al-Yaari M, Hussein IA, Al-Sarkhi A, Abbad M, Chang F. Effect of water salinity on surfactant-stabilized water–oil emulsions flow characteristics. Experimental Thermal and Fluid Science. 2015 Jun 1;64:54-61.
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[17] Zaki N, Schoriing PC, Rahimian I. Effect of asphaltene and resins on the stability of water-in-waxy oil emulsions. Petroleum science and technology. 2000 Aug 1;18(7-8):945-63.
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[18] Einestein, A. Eine neue bestimmung der molecule dimensionen. Ann. Phys. 19, 289 -306
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[19] Eilers VH. The viscosity of emulsions of highly viscous substances as a function of concentration. Colloid Journal. 1941 Dec 1; 97 (3): 313-21.
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[20] Mooney, M.J. The viscosity of a concentrated suspension of spherical particles. Journal of Colloid Science, Vol. 6. No.2, pp.162-170.
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[21] Pal R, Rhodes E. Viscosity/concentration relationships for emulsions. Journal of Rheology. 1989 Oct;33(7):1021-45.
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[22] Johnsen EE, Rønningsen HP. Viscosity of ‘live’water-in-crude-oil emulsions: experimental work and validation of correlations. Journal of Petroleum Science and Engineering. 2003 May 1;38(1-2):23-36.
22
ORIGINAL_ARTICLE
Experimental Investigation and Modelling of Asphaltene Precipitation during Gas Injection
Due to the limited crude oil resources, the role of enhanced oil recovery (EOR) techniques in the production of the oil that has not been extracted during the primary and secondary oil production techniques is crucial. Gas injection is known as an important EOR technology, but one of the main concerns during gas injection is asphaltene precipitation and deposition within reservoir formation. In this study, the effect of temperature (ranges 376-416 K) and concentration of injected gas (N2 (10, 20 and 40, mole percent) and first separator gas (20, 40 and 60, mole percent)) on the onset pressures and amount of asphaltene precipitation in one of the Iranian oil reservoirs were investigated. Two series of experiments were accomplished on live oil by gravimetric method; first: injection of different concentrationsof nitrogen and first separator gas at reservoir temperature and under different pressures (3000-8000 psia) and second: natural depletion at different temperatures. Besides, the experimental data of asphaltene precipitation due to N2, first separator gas, and also CO2 injection were compared together. Finally, the experimental data were modeled with a solid model. The results indicate that the amount of asphaltene precipitation due to N2 injection (0.1-0.2 wt %) is lower than the first separator gas and CO2 injection at the same concentration. Experiments show that in the range of experimental temperatures the asphaltene precipitation changes up to 0.06 wt %. For pressures below the bubble pressure (~ 4700 psi), precipitation changes directly with temperature, and indirect relation is observed for pressures above the bubble point pressure.
https://jchpe.ut.ac.ir/article_77214_e86af0142387278de114b5d1b8756d24.pdf
2020-12-01
223
234
10.22059/jchpe.2020.291688.1299
Asphaltene precipitation
gas injection
Natural depletion
Solid Model
temperature
Neda
Hajizadeh
nd.hajizadeh@yahoo.com
1
Faculty of Chemical and Petroleum Engineering, Razi University, Kermanshah, Iran
AUTHOR
Gholamreza
Moradi
gmoradi@razi.ac.ir
2
Faculty of Chemical and Petroleum Engineering, Razi University, Kermanshah, Iran
LEAD_AUTHOR
Siavash
Ashoori
ashoori39@yahoo.com
3
Department of Petroleum Engineering, Petroleum University of Technology (PUT), Ahvaz, Iran
AUTHOR
[1] Wang P, Zhao F, Hou J, Lu G, Zhang M, Wang Z. Comparative analysis of CO2, N2, and gas mixture injection on asphaltene deposition pressure in reservoir conditions. Energies. 2018 Sep;11(9):2483.
1
[2] Alagorni AH, Yaacob ZB, Nour AH. An overview of oil production stages: enhanced oil recovery techniques and nitrogen injection. International Journal of Environmental Science and Development. 2015 Sep 1;6(9):693-701.
2
[3] Piccaglia R, Marotti M. Characterization of some Italian types of wild fennel (Foeniculum vulgare Mill.). Journal of Agricultural and Food Chemistry. 2001 Jan 15;49(1):239-44.
3
[4] Zekri AY, Shedid SA, Almehaideb RA. An experimental investigation of interactions between supercritical CO2, aspheltenic crude oil, and reservoir brine in carbonate cores. InInternational Symposium on Oilfield Chemistry 2007 Jan 1. Society of Petroleum Engineers.
4
[5] Subramanian S, Simon S, Sjöblom J. Asphaltene precipitation models: a review. Journal of Dispersion Science and Technology. 2016 Jul 2;37(7):1027-49.
5
[6] Arya A, Liang X, von Solms N, Kontogeorgis GM. Prediction of gas injection effect on asphaltene precipitation onset using the cubic and cubic-plus-association equations of state. Energy & Fuels. 2017 Mar 16;31(3):3313-28.
6
[7] Rastgoo A, Kharrat R. Investigation of asphaltene deposition and precipitation in production tubing. International Journal of Clean Coal and Energy. 2017 Jan 10;6(1):14-29.
7
[8] Hemmati-Sarapardeh A, Alipour-Yeganeh-Marand R, Naseri A, Safiabadi A, Gharagheizi F, Ilani-Kashkouli P, Mohammadi AH. Asphaltene precipitation due to natural depletion of reservoir: Determination using a SARA fraction based intelligent model. Fluid Phase Equilibria. 2013 Sep 25;354:177-84.
8
[9] Zendehboudi S, Ahmadi MA, Mohammadzadeh O, Bahadori A, Chatzis I. Thermodynamic investigation of asphaltene precipitation during primary oil production: laboratory and smart technique. Industrial & Engineering Chemistry Research. 2013 May 1;52(17):6009-31.
9
[10] Bouhadda Y, Bormann D, Sheu E, Bendedouch D, Krallafa A, Daaou M. Characterization of Algerian Hassi-Messaoud asphaltene structure using Raman spectrometry and X-ray diffraction. Fuel. 2007 Aug 1;86(12-13):1855-64.
10
[11] Neuhaus N, Nascimento PT, Moreira I, Scheer AP, Santos AF, Corazza ML. Thermodynamic analysis and modeling of brazilian crude oil and asphaltene systems: an experimental measurement and a pc-saft application. Brazilian Journal of Chemical Engineering. 2019 Mar;36(1):557-71.
11
[12] Mullins OC, Sabbah H, Eyssautier J, Pomerantz AE, Barré L, Andrews AB, Ruiz-Morales Y, Mostowfi F, McFarlane R, Goual L, Lepkowicz R. Advances in asphaltene science and the Yen–Mullins model. Energy & Fuels. 2012 Jul 19;26(7):3986-4003.
12
[13] Soleymanzadeh A, Yousefi M, Kord S, Mohammadzadeh O. A review on methods of determining onset of asphaltene precipitation. Journal of Petroleum Exploration and Production Technology. 2019 Jun 1;9(2):1375-96.
13
[14] Alhreez M, Wen D. Molecular structure characterization of asphaltene in the presence of inhibitors with nanoemulsions. RSC advances. 2019;9(34):19560-70.
14
[15] Santos D, Filho EB, Dourado RS, Amaral M, Filipakis S, Oliveira LM, Guimarães RC, Santos AF, Borges GR, Franceschi E, Dariva C. Study of asphaltene precipitation in crude oils at desalter conditions by near-infrared spectroscopy. Energy & Fuels. 2017 May 18;31(5):5031-6.
15
[16] Eshraghi SE, Kazemzadeh Y, Etemadan Z, Papi A. Detecting high-potential conditions of asphaltene precipitation in oil reservoir. Journal of Dispersion Science and Technology. 2018 Jul 3;39(7):943-51.
16
[17] Mohammadi S, Rashidi F, Mousavi‐Dehghani SA, Ghazanfari MH. On the effect of temperature on precipitation and aggregation of asphaltenes in light live oils. The Canadian Journal of Chemical Engineering. 2016 Sep;94(9):1820-9.
17
[18] Mahmoudi B, Zare-Reisabadi MR. Experimental study of temperature effect on onset pressure of asphaltene in live oil. Petroleum & Coal. 2015 Oct 1;57(4).
18
[19] Ashoori S, Balavi A. An investigation of asphaltene precipitation during natural production and the --CO2 injection process. Petroleum science and technology. 2014 Jun 3;32(11):1283-90.
19
[20] IP 143/84. Standard Methods for Analysis and Testing of Petroleum and Related Products.
20
[21] Abouie A, Darabi H, Sepehrnoori K. Data-driven comparison between solid model and PC-SAFT for modeling asphaltene precipitation. Journal of Natural Gas Science and Engineering. 2017 Sep 1;45:325-37.
21
[22] Hajizadeh N, Moradi G, Ashoori S. Modified SRK Equation of State for Modeling Asphaltene Precipitation. International Journal of Chemical Reactor Engineering. 2020 Feb 28;18(3).
22
[23] Zanganeh P, Dashti H, Ayatollahi S. Visual investigation and modeling of asphaltene precipitation and deposition during CO2 miscible injection into oil reservoirs. Fuel. 2015 Nov 15;160:132-9.
23
[24] Nghiem LX, Coombe DA, Ali SM. Compositional simulation of asphaltene deposition and plugging. InSPE Annual Technical Conference and Exhibition 1998 Jan 1. Society of Petroleum Engineers.
24
[25] Behbahani TJ, Ghotbi C, Taghikhani V, Shahrabadi A. Experimental investigation and thermodynamic modeling of asphaltene precipitation. Scientia Iranica. 2011 Dec 1;18(6):1384-90.
25
[26] Arya A, Liang X, Von Solms N, Kontogeorgis GM. Modeling of asphaltene onset precipitation conditions with cubic plus association (CPA) and perturbed chain statistical associating fluid theory (PC-SAFT) equations of state. Energy & Fuels. 2016 Aug 18;30(8):6835-52.
26
ORIGINAL_ARTICLE
Sizing, Parametric Investigation and Analysis of Automated Sucker Rod Pump using Beam Pump Simulators
Reciprocating piston artificial lift systems are widely adopted especially, for onshore wells. Matching the pump mode to well and reservoir conditions reduces the pumping cost and increases the efficiency of production. Parameters influencing the energy requirement of sucker-rod lifted oil wells are investigated in this study, and new insights are provided for the parametric investigation of design variables required for sizing beam-pumped wells. Two (2) artificial lift simulators are integrated for automated sizing of beam-pumped systems. A sucker-rod artificial lift system is optimally sized for a case study oil well, to obtain the minimum API rating of the pumping unit, sustain the target production rate, and determine the corresponding minimum prime mover required to drive the pump sustainably. Compared to using a single simulator for the case study, the integrated approach reduces the damped and polished rod horsepower by 54.9% and 26.5% respectively, for a corresponding decrease in minimum NEMA D motor size by 38.6%. These key performance indicators demonstrate the benefits of simulator integration in automated sizing of beam pumps.
https://jchpe.ut.ac.ir/article_77762_6d54f874adb2c9ef275d3b62264bacaa.pdf
2020-12-01
235
251
10.22059/jchpe.2020.295689.1303
Artificial lift simulator
Energy requirement
Parametric investigation
PROSPER
QRod
Sucker-rod pump
Charles
Osaretin
caosaretin@mun.ca
1
Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland St. John's, Newfoundland, Canada, A1B 3X5
LEAD_AUTHOR
Stephen
Butt
sdbutt@mun.ca
2
Department of Earth Sciences, Memorial University of Newfoundland , St. John's, Newfoundland, Canada, A1B 3X5.
AUTHOR
M. Tariq
Iqbal
tariq@mun.ca
3
Department of Electrical and Computer Engineering Faculty of Engineering and Applied Science Memorial University of Newfoundland St. John's, Newfoundland, Canada, A1B 3X5
AUTHOR
[1] Shedid SA. Effects of Subsurface Pump Size and Setting Depth on Performance of Sucker-Rod Artificial Lift: A Simulation Approach. InSPE Production and Operations Symposium 2009 Jan 1. Society of Petroleum Engineers.
1
[2] Aguilera RF. The Exceptional Price Performance of Oil–Explanations and Prospects. Natural gas. 2019;25:25.
2
[3] Dave MK, Ghareeb Mustafa M. Performance Evaluations of the Different Sucker Rod Artificial Lift Systems. InSPE Symposium: Production Enhancement and Cost Optimisation 2017 Nov 7. Society of Petroleum Engineers.
3
[4] McCoy JN, Podio AL, Drake B, Rowlan L. Modern Total Well Management-Sucker Rod Lift Case Study. InSPE Western Regional Meeting 2001 Jan 1. Society of Petroleum Engineers.
4
[5] Podio AL, McCoy JN, Becker D. Total well management-A methodology for minimizing production cost of beam pumped wells. InSPE Western Regional Meeting 1995 Jan 1. Society of Petroleum Engineers.
5
[6] Hein Jr NW, Loudermilk MD. Review of New API Pump Setting Depth Recommendations. InSPE Annual Technical Conference and Exhibition 1992 Jan 1. Society of Petroleum Engineers.
6
[7] Agarwal AK, Purwar S, Bravo CE. Real-time Diagnostic Analysis of Artificially Lifted Wells: A Smart Workflow Approach. InSPE Intelligent Energy Conference & Exhibition 2014 Apr 1. Society of Petroleum Engineers.
7
[8] Dave MK, Ghareeb Mustafa M. Performance Evaluations of the Different Sucker Rod Artificial Lift Systems. InSPE Symposium: Production Enhancement and Cost Optimisation 2017 Nov 7. Society of Petroleum Engineers.
8
[9] Xing M, Dong S. A new simulation model for a beam-pumping system applied in energy saving and resource-consumption reduction. SPE Production & Operations. 2015 May 1;30(02):130-40.
9
[10] Feng ZM, Tan JJ, Li Q, Fang X. A review of beam pumping energy-saving technologies. Journal of Petroleum Exploration and Production Technology. 2018 Mar 1;8(1):299-311.
10
[11] Di Tullio MT, Marfella F. Enhanced Sucker Rod Pumping Model: A Powerful Tool for Optimizing Production, Efficiency and Reliability. InSPE Middle East Artificial Lift Conference and Exhibition 2018 Nov 28. Society of Petroleum Engineers.
11
[12] Jennings JW. The Design of Sucker Rod Pump Systems. InSPE Centennial Symposium at New Mexico Tech 1989 Jan 1. Society of Petroleum Engineers.
12
[13] Durham MO, Lockerd CR. Beam pump motors: The effect of cyclical loading on optimal sizing. InSPE Annual Technical Conference and Exhibition 1988 Jan 1. Society of Petroleum Engineers.
13
[14] Paik ME. Reducing electric power costs in old oil fields. InSPE/DOE Improved Oil Recovery Symposium 1996 Jan 1. Society of Petroleum Engineers.
14
[15] Takacs G, Handbook SR. Production Engineering Fundamentals and Long-Stroke Rod Pumping‖. Sucker-Rod Pumping Handbook. 2015.
15
[16] Guo, B., Liu, X., & Tan, X. (2017). Petroleum production engineering. Cambridge: Gulf Professional Publishing.
16
[17] Rowlan OL, Mccoy JN, Podio AL. Best method to balance torque loadings on a pumping unit gearbox. Journal of Canadian Petroleum Technology. 2005 Jul 1;44(07).
17
[18] Hicks AW. Using fiberglass sucker rods in deep wells. InSPE Deep Drilling and Production Symposium 1986 Jan 1. Society of Petroleum Engineers.
18
[19] Osaretin CA, Iqbal T, Butt S. Optimal sizing and techno-economic analysis of a renewable power system for a remote oil well. AIMS Electronics and Electrical Engineering. 2020 Feb 18;4(2):132.
19
[20] Agrawal N, Baid R, Mishra L, Ghosh P, Kushwaha M. Quick look methodology for progressive cavity pump sizing and performance monitoring. InSPE Oil & Gas India Conference and Exhibition 2015 Nov 24. Society of Petroleum Engineers.
20
[21] Gibbs SG. Rod pumping. Modern methods of design, diagnosis and surveillance. BookMasters Inc., Ashland. 2012.
21
[22] Gibbs SG. A review of methods for design and analysis of rod pumping installations. Journal of Petroleum Technology. 1982 Dec 1;34(12):2-931.
22
[23] Palka K, Czyz J. Optimizing downhole fluid production of sucker rod pumps using variable motor speed. InSPE Western Regional and Pacific Section AAPG Joint Meeting 2008 Jan 1. Society of Petroleum Engineers.
23
[24] Bellarby J. Well completion design. Elsevier; 2009 Apr 13.
24
[25] Tripp HA. Mechanical performance of fiberglass sucker-rod strings. SPE production engineering. 1988 Aug 1;3(03):346-50.
25
[26] Watkins DL, Haarsma J. Fiberglass sucker rods in beam-pumped oil wells. Journal of Petroleum Technology. 1978 May 1;30(05):731-6.
26
[27] Gibbs SG. Application of fiberglass sucker rods. SPE Production Engineering. 1991 May 1;6(02):147-54.
27
[28] Tripp HA. Mechanical performance of fiberglass sucker-rod strings. SPE production engineering. 1988 Aug 1;3(03):346-50.
28
[29] Takács G. „Sucker-Rod Pumping Manual” PennWell Books. Tulsa, Oklahoma. 2003.
29
[30] Rowlan L (2006). International Sucker Rod Pumping Workshop, South-Western Petroleum Short Course. Artificial Lift Research and Development Council (ALRDC).
30
[31] National Electrical Manufacturers Association (NEMA) (2018) Standards. ANSI/NEMA Motors and Generators MG1.
31
[32] Lekia SD, Evans RD. A Coupled Rod and Fluid Dynamic Model for Predicting the Behavior of Sucker-Rod Pumping Systems-Part 2: Parametric Study and Demonstration of Model Capabilities. SPE Production & Facilities. 1995 Feb 1;10(01):34-40.
32
[33] Lyons W C, Plisga G J & Lorentz M D (2015). Standard Handbook of Petroleum and Natural Gas Engineering. Gulf Professional Publishing, Tulsa
33
[34] PROSPER™ User Manual, 2015.
34
ORIGINAL_ARTICLE
A Predictive Correlation for Vapor-Liquid Equilibrium of CO2 + n-Alkane Ternary Systems Based on Cubic Mixing Rules
The accurate description of the phase equilibria of CO2 and n-alkane multicomponent mixtures over a wide range of temperature, pressure, and n-alkane molecular weight, requires the models that are both consistent and mathematically flexible for such highly non-ideal systems. In this study, a predictive correlation was proposed for the vapor-liquid equilibrium data (VLE) of CO2 and n-alkane ternary systems, based on the Peng-Robinson equation of state (PR EOS), coupled to cubic mixing rules (CMRs). The ternary interaction parameters (TIP) correlation is developed using binary VLE data and tested for CO2 + n-alkane+ n-alkane ternary systems. For this purpose, binary VLE data of CO2 + n-alkane and n-alkane + n-alkane systems for n-alkane from C3 to C24, covering a total of about 70 references, used to correlate TIP in the ranges of 0.5-31 MPa and 230-663 K. Two temperature-dependent TIP correlations, based on acentric factor ratio, have been tuned with more than 2000 data points of the CO2 + n-alkane and the n-alkane + n-alkane binary systems with AARD of 3.13% and 6.71%, respectively. The generalized predictive correlation was proposed based on the proper three-body interaction contributions and successfully tested for VLE data of the CO2 + n-alkane + n-alkane ternary systems.
https://jchpe.ut.ac.ir/article_78414_f7d2366b110ba89cb13f0e1c54dc6652.pdf
2020-12-01
253
272
10.22059/jchpe.2020.295906.1305
Vapor-Liquid Equilibrium
Ternary interaction parameter
CO2
n-Alkane
Peng-Robinson EOS
Predictive Model
Seyed Mohammad
Arzideh
sm_arzideh@yahoo.com
1
Babol University of Technology, Faculty of Chemical Engineering, Babol, Iran
AUTHOR
Kamyar
Movagharnejad
k-movaghar@nit.ac.ir
2
Babol University of Technology, Faculty of Chemical Engineering, Babol, Iran
LEAD_AUTHOR
[1] A.-J. Shen, Q. Liu, Y.-Y. Duan, and Z. Yang, "Crossover VTSRK equation of state for selected alkane+ alkane and CO 2+ alkane binary mixtures," Fluid Phase Equilibria, vol. 408, pp. 180-189, 2016.
1
[2] J. A. Coutinho, G. M. Kontogeorgis, and E. H. Stenby, "Binary interaction parameters for nonpolar systems with cubic equations of state: a theoretical approach 1. CO2/hydrocarbons using SRK equation of state," Fluid phase equilibria, vol. 102, no. 1, pp. 31-60, 1994.
2
[3] H. Li, S. Zheng, and D. T. Yang, "Enhanced swelling effect and viscosity reduction of solvent (s)/CO2/heavy-oil systems," Spe Journal, vol. 18, no. 04, pp. 695-707, 2013.
3
[4] C. Lerouge, M. Blessing, C. Flehoc, E. Gaucher, B. Henry, A. Lassin, N. Marty, J. Matray, E. Proust, and D. Rufer, "Dissolved CO2 and alkane gas in clay formations," Procedia Earth and Planetary Science, vol. 13, pp. 88-91, 2015.
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[5] F. Chang, J. Jin, N. Zhang, G. Wang, and H.-J. Yang, "The effect of the end group, molecular weight and size on the solubility of compounds in supercritical carbon dioxide," Fluid Phase Equilibria, vol. 317, pp. 36-42, 2012.
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[6] I. Tsivintzelis, S. Ali, and G. M. Kontogeorgis, "Modeling phase equilibria for acid gas mixtures using the CPA equation of state. Part IV. Applications to mixtures of CO 2 with alkanes," Fluid Phase Equilibria, vol. 397, pp. 1-17, 2015.
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[7] E. Ebrahimzadeh, J. Matagi, F. Fazlollahi, and L. L. Baxter, "Alternative extractive distillation system for CO 2–ethane azeotrope separation in enhanced oil recovery processes," Applied Thermal Engineering, vol. 96, pp. 39-47, 2016.
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[8] M. Van Den Broek, N. Berghout, and E. S. Rubin, "The potential of renewables versus natural gas with CO 2 capture and storage for power generation under CO 2 constraints," Renewable and Sustainable Energy Reviews, vol. 49, pp. 1296-1322, 2015.
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[9] I. Polishuk, J. Wisniak, and H. Segura, "Estimation of liquid− liquid− vapor equilibria using predictive EOS models. 1. Carbon dioxide− n-alkanes," The Journal of Physical Chemistry B, vol. 107, no. 8, pp. 1864-1874, 2003.
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[10] A. M. Abudour, S. A. Mohammad, R. L. Robinson Jr, and K. A. Gasem, "Generalized binary interaction parameters for the Peng–Robinson equation of state," Fluid Phase Equilibria, vol. 383, pp. 156-173, 2014.
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[11] J. R. Elliott and C. T. Lira, Introductory chemical engineering thermodynamics. Prentice Hall PTR Upper Saddle River, NJ, 1999.
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[12] J. O. Valderrama, S. Obaid-Ur-Rehman, and L. A. Cisternas, "Generalized interaction parameters in cubic equations of state for CO2—n-alkane mixtures," Fluid Phase Equilibria, vol. 40, no. 3, pp. 217-233, 1988.
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[13] M. Cismondi, S. B. Rodríguez-Reartes, J. M. Milanesio, and M. S. Zabaloy, "Phase equilibria of CO2+ n-alkane binary systems in wide ranges of conditions: Development of predictive correlations based on cubic mixing rules," Industrial & Engineering Chemistry Research, vol. 51, no. 17, pp. 6232-6250, 2012.
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[14] M. S. Zabaloy, "Cubic mixing rules," Industrial & Engineering Chemistry Research, vol. 47, no. 15, pp. 5063-5079, 2008.
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[15] T. Brown, V. Niesen, E. Sloan, and A. Kidnay, "Vapor-liquid equilibria for the binary systems of nitrogen, carbon dioxide, and n-butane at temperatures from 220 to 344 K," Fluid phase equilibria, vol. 53, pp. 7-14, 1989.
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[16] P. M. Mathias, H. C. Klotz, and J. M. Prausnitz, "Equation-of-state mixing rules for multicomponent mixtures: the problem of invariance," Fluid Phase Equilibria, vol. 67, pp. 31-44, 1991.
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[17] M. Cismondi, J. M. Mollerup, and M. S. Zabaloy, "Equation of state modeling of the phase equilibria of asymmetric CO 2+ n-alkane binary systems using mixing rules cubic with respect to mole fraction," The Journal of Supercritical Fluids, vol. 55, no. 2, pp. 671-681, 2010.
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[18] K. Kato, K. Nagahama, and M. Hirata, "Generalized interaction parameters for the Peng—Robinson equation of state: carbon dioxide—n-paraffin binary systems," Fluid Phase Equilibria, vol. 7, no. 3-4, pp. 219-231, 1981.
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[19] A. Kordas, K. Tsoutsouras, S. Stamataki, and D. Tassios, "A generalized correlation for the interaction coefficients of CO2—hydrocarbon binary mixtures," Fluid Phase Equilibria, vol. 93, pp. 141-166, 1994.
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[20] X. Li, D. Yang, X. Zhang, G. Zhang, and J. Gao, "Binary interaction parameters of CO 2− heavy-n-alkanes systems by using Peng–Robinson equation of state with modified alpha function," Fluid Phase Equilibria, vol. 417, pp. 77-86, 2016.
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[21] D. Fu, L. Liang, X.-S. Li, S. Yan, and T. Liao, "Investigation of vapor− liquid equilibria for supercritical carbon dioxide and hydrocarbon mixtures by perturbed-chain statistical associating fluid theory," Industrial & engineering chemistry research, vol. 45, no. 12, pp. 4364-4370, 2006.
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[22] M. Kariznovi, H. Nourozieh, and J. Abedi, "Phase composition and saturated liquid properties in binary and ternary systems containing carbon dioxide, n-decane, and n-tetradecane," The Journal of Chemical Thermodynamics, vol. 57, pp. 189-196, 2013.
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[23] A. Kumar and R. Okuno, "Critical parameters optimized for accurate phase behavior modeling for heavy n-alkanes up to C 100 using the Peng–Robinson equation of state," Fluid Phase Equilibria, vol. 335, pp. 46-59, 2012.
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[24] C. Sánchez-García, K. E. Vázquez-Hernández, L. A. Galicia-Luna, and O. Elizalde-Solis, "Vapor–Liquid Equilibrium Measurements for the Ternary Systems of CO2+ n-Hexane+ n-Decane and CO2+ n-Octane+ n-Decane," Industrial & Engineering Chemistry Research, vol. 50, no. 21, pp. 12254-12258, 2011.
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[25] J. O. Valderrama, S. Obaid-Ur-Rehman, and L. A. Cisternas, "Application of a new cubic equation of state to hydrogen sulfide mixtures," Chemical engineering science, vol. 42, no. 12, pp. 2935-2940, 1987.
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[26] G. Pisoni, S. Rodriguez-Reartes, J. Ramello, M. Cismondi, and M. Zabaloy, "A study on the effect of ternary interaction parameters on the equation of state description of ternary fluid phase equilibria," Fluid Phase Equilibria, vol. 391, pp. 54-66, 2015.
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[27] V. G. Niesen and J. C. Rainwater, "Critical locus,(vapor+ liquid) equilibria, and coexisting densities of (carbon dioxide+ propane) at temperatures from 311 K to 361 K," The Journal of Chemical Thermodynamics, vol. 22, no. 8, pp. 777-795, 1990.
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[28] L. A. Webster and A. J. Kidnay, "Vapor− liquid equilibria for the methane− propane− carbon dioxide systems at 230 K and 270 K," Journal of Chemical & Engineering Data, vol. 46, no. 3, pp. 759-764, 2001.
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[29] J. J. Hsu, N. Nagarajan, and R. Robinson Jr, "Equilibrium phase compositions, phase densities, and interfacial tensions for carbon dioxide+ hydrocarbon systems. 1. Carbon dioxide+ n-butane," Journal of Chemical and Engineering Data, vol. 30, no. 4, pp. 485-491, 1985.
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[32] A. Q. Clark and K. Stead, "(Vapour+ liquid) phase equilibria of binary, ternary, and quaternary mixtures of CH4, C2H6, C3H8, C4H10, and CO2," The Journal of Chemical Thermodynamics, vol. 20, no. 4, pp. 413-427, 1988.
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[34] K. Tochigi, K. Hasegawa, N. Asano, and K. Kojima, "Vapor− liquid equilibria for the carbon dioxide+ pentane and carbon dioxide+ toluene systems," Journal of Chemical & Engineering Data, vol. 43, no. 6, pp. 954-956, 1998.
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[35] A. D. Leu and D. B. Robinson, "Equilibrium phase properties of selected carbon dioxide binary systems: n-pentane-carbon dioxide and isopentane-carbon dioxide," Journal of Chemical and Engineering Data, vol. 32, no. 4, pp. 447-450, 1987.
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[36] K. Ohgaki and T. Katayama, "Isothermal vapor-liquid equilibrium data for binary systems containing carbon dioxide at high pressures: methanol-carbon dioxide, n-hexane-carbon dioxide, and benzene-carbon dioxide systems," Journal of chemical and Engineering Data, vol. 21, no. 1, pp. 53-55, 1976.
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89
ORIGINAL_ARTICLE
Cuttings Transport Modeling in Wellbore Annulus in Oil Drilling Operation using Evolutionary Fuzzy System
A difficult problem in drilling operation that concerns the very drilling parameters is the cutting transport process. Correct calculation of the cuttings concentration (hole cleaning efficiency) in the wellbore annulus using drilling variables such as the geometry of wellbore, rheology, and density of drilling fluid, and pump rate is very important for optimizing these variables. In this study, a hybrid evolutionary fuzzy system (EFS) using artificial intelligent (AI) techniques is presented for estimation of the cuttings concentration in oil drilling operation using operational drilling parameters. A well-organized genetic learning algorithm that computes fitness values by symbiotic evolution is used for extraction of the Takagi–Sugeno–Kang (TSK) type fuzzy rule-based system for the EFS. A determination coefficient (R2) of 0.877 together with a root mean square error (RMSE) of 1.4 between prediction and measured data for test data verified a very satisfactory model performance. Results confirmed that the estimation accuracy of the proposed EFS is better than other models such as Multiple Linear Regression (MLR), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) for hole cleaning modeling.
https://jchpe.ut.ac.ir/article_77259_e02c3b6f02e659eb454b42c5aef6fbe9.pdf
2020-12-01
273
283
10.22059/jchpe.2020.297247.1307
Artificial intelligent methods
Drilling
EFS
Hole cleaning
Wellbore
Reza
Rooki
reza_rooki@yahoo.com
1
Department of Mining, Civil and Chemical Engineering, Birjand University of Technology, Birjand, Iran
LEAD_AUTHOR
Seyed Mohammad Reza
Kazemi
kazemi@birjandut.ac.ir
2
Department of Computer and Industrial Engineering, Birjand University of Technology, Birjand, Iran
AUTHOR
Esmaeil
Hadavandi
eshadavandi@birjandut.ac.ir
3
Department of Computer and Industrial Engineering, Birjand University of Technology, Birjand, Iran
AUTHOR
Seyed Mahmood
Kazemi
kazemi_m_s@birjandut.ac.ir
4
Department of Computer and Industrial Engineering, Birjand University of Technology, Birjand, Iran
AUTHOR
[1] Larsen TI, Pilehvari AA, Azar JJ. Development of a new cuttings-transport model for high-angle wellbores including horizontal wells. SPE Drilling & Completion. 1997 Jun 1;12(02):129-36.
1
[2] Tomren PH, Iyoho AW, Azar JJ. Experimental study of cuttings transport in directional wells. SPE Drilling Engineering. 1986 Feb 1;1(01):43-56.
2
[3] Mirhaj SA, Shadizadeh R, Fazaeli-zadeh M. Cuttings removal simulation for deviated and horizontal wellbores. InSPE Middle East Oil and Gas Show and Conference 2007 Mar 11.
3
[4] Bourgoyne Jr AT, Millheim KK, Chenevert ME, Young Jr FS. Applied drilling engineering chapter 8 solutions.
4
[5] Rooki R, Ardejani FD, Moradzadeh A. Hole cleaning prediction in foam drilling using artificial neural network and multiple linear regression. Geomaterials. 2014 Jan 9;2014.
5
[6] Rooki R, Ardejani FD, Moradzadeh A, Norouzi M. CFD simulation of rheological model effect on cuttings transport. Journal of Dispersion Science and Technology. 2015 Mar 4;36(3):402-10.
6
[7] Duan, M., 2007. Study of Cuttings Transport Using Foam with Drill Pipe Rotation under Simulated Downhole Conditions, PhD Dissertation, Tulsa University, USA.
7
[8] Chen Z. Cuttings transport with foam in horizontal concentric annulus under elevated pressure and temperature conditions. The University of Tulsa; 2005.
8
[9] Ozbayoglu, M.E., 2002. Cuttings transport with foam in horizontal and highly-inclined wellbores, PhD Dissertation, University of Tulsa, USA.
9
[10] Rojas Y, Vieira P, Borrell M, Blanco J, Ford M, Nieto L, Lopez G, Atencio B. Field application of near-balanced drilling using aqueous foams in western Venezuela. InIADC/SPE Drilling Conference 2002 Jan 1. Society of Petroleum Engineers.
10
[11] Suradi SR, Mamat NS, Jaafar MZ, Sulaiman WR, Ismail AR. Study of cuttings transport using stable foam based mud in inclined wellbore. J. Appl. Sci.. 2015 Mar 1;15(5):808.
11
[12] He M, Zhang Y, Xu M, Li J, Song J. Real-Time Interpretation Model of Reservoir Characteristics While Underbalanced Drilling Based on UKF. Geofluids. 2020 May 19;2020.
12
[13] Okpobiri GA, Ikoku CU. Volumetric requirements for foam and mist drilling operations. SPE Drilling Engineering. 1986 Feb 1;1(01):71-88.
13
[14] Guo, B., Miska, S., and Hareland, G., 1995. A simple approach to determination of bottom hole pressure in directional foam drilling, ASME Drilling Technology Symposium, PD-Vol. 65: 329-338.
14
[15] STAINTPERE S. Hole Cleaning Capabilities of Drilling Foams Compared to Conventional Fluids. Inpresented at the 2000 SPE Annual Technical Conference and Exhibitions, Dallas-Texas 2000.
15
[16] Li Y, Kuru E. Numerical modelling of cuttings transport with foam in horizontal wells. Journal of Canadian Petroleum Technology. 2003 Oct 1;42(10).
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[17] Li, Y., Kuru, E., 2005, Numerical modeling of cuttings transport with foam in vertical wells, Journal of Canadian Petroleum Technology 44(3): 31-39.
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[18] Martins, A.L., Luorenco, A.M.F de Sa, C.H.M., 2001. Foam properties requirements for proper hole cleaning while drilling horizontal wells in underbalanced conditions, SPE Drill & Completion 16 (4): 195-200.
18
[19] Capo, J., Yu, M., and Miska, S. Z., Takach, N.E., Ahmed, R., 2006. Cuttings transport with aqueous foam at intermediate inclined wells [C], SPE Drilling and Completion 21(2):99–107.
19
[20] Arya A, Liang X, Von Solms N, Kontogeorgis GM. Modeling of asphaltene onset precipitation conditions with cubic plus association (CPA) and perturbed chain statistical associating fluid theory (PC-SAFT) equations of state. Energy & Fuels. 2016 Jul 26;30(8):6835-52.
20
[21] Chen Z, Ahmed RM, Miska SZ, Takach NE, Yu M, Pickell MB, Hallman JH. Experimental study on cuttings transport with foam under simulated horizontal downhole conditions. SPE Drilling & Completion. 2007 Dec 1;22(04):304-12..
21
[22] Yan T, Wang K, Sun X, Luan S, Shao S. State-of-the-art cuttings transport with aerated liquid and foam in complex structure wells. Renewable and Sustainable Energy Reviews. 2014 Sep 1;37:560-8.
22
[23] Hadavandi E, Shavandi H, Ghanbari A, Abbasian-Naghneh S. Developing a hybrid artificial intelligence model for outpatient visits forecasting in hospitals. Applied Soft Computing. 2012 Feb 1;12(2):700-11.
23
[24] Braunschweig, B., Bremdal B.A. 1996, Artificial intelligence in the petroleum industry: symbolic and computational applications. Volume 2, Editions TECHNIP, Technology & Engineering - 381 pages.
24
[25] Rooki R. Application of general regression neural network (GRNN) for indirect measuring pressure loss of Herschel–Bulkley drilling fluids in oil drilling. Measurement. 2016 May 1;85:184-91.
25
[26] Bello O, Holzmann J, Yaqoob T, Teodoriu C. Application of artificial intelligence methods in drilling system design and operations: a review of the state of the art. Journal of Artificial Intelligence and Soft Computing Research. 2015 Apr 1;5(2):121-39.
26
[27] Cranganu C, Luchian H, Breaban ME, editors. Artificial intelligent approaches in petroleum geosciences. Berlin: Springer; 2015 Apr 18.
27
[28] Al-Azani K, Elkatatny S, Ali A, Ramadan E, Abdulraheem A. Cutting concentration prediction in horizontal and deviated wells using artificial intelligence techniques. Journal of Petroleum Exploration and Production Technology. 2019 Dec 1;9(4):2769-79.
28
[29] Ouaer H, Gareche M, Rooki R. Rheological studies and optimization of Herschel–Bulkley parameters of an environmentally friendly drilling fluid using genetic algorithm. Rheologica Acta. 2018 Nov 1;57(11):693-704.
29
[30] Cord O. Genetic fuzzy systems: evolutionary tuning and learning of fuzzy knowledge bases. World Scientific; 2001.
30
[31] Herrera F. Genetic fuzzy systems: taxonomy, current research trends and prospects. Evolutionary Intelligence. 2008 Mar 1;1(1):27-46. [32] Kazemi SM, Hadavandi E, Mehmanpazir F, Nakhostin MM. A hybrid intelligent approach for modeling brand choice and constructing a market response simulator. Knowledge-Based Systems. 2013 Mar 1;40:101-10.
31
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32
[34] Juang CF, Lin JY, Lin CT. Genetic reinforcement learning through symbiotic evolution for fuzzy controller design. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 2000 Apr;30(2):290-302.
33
[35] Shahrabi J, Hadavandi E, Asadi S. Developing a hybrid intelligent model for forecasting problems: Case study of tourism demand time series. Knowledge-Based Systems. 2013 May 1;43:112-22.
34
[36] Eiben ÁE, Hinterding R, Michalewicz Z. Parameter control in evolutionary algorithms. IEEE Transactions on evolutionary computation. 1999 Jul;3(2):124-41.
35
ORIGINAL_ARTICLE
Liquid-Liquid Equilibrium for Ternary Systems Containing Biodiesel+ Glycerol+ Alcohol (Ethanol or Methanol): Thermodynamic Modeling
Biodiesel is a substitute for fossil fuels which is produced through a transesterification reaction between vegetable oils or animal fats and light alcohols such as methanol or ethanol. In this reaction, along with the production of biodiesel, glycerol as a byproduct and non-reacted alcohol that reduces biodiesel quality is produced. Hence, many studies have been carried out on liquid-liquid equilibrium (LLE) for ternary systems containing biodiesel + glycerol + alcohol. Two phases are formed as 1-rich in biodiesel and 2-rich in glycerol; moreover, alcohol is distributed between these two phases. In this work, based on previous experimental data, the UNIQUAC and NRTL thermodynamic models were used to forecast the composition of the phases. The intermolecular interaction term for each of the models was considered as a linear function of the reverse temperature. In both models, there was no difference between the amount of biodiesel produced from different oils and obtained from the general interaction parameters. Based on the results, the percentage of absolute average deviation for NRTL and UNIQUAC models for biodiesel + glycerol + ethanol system were 1.24% and 2.13%, respectively, and for biodiesel + glycerol + methanol system was 1.13% and 1.71%, respectively.
https://jchpe.ut.ac.ir/article_78318_ae09c5bada806afa9eeefc6722fb7d99.pdf
2020-12-01
285
295
10.22059/jchpe.2020.299983.1309
Biodiesel
Ethanol or methanol
Glycerol
LLE
NRTL
UNIQUAC
Majid
Mohadesi
m.mohadesi@kut.ac.ir
1
Department of Chemical Engineering, Faculty of Energy, Kermanshah University of Technology, Kermanshah, Iran
LEAD_AUTHOR
[1] Subramaniam R, Dufreche S, Zappi M, Bajpai R. Microbial lipids from renewable resources: production and characterization. Journal of industrial microbiology & biotechnology. 2010 Dec 1;37(12):1271-87.
1
[2] Demirbas A. Political, economic and environmental impacts of biofuels: A review. Applied energy. 2009 Nov 1;86:S108-17.
2
[3] Monyem A, Van Gerpen JH. The effect of biodiesel oxidation on engine performance and emissions. Biomass and bioenergy. 2001 Apr 1;20(4):317-25..
3
[4] Van Gerpen J. Biodiesel processing and production. Fuel processing technology. 2005 Jun 25;86(10):1097-107.
4
[5] Kralova I, Sjöblom J. Biofuels–renewable energy sources: a review. Journal of Dispersion Science and Technology. 2010 Feb 26;31(3):409-25.
5
[6] Van Gerpen J, Shanks B, Pruszko R, Clements D, Knothe G. Biodiesel Analytical Methods: August 2002--January 2004. National Renewable Energy Lab., Golden, CO (US); 2004 Jul 1.
6
[7] Van Gerpen JH, Hammond EG, Yu L, Monyem A. Determining the influence of contaminants on biodiesel properties. SAE Technical Paper; 1997 May 1.
7
[8] Hakim M, Abedini Najafabadi H, Pazuki G, Vossoughi M. Novel Approach for Liquid–Liquid Phase Equilibrium of Biodiesel (Canola and Sunflower)+ Glycerol+ Methanol. Industrial & Engineering Chemistry Research. 2014 Jan 15;53(2):855-64.
8
[9] Kuramochi H, Maeda K, Kato S, Osako M, Nakamura K, Sakai SI. Application of UNIFAC models for prediction of vapor–liquid and liquid–liquid equilibria relevant to separation and purification processes of crude biodiesel fuel. Fuel. 2009 Aug 1;88(8):1472-7.
9
[10] Negi DS, Sobotka F, Kimmel T, Wozny G, Schomäcker R. Liquid− liquid phase equilibrium in glycerol− methanol− methyl oleate and glycerol− monoolein− methyl oleate ternary systems. Industrial & engineering chemistry research. 2006 May 10;45(10):3693-6.
10
[11] Rostami M, Raeissi S, Mahmoodi M, Nowroozi M. Liquid–liquid equilibria in biodiesel production. Journal of the American Oil Chemists' Society. 2013 Jan 1;90(1):147-54.
11
[12] Mesquita FM, Evangelista NS, de Sant’Ana HB, de Santiago-Aguiar RS. Liquid–liquid equilibrium for the glycerol+ alcohol+ coconut biodiesel system at different temperatures and atmospheric pressure. Journal of Chemical & Engineering Data. 2012 Dec 13;57(12):3557-62.
12
[13] Di Felice R, De Faveri D, De Andreis P, Ottonello P. Component distribution between light and heavy phases in biodiesel processes. Industrial & engineering chemistry research. 2008 Oct 15;47(20):7862-7.
13
[14] Mesquita FM, Feitosa FX, Sombra NE, de Santiago-Aguiar RS, de Sant'Ana HB. Liquid–liquid equilibrium for ternary mixtures of biodiesel (soybean or sunflower) + glycerol + ethanol at different temperatures. Journal of Chemical & Engineering Data. 2011 Nov 10;56(11):4061-7.
14
[15] Machado AB, Ardila YC, de Oliveira LH, Aznar M, Wolf Maciel MR. Liquid–liquid equilibria in ternary and quaternary systems present in biodiesel production from soybean oil at (298.2 and 333.2) K. Journal of Chemical & Engineering Data. 2012 May 10;57(5):1417-22.
15
[16] Machado AB, Ardila YC, de Oliveira LH, Aznar M, Wolf Maciel MR. Liquid− Liquid Equilibrium Study in Ternary Castor Oil Biodiesel+ Ethanol+ Glycerol and Quaternary Castor Oil Biodiesel+ Ethanol+ Glycerol+ NaOH Systems at (298.2 and 333.2) K. Journal of Chemical & Engineering Data. 2011 May 12;56(5):2196-201.
16
[17] Mazutti MA, Voll FA, Cardozo-Filho L, Corazza ML, Lanza M, Priamo WL, Oliveira JV. Thermophysical properties of biodiesel and related systems:(Liquid+ liquid) equilibrium data for castor oil biodiesel. The Journal of Chemical Thermodynamics. 2013 Jul 1;62:17-26.
17
[18] Mesquita FM, Bessa AM, de Lima DD, de Sant’Ana HB, de Santiago-Aguiar RS. Liquid–liquid equilibria of systems containing cottonseed biodiesel+ glycerol+ ethanol at 293.15, 313.15 and 333.15 K. Fluid phase equilibria. 2012 Mar 25;318:51-5.
18
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19
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20
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21
[22] de Azevedo Rocha EG, Follegatti-Romero LA, Duvoisin Jr S, Aznar M. Liquid–liquid equilibria for ternary systems containing ethylic palm oil biodiesel+ ethanol+ glycerol/water: Experimental data at 298.15 and 323.15 K and thermodynamic modeling. Fuel. 2014 Jul 15;128:356-65.
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23
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24
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28
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31
ORIGINAL_ARTICLE
Thermodynamic Modeling of the Gas-Antisolvent (GAS) Process for Precipitation of Finasteride
Experimental study of the effect of gas antisolvent (GAS) system conditions on the particle size distribution of finasteride (FNS) requires a thermodynamic model for the volume expansion process. In this study, the phase behavior of the binary system including carbon dioxide and Dimethyl sulfoxide, and a ternary system comprising carbon dioxide, dimethyl sulfoxide, and Finasteride was studied. The Peng-Robinson equation of state was employed for the evaluation of the fluid phases and a fugacity expression to represent the solid phase. By developing an accurate predictive model, the GAS operating conditions can be optimized to produce particles with no need for a large number of experiments. First, the critical properties of the FNS were evaluated by the group contribution methods. The method of Marrero and Gani was also selected to predict the normal boiling point, critical temperature, and critical pressure. The correlation of Edmister was chosen for the prediction of the acentric factor. The lowest pressures for the ternary system at 308, 318, 328, and 338 K were 7.49, 8.13, 8.51, and 9.03 MPa, respectively. The precipitation of the dissolved finasteride happened at these operating pressures.
https://jchpe.ut.ac.ir/article_77330_fd6a6f3fa051f81287b5459a3821f39f.pdf
2020-12-01
297
309
10.22059/jchpe.2020.300747.1311
Finasteride
Genetic Algorithm
Group Contribution
Supercritical Fluid
Thermodynamic Modeling
Mohammad
Najafi
najafi.mohmd@gmail.com
1
Department of Chemical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
AUTHOR
Nadia
Esfandiari
esfandiari_n@miau.ac.ir
2
Department of Chemical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
LEAD_AUTHOR
Bizhan
Honarvar
honarvar2@gmail.com
3
Department of Chemical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
AUTHOR
Zahra
Arab Aboosadi
zarababoosadi@yahoo.com
4
Department of Chemical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran
AUTHOR
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12
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[18] Wichianphong N, Charoenchaitrakool M. Application of Box–Behnken design for processing of mefenamic acid–paracetamol cocrystals using gas anti-solvent (GAS) process. Journal of CO2 Utilization. 2018 Jul 1;26:212-20.
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[19] Ulker Z, Erkey C. An advantageous technique to load drugs into aerogels: Gas antisolvent crystallization inside the pores. The Journal of Supercritical Fluids. 2017 Feb 1;120:310-9.
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[20] Dittanet P, Phothipanyakun S, Charoenchaitrakool M. Co-precipitation of mefenamic acid− polyvinylpyrrolidone K30 composites using Gas Anti-Solvent. Journal of the Taiwan Institute of Chemical Engineers. 2016 Jun 1;63:17-24.
20
[21] Lőrincz L, Bánsághi G, Zsemberi M, de Simón Brezmes S, Szilágyi IM, Madarász J, Sohajda T, Székely E. Diastereomeric salt precipitation based resolution of ibuprofen by gas antisolvent method. The Journal of Supercritical Fluids. 2016 Dec 1;118:48-53.
21
[22] Esfandiari N, Ghoreishi SM. Kinetic Modeling of the Gas Antisolvent Process for Synthesis of 5‐Fluorouracil Nanoparticles. Chemical Engineering & Technology. 2014 Jan;37(1):73-80.
22
[23] Esfandiari N, Ghoreishi SM. Kinetics modeling of ampicillin nanoparticles synthesis via supercritical gas antisolvent process. The Journal of Supercritical Fluids. 2013 Sep 1;81:119-27.
23
[24] Esfandiari N, Ghoreishi SM. Synthesis of 5-fluorouracil nanoparticles via supercritical gas antisolvent process. The Journal of Supercritical Fluids. 2013 Dec 1;84:205-10.
24
[25] Jafari D, Nowee SM, Noie SH. A kinetic modeling of particle formation by gas antisolvent process: Precipitation of aspirin. Journal of Dispersion Science and Technology. 2017 May 4;38(5):677-85.
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[27] Bakhbakhi Y, Charpentier PA, Rohani S. Experimental study of the GAS process for producing microparticles of beclomethasone-17, 21-dipropionate suitable for pulmonary delivery. International journal of pharmaceutics. 2006 Feb 17;309(1-2):71-80.
27
[28] Esfandiari N, Ghoreishi SM. Ampicillin Nanoparticles Production via Supercritical CO2 Gas Antisolvent Process. AAPS PharmSciTech. 2015 Dec 1;16(6):1263-9.
28
[29] Mukhopadhyay M. Partial molar volume reduction of solvent for solute crystallization using carbon dioxide as antisolvent. The Journal of supercritical fluids. 2003 Apr 1;25(3):213-23.
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[31] Esfandiari N, Ghoreishi SM. Optimal thermodynamic conditions for ternary system (CO2, DMSO, ampicillin) in supercritical CO2 antisolvent process. Journal of the Taiwan Institute of Chemical Engineers. 2015 May 1;50:31-6.
31
[32] Kloc AP, Grilla E, Capeletto CA, Papadaki M, Corazza ML. Phase equilibrium measurements and thermodynamic modeling of {CO2+ diethyl succinate+ cosolvent} systems. Fluid Phase Equilibria. 2019 Dec 15;502:112285.
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33
[34] Almeida HM, Marques HM. Physicochemical characterization of finasteride: PEG 6000 and finasteride: Kollidon K25 solid dispersions, and finasteride: β-cyclodextrin inclusion complexes. Journal of Inclusion Phenomena and Macrocyclic Chemistry. 2011 Aug 1;70(3-4):397-406.
34
[35] Ahmed TA, Al-Abd AM. Effect of finasteride particle size reduction on its pharmacokinetic, tissue distribution and cellular permeation. Drug Delivery. 2018 Jan 1;25(1):555-63.
35
[36] Yamini Y, Kalantarian P, Hojjati M, Esrafily A, Moradi M, Vatanara A, Harrian I. Solubilities of flutamide, dutasteride, and finasteride as antiandrogenic agents, in supercritical carbon dioxide: Measurement and correlation. Journal of Chemical & Engineering Data. 2010 Feb 11;55(2):1056-9.
36
[37] Shariati A, Peters CJ. Measurements and modeling of the phase behavior of ternary systems of interest for the GAS process: I. The system carbon dioxide+ 1-propanol+ salicylic acid. The Journal of supercritical fluids. 2002 Aug 1;23(3):195-208.
37
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42
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43
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47
[48] Esfandiari N, Estimation of Thermodynamic Properties of Ampicillin and Paclitaxel via Group Contribution, The 9th International Chemical Engineering Congress & Exhibition, Shiraz, Iran, 26-28 December, 2015.
48
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50
ORIGINAL_ARTICLE
Improving CO2 /N2 and CO2/H2 Selectivity of Hypercrosslinked Carbazole-Based Polymeric Adsorbent for Environmental Protection
In this study, carbazole-based hypercrosslinked polymer (HCP) adsorbent was synthesized using the knitting method by Friedel-Crafts reaction. The effects of crosslinker to carbazole ratio and synthesis time on the adsorbent structure were investigated to improve CO2/N2 and CO2/H2 selectivity. Crosslinker to carbazole ratio and the synthesis time was considered in the range of 1-4 (mol/mol) and 8-18 (h), respectively. HCP adsorbents were analyzed by energy-dispersive X-ray spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), and Brunauer-Emmett-teller analysis (BET). The adsorption capacity of CO2, N2, and H2 were measured by carbazole-based HCP and it was correlated with the nonlinear form of the Langmuir isotherm model. The achieved BET surface area of adsorbent with the highest amount of synthesis parameters was 922 (m2/g). The ideal adsorbed solution theory (IAST) was utilized to anticipate CO2/N2 and CO2/H2 selectivity at 298 k and 1 bar. CO2/N2 and CO2/H2 selectivity for adsorbent with the maximum amount of synthesis parameters were 8.4 and 4.4, respectively. The high selectivity values of carbazole-based HCPs are due to the presence of nitrogen atoms in the adsorbent structure and a more robust interaction between CO2 molecules and the adsorbent surface.
https://jchpe.ut.ac.ir/article_79119_1c24dece6e5568ec04a8e2a4e31a12a5.pdf
2020-12-01
311
321
10.22059/jchpe.2020.303331.1315
Adsorption
CO2/H2
CO2 /N2
Hypercrosslinked polymer
Selectivity
Pegah
Najafi
pegah.najafi91@yahoo.com
1
Iran University of Science and Technology
AUTHOR
Hamid
Ramezanipour Penchah
hamidrpp@gmail.com
2
Guilan University
AUTHOR
َAhad
Ghaemi
aghaemi@iust.ac.ir
3
Iran University of Science and Technology, Teharn, Iran
LEAD_AUTHOR
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1
[2] Y. Luo, B. Li, W. Wang, K. Wu, and B. Tan, "Hypercrosslinked Aromatic Heterocyclic Microporous Polymers: A New Class of Highly Selective CO2 Capturing Materials," Advanced Materials, vol. 24, no. 42, pp. 5703-5707, 2012/11/08 2012.
2
[3] H. Ramezanipour Penchah, H. Ghanadzadeh Gilani, and A. Ghaemi, "CO2, N2, and H2 Adsorption by Hyper-Cross-Linked Polymers and Their Selectivity Evaluation by Gas–Solid Equilibrium," Journal of Chemical & Engineering Data, vol. 65, no. 10, pp. 4905-4913, 2020/10/08 2020.
3
[4] F. Mirzaei and A. Ghaemi, "Mass Transfer Modeling of CO2 Absorption into Blended Aqueous MDEA–PZ Solution," (in en), Iranian Journal of Oil and Gas Science and Technology, vol. 9, no. 3, pp. 77-101, 2020.
4
[5] A. Ghaemi, "Mass Transfer Modeling of CO2 Absorption into Blended MDEA-MEA Solution," (in en), Journal of Chemical and Petroleum Engineering, vol. 54, no. 1, pp. 111-128, 2020.
5
[6] M. Khajeh and A. Ghaemi, "Exploiting response surface methodology for experimental modeling and optimization of CO2 adsorption onto NaOH-modified nanoclay montmorillonite," Journal of Environmental Chemical Engineering, vol. 8, no. 2, p. 103663, 2020/04/01/ 2020.
6
[7] C. Song, X. Xu, J. M. Andresen, B. G. Miller, and A. W. Scaroni, "Novel nanoporous" molecular basket" adsorbent for CO2 capture," Stud Surf Sci Catal, vol. 153, pp. 411-416, 2004.
7
[8] H. Pashaei, M. N. Zarandi, and A. Ghaemi, "Experimental study and modeling of CO2 absorption into diethanolamine solutions using stirrer bubble column," Chemical Engineering Research and Design, vol. 121, pp. 32-43, 2017/05/01/ 2017.
8
[9] L. Shao, S. Wang, M. Liu, J. Huang, and Y.-N. Liu, "Triazine-based hyper-cross-linked polymers derived porous carbons for CO2 capture," Chemical Engineering Journal, vol. 339, pp. 509-518, 2018/05/01/ 2018.
9
[10] R. Dawson, A. I. Cooper, and D. J. Adams, "Chemical functionalization strategies for carbon dioxide capture in microporous organic polymers," Polymer International, vol. 62, no. 3, pp. 345-352, 2013/03/01 2013.
10
[11] Z. Liang, M. Marshall, and A. L. Chaffee, "CO2 adsorption, selectivity and water tolerance of pillared-layer metal organic frameworks," Microporous and Mesoporous Materials, vol. 132, no. 3, pp. 305-310, 2010/08/01/ 2010.
11
[12] H. Pashaei and A. Ghaemi, "CO2 absorption into aqueous diethanolamine solution with nano heavy metal oxide particles using stirrer bubble column: Hydrodynamics and mass transfer," Journal of Environmental Chemical Engineering, vol. 8, no. 5, p. 104110, 2020/10/01/ 2020.
12
[13] A. H. Behroozi, N. Akbarzad, and A. Ghaemi, "CO2 Reactive Absorption into an Aqueous Blended MDEA and TMS Solution: Experimental and Modeling," International Journal of Environmental Research, vol. 14, no. 3, pp. 347-363, 2020/06/01 2020.
13
[14] N. Karbalaei Mohammad, A. Ghaemi, K. Tahvildari, and A. A. M. Sharif, "Experimental Investigation and Modeling of CO2 Adsorption Using Modified Activated Carbon," (in en), Iranian Journal of Chemistry and Chemical Engineering (IJCCE), vol. 39, no. 1, pp. 177-192, 2020.
14
[15] M. Khajeh Amiri, A. Ghaemi, and H. Arjomandi, "Experimental, Kinetics and Isotherm Modeling of Carbon Dioxide Adsorption with 13X Zeolite in a fixed bed column," (in en), Iranian Journal of Chemical Engineering(IJChE), vol. 16, no. 1, pp. 54-64, 2019.
15
[16] R. Dawson, T. Ratvijitvech, M. Corker, A. Laybourn, Y. Z. Khimyak, A. I. Cooper, and D. J. Adams, "Microporous copolymers for increased gas selectivity," Polymer Chemistry, 10.1039/C2PY20136D vol. 3, no. 8, pp. 2034-2038, 2012.
16
[17] C. F. Martín, E. Stöckel, R. Clowes, D. J. Adams, A. I. Cooper, J. J. Pis, F. Rubiera, and C. Pevida, "Hypercrosslinked organic polymer networks as potential adsorbents for pre-combustion CO2 capture," Journal of Materials Chemistry, 10.1039/C0JM03534C vol. 21, no. 14, pp. 5475-5483, 2011.
17
[18] H. Ramezanipour Penchah, A. Ghaemi, and H. Ganadzadeh Gilani, "Benzene-Based Hyper-Cross-Linked Polymer with Enhanced Adsorption Capacity for CO2 Capture," Energy & Fuels, vol. 33, no. 12, pp. 12578-12586, 2019/12/19 2019.
18
[19] M. Saleh, H. M. Lee, K. C. Kemp, and K. S. Kim, "Highly Stable CO2/N2 and CO2/CH4 Selectivity in Hyper-Cross-Linked Heterocyclic Porous Polymers," ACS Applied Materials & Interfaces, vol. 6, no. 10, pp. 7325-7333, 2014/05/28 2014.
19
[20] R. Babarao, S. Dai, and D.-e. Jiang, "Functionalizing Porous Aromatic Frameworks with Polar Organic Groups for High-Capacity and Selective CO2 Separation: A Molecular Simulation Study," Langmuir, vol. 27, no. 7, pp. 3451-3460, 2011/04/05 2011.
20
[21] F. S. Taheri, A. Ghaemi, A. Maleki, and S. Shahhosseini, "High CO2 Adsorption on Amine-Functionalized Improved Mesoporous Silica Nanotube as an Eco-Friendly Nanocomposite," Energy & Fuels, vol. 33, no. 6, pp. 5384-5397, 2019/06/20 2019.
21
[22] S. Kazemi, A. Ghaemi, and K. Tahvildari, "Chemical absorption of carbon dioxide into aqueous piperazine solutions using a stirred reactor," (in en), Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 2019.
22
[23] A. Ghaemi, Z. Jafari, and E. Etemad, "Prediction of CO2 mass transfer flux in aqueous amine solutions using artificial neural networks," (in en), Iranian Journal of Chemistry and Chemical Engineering (IJCCE), 2018.
23
[24] R. Bera, M. Ansari, A. Alam, and N. Das, "Triptycene, Phenolic-OH, and Azo-Functionalized Porous Organic Polymers: Efficient and Selective CO2 Capture," ACS Applied Polymer Materials, vol. 1, no. 5, pp. 959-968, 2019/05/10 2019.
24
[25] B. Li, R. Gong, W. Wang, X. Huang, W. Zhang, H. Li, C. Hu, and B. Tan, "A New Strategy to Microporous Polymers: Knitting Rigid Aromatic Building Blocks by External Cross-Linker," Macromolecules, vol. 44, no. 8, pp. 2410-2414, 2011/04/26 2011.
25
[26] B. Li, R. Gong, W. Wang, X. Huang, W. Zhang, H. Li, C. Hu, and B. J. M. Tan, "A new strategy to microporous polymers: knitting rigid aromatic building blocks by external cross-linker," vol. 44, no. 8, pp. 2410-2414, 2011.
26
[27] G. Santori, M. Luberti, and H. Ahn, "Ideal adsorbed solution theory solved with direct search minimisation," Computers & Chemical Engineering, vol. 71, pp. 235-240, 2014/12/04/ 2014.
27
ORIGINAL_ARTICLE
Sensitivity Analysis and Prediction of Gas Reservoirs Performance Supported by an Aquifer Based using Box-Behnken Design and Simulation Studies
Prediction of gas reservoir performance in some industrial cases requires costly and time-consuming simulation runs and a strong CPU must be involved in the simulation procedure. Many reservoir parameters conform to a strong aquifer behavior on gas reservoir performance. Effects of parameters, including reservoir permeability, aquifer permeability, initial reservoir pressure, brine water salinity, gas zone thickness, water zone thickness, temperature, tubing diameter, reservoir inclination, the effective intruding angle of the aquifer, and porosity were investigated using Tornado chart, and seven parameters were filtered. Response functions of aquifer productivity index, gas recovery factor, initial maximum gas production, water sweep efficiency, gas production rate, water breakthrough time, and water production were defined statistically, using Eclipse E100 and Box-Behnken design (BBD). According to the formulae generated by the BBD based on simulation runs, reservoir permeability, aquifer permeability, well-head pressure, and gas zone thickness are the most influencing parameters on the gas reservoir performance supported by the strong aquifer. The aquifer was found to be important especially due to its productivity index and sweep water efficiency. Validation of results given by the BBD through simulation runs showed response functions of aquifer productivity index, sweep water efficiency, maximum gas production, and recovery factor are of deviation percentages in the ranges of 10.61%, 6.302%, 3.958%, and 2.04%, respectively.
https://jchpe.ut.ac.ir/article_77555_4b9bf7728df699421d7b03c6de1ac082.pdf
2020-12-01
323
339
10.22059/jchpe.2020.303778.1318
Aquifer
Box-Behnken
gas reservoir
Gas Production Permeability
Amir Hossein
Saeedi Dehaghani
asaeedi@modares.ac.ir
1
Petroleum Engineering Department, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran
LEAD_AUTHOR
Saeed
Karami
saeed.karami@modares.ac.ir
2
Petroleum Engineering Department, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran
AUTHOR
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[12] Wang, J., et al. The Prediction Methods of the Water Influx Intensity of the Non-homogeneous Aquifer Gas Reservoir. in Fourth International Conference on Computational and Information Sciences (ICCIS). 2012.
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[13] Tran, T.V., et al., A case study of gas-condensate reservoir performance under bottom water drive mechanism. Journal of Petroleum Exploration Production Technology, 2018: p. 1-17.
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[20] Long, L.C. Experimental research on gas saturation behind the water front in gas reservoirs subjected to water drive. in 6th World Petroleum Congress. 1963.
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[21] Myers, R.H., D.C. Montgomery, and C.M. Anderson-Cook, Response surface methodology: process and product optimization using designed experiments. 2016: John Wiley & Sons.
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