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Volumn 52, Issue 44, 2013, Pages 15664-15672

Robust model for the determination of wax deposition in oil systems

Author keywords

[No Author keywords available]

Indexed keywords

ACCURATE PREDICTION; LEAST-SQUARES SUPPORT VECTOR MACHINES; OIL/GAS PRODUCTION; OPTIMIZATION APPROACH; PREDICTIVE MODELING; RELIABLE MODELS; SOFT COMPUTING APPROACHES; SOLID DEPOSITION;

EID: 84887593328     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie402462q     Document Type: Conference Paper
Times cited : (66)

References (56)
  • 1
    • 34147151615 scopus 로고    scopus 로고
    • A thermodynamic model for wax deposition phenomena
    • Dalirsefat, R.; Feyzi, F. A thermodynamic model for wax deposition phenomena Fuel 2007, 86 (10) 1402-1408
    • (2007) Fuel , vol.86 , Issue.10 , pp. 1402-1408
    • Dalirsefat, R.1    Feyzi, F.2
  • 2
    • 0035861345 scopus 로고    scopus 로고
    • An improved thermodynamic model for wax precipitation from petroleum fluids
    • Zuo, J. Y.; Zhang, D. D.; Ng, H.-J. An improved thermodynamic model for wax precipitation from petroleum fluids Chem. Eng. Sci. 2001, 56 (24) 6941-6947
    • (2001) Chem. Eng. Sci. , vol.56 , Issue.24 , pp. 6941-6947
    • Zuo, J.Y.1    Zhang, D.D.2    Ng, H.-J.3
  • 3
    • 84861559623 scopus 로고    scopus 로고
    • The Prediction of Wax Precipitation by Neural Network and Genetic Algorithm and Comparison with a Multisolid Model in Crude Oil Systems
    • Khaksar Manshad, A.; Ashoori, S.; Khaksar Manshad, M.; Omidvar, P. The Prediction of Wax Precipitation by Neural Network and Genetic Algorithm and Comparison With a Multisolid Model in Crude Oil Systems Pet. Sci. Technol. 2012, 30 (13) 1369-1378
    • (2012) Pet. Sci. Technol. , vol.30 , Issue.13 , pp. 1369-1378
    • Khaksar Manshad, A.1    Ashoori, S.2    Khaksar Manshad, M.3    Omidvar, P.4
  • 4
    • 0019380972 scopus 로고
    • Studies of wax deposition in the trans Alaska pipeline
    • Burger, E.; Perkins, T.; Striegler, J. Studies of wax deposition in the trans Alaska pipeline J. Pet. Technol. 1981, 33 (6) 1075-1086
    • (1981) J. Pet. Technol. , vol.33 , Issue.6 , pp. 1075-1086
    • Burger, E.1    Perkins, T.2    Striegler, J.3
  • 5
    • 0029657413 scopus 로고    scopus 로고
    • Thermodynamics of wax precipitation in petroleum mixtures
    • Lira-Galeana, C.; Firoozabadi, A.; Prausnitz, J. M. Thermodynamics of wax precipitation in petroleum mixtures AIChE J. 1996, 42 (1) 239-248
    • (1996) AIChE J. , vol.42 , Issue.1 , pp. 239-248
    • Lira-Galeana, C.1    Firoozabadi, A.2    Prausnitz, J.M.3
  • 6
    • 84875512004 scopus 로고    scopus 로고
    • An experimental design approach for investigating the effects of operating factors on the wax deposition in pipelines
    • Valinejad, R.; Solaimany Nazar, A. R. An experimental design approach for investigating the effects of operating factors on the wax deposition in pipelines Fuel 2013, 106, 843-850
    • (2013) Fuel , vol.106 , pp. 843-850
    • Valinejad, R.1    Solaimany Nazar, A.R.2
  • 7
    • 39449124326 scopus 로고    scopus 로고
    • Introduction to a novel approach for modeling wax deposition in fluid flows. 1. Taylor-Couette system
    • Akbarzadeh, K.; Zougari, M. Introduction to a novel approach for modeling wax deposition in fluid flows. 1. Taylor-Couette system Ind. Eng. Chem. Res. 2008, 47 (3) 953-963
    • (2008) Ind. Eng. Chem. Res. , vol.47 , Issue.3 , pp. 953-963
    • Akbarzadeh, K.1    Zougari, M.2
  • 8
    • 84874066869 scopus 로고    scopus 로고
    • Effect of Carbon Number Distribution of Wax on the Yield Stress of Waxy Oil Gels
    • Bai, C.; Zhang, J. Effect of Carbon Number Distribution of Wax on the Yield Stress of Waxy Oil Gels Ind. Eng. Chem. Res. 2013, 52 (7) 2732-2739
    • (2013) Ind. Eng. Chem. Res. , vol.52 , Issue.7 , pp. 2732-2739
    • Bai, C.1    Zhang, J.2
  • 9
    • 84884157137 scopus 로고    scopus 로고
    • Prediction of Wax Deposition Problems of Hydrocarbon Production System
    • Kelechukwu, E. M.; Al-Salim, H. S.; Saadi, A. Prediction of Wax Deposition Problems of Hydrocarbon Production System J. Pet. Sci. Eng. 2013, 108, 128-136
    • (2013) J. Pet. Sci. Eng. , vol.108 , pp. 128-136
    • Kelechukwu, E.M.1    Al-Salim, H.S.2    Saadi, A.3
  • 10
    • 0023960944 scopus 로고
    • Methods for predicting wax precipitation and deposition
    • Weingarten, J.; Euchner, J. Methods for predicting wax precipitation and deposition SPE Prod. Eng. 1988, 3 (1) 121-126
    • (1988) SPE Prod. Eng. , vol.3 , Issue.1 , pp. 121-126
    • Weingarten, J.1    Euchner, J.2
  • 11
    • 77955173749 scopus 로고    scopus 로고
    • A support vector machine algorithm to classify lithofacies and model permeability in heterogeneous reservoirs
    • Al-Anazi, A.; Gates, I. A support vector machine algorithm to classify lithofacies and model permeability in heterogeneous reservoirs Eng. Geol. 2010, 114 (3) 267-277
    • (2010) Eng. Geol. , vol.114 , Issue.3 , pp. 267-277
    • Al-Anazi, A.1    Gates, I.2
  • 12
    • 54049139304 scopus 로고    scopus 로고
    • A new neural network-group contribution method for estimation of flash point temperature of pure components
    • Gharagheizi, F.; Alamdari, R. F.; Angaji, M. T. A new neural network-group contribution method for estimation of flash point temperature of pure components Energy Fuels 2008, 22 (3) 1628-1635
    • (2008) Energy Fuels , vol.22 , Issue.3 , pp. 1628-1635
    • Gharagheizi, F.1    Alamdari, R.F.2    Angaji, M.T.3
  • 13
    • 80052770488 scopus 로고    scopus 로고
    • Permeability prediction based on reservoir zonation by a hybrid neural genetic algorithm in one of the Iranian heterogeneous oil reservoirs
    • Kaydani, H.; Mohebbi, A.; Baghaie, A. Permeability prediction based on reservoir zonation by a hybrid neural genetic algorithm in one of the Iranian heterogeneous oil reservoirs J. Pet. Sci. Eng. 2011, 78 (2) 497-504
    • (2011) J. Pet. Sci. Eng. , vol.78 , Issue.2 , pp. 497-504
    • Kaydani, H.1    Mohebbi, A.2    Baghaie, A.3
  • 14
    • 84855555199 scopus 로고    scopus 로고
    • Support vector regression to predict porosity and permeability: Effect of sample size
    • Al-Anazi, A.; Gates, I. Support vector regression to predict porosity and permeability: Effect of sample size Comput. Geosci. 2012, 39, 64-76
    • (2012) Comput. Geosci. , vol.39 , pp. 64-76
    • Al-Anazi, A.1    Gates, I.2
  • 15
    • 0004831593 scopus 로고
    • Design and development of an artificial neural network for estimation of formation permeability
    • Mohaghegh, S.; Arefi, R.; Ameri, S.; Rose, D. Design and development of an artificial neural network for estimation of formation permeability SPE Comput. Appl. 1995, 7 (6) 151-154
    • (1995) SPE Comput. Appl. , vol.7 , Issue.6 , pp. 151-154
    • Mohaghegh, S.1    Arefi, R.2    Ameri, S.3    Rose, D.4
  • 16
    • 29544449323 scopus 로고    scopus 로고
    • Reservoir properties determination using fuzzy logic and neural networks from well data in offshore Korea
    • Lim, J.-S. Reservoir properties determination using fuzzy logic and neural networks from well data in offshore Korea J. Pet. Sci. Eng. 2005, 49 (3) 182-192
    • (2005) J. Pet. Sci. Eng. , vol.49 , Issue.3 , pp. 182-192
    • Lim, J.-S.1
  • 17
    • 0032638628 scopus 로고    scopus 로고
    • Least squares support vector machine classifiers
    • Suykens, J. A.; Vandewalle, J. Least squares support vector machine classifiers Neural Process. Lett 1999, 9 (3) 293-300
    • (1999) Neural Process. Lett , vol.9 , Issue.3 , pp. 293-300
    • Suykens, J.A.1    Vandewalle, J.2
  • 23
    • 0026256221 scopus 로고
    • Wax precipitation from North Sea crude oils. 2. Solid-phase content as function of temperature determined by pulsed NMR
    • Batsberg Pedersen, W.; Baltzer Hansen, A.; Larsen, E.; Nielsen, A. B.; Roenningsen, H. P. Wax precipitation from North Sea crude oils. 2. Solid-phase content as function of temperature determined by pulsed NMR Energy Fuels 1991, 5 (6) 908-913
    • (1991) Energy Fuels , vol.5 , Issue.6 , pp. 908-913
    • Batsberg Pedersen, W.1    Baltzer Hansen, A.2    Larsen, E.3    Nielsen, A.B.4    Roenningsen, H.P.5
  • 24
    • 0026258603 scopus 로고
    • Wax precipitation from North Sea crude oils. 4. Thermodynamic modeling
    • Schou Pedersen, K.; Skovborg, P.; Roenningsen, H. P. Wax precipitation from North Sea crude oils. 4. Thermodynamic modeling Energy Fuels 1991, 5 (6) 924-932
    • (1991) Energy Fuels , vol.5 , Issue.6 , pp. 924-932
    • Schou Pedersen, K.1    Skovborg, P.2    Roenningsen, H.P.3
  • 25
    • 0026256287 scopus 로고
    • Wax precipitation from North Sea crude oils. 3. Precipitation and dissolution of wax studied by differential scanning calorimetry
    • Baltzer Hansen, A.; Larsen, E.; Batsberg Pedersen, W.; Nielsen, A. B.; Roenningsen, H. P. Wax precipitation from North Sea crude oils. 3. Precipitation and dissolution of wax studied by differential scanning calorimetry Energy Fuels 1991, 5 (6) 914-923
    • (1991) Energy Fuels , vol.5 , Issue.6 , pp. 914-923
    • Baltzer Hansen, A.1    Larsen, E.2    Batsberg Pedersen, W.3    Nielsen, A.B.4    Roenningsen, H.P.5
  • 27
    • 33748191245 scopus 로고    scopus 로고
    • Enhancement of the extended corresponding states techniques for thermodynamic modeling. II. Mixtures
    • Scalabrin, G.; Marchi, P.; Bettio, L.; Richon, D. Enhancement of the extended corresponding states techniques for thermodynamic modeling. II. Mixtures Int. J. Refrig. 2006, 29 (7) 1195-1207
    • (2006) Int. J. Refrig. , vol.29 , Issue.7 , pp. 1195-1207
    • Scalabrin, G.1    Marchi, P.2    Bettio, L.3    Richon, D.4
  • 28
    • 49249083725 scopus 로고    scopus 로고
    • A mathematical model based on artificial neural network technique for estimating liquid water-hydrate equilibrium of water-hydrocarbon system
    • Mohammadi, A. H.; Richon, D. A mathematical model based on artificial neural network technique for estimating liquid water-hydrate equilibrium of water-hydrocarbon system Ind. Eng. Chem. Res. 2008, 47 (14) 4966-4970
    • (2008) Ind. Eng. Chem. Res. , vol.47 , Issue.14 , pp. 4966-4970
    • Mohammadi, A.H.1    Richon, D.2
  • 29
    • 67649216406 scopus 로고    scopus 로고
    • Prediction of the standard enthalpy of formation of pure compounds using molecular structure
    • Gharagheizi, F. Prediction of the standard enthalpy of formation of pure compounds using molecular structure Aust. J. Chem. 2009, 62 (4) 376-381
    • (2009) Aust. J. Chem. , vol.62 , Issue.4 , pp. 376-381
    • Gharagheizi, F.1
  • 30
    • 41949085376 scopus 로고    scopus 로고
    • A new method for the determination of wax precipitation from non-diluted crude oils by fractional precipitation
    • Coto, B.; Martos, C.; Peña, J. L.; Espada, J. J.; Robustillo, M. D. A new method for the determination of wax precipitation from non-diluted crude oils by fractional precipitation Fuel 2008, 87 (10) 2090-2094
    • (2008) Fuel , vol.87 , Issue.10 , pp. 2090-2094
    • Coto, B.1    Martos, C.2    Peña, J.L.3    Espada, J.J.4    Robustillo, M.D.5
  • 31
    • 80052367812 scopus 로고    scopus 로고
    • Solubility parameters of nonelectrolyte organic compounds: Determination using quantitative structure-property relationship strategy
    • Gharagheizi, F.; Eslamimanesh, A.; Farjood, F.; Mohammadi, A. H.; Richon, D. Solubility parameters of nonelectrolyte organic compounds: Determination using quantitative structure-property relationship strategy Ind. Eng. Chem. Res. 2011, 50 (19) 11382-11395
    • (2011) Ind. Eng. Chem. Res. , vol.50 , Issue.19 , pp. 11382-11395
    • Gharagheizi, F.1    Eslamimanesh, A.2    Farjood, F.3    Mohammadi, A.H.4    Richon, D.5
  • 32
    • 37349044609 scopus 로고    scopus 로고
    • Predicting the hydrate stability zones of natural gases using artificial neural networks
    • Chapoy, A.; Mohammadi, A.-H.; Richon, D. Predicting the hydrate stability zones of natural gases using artificial neural networks Oil Gas Sci. Technol. 2007, 62 (5) 701-706
    • (2007) Oil Gas Sci. Technol. , vol.62 , Issue.5 , pp. 701-706
    • Chapoy, A.1    Mohammadi, A.-H.2    Richon, D.3
  • 33
    • 84855174209 scopus 로고    scopus 로고
    • Phase equilibrium modeling of clathrate hydrates of methane, carbon dioxide, nitrogen, and hydrogen + water soluble organic promoters using Support Vector Machine algorithm
    • Eslamimanesh, A.; Gharagheizi, F.; Illbeigi, M.; Mohammadi, A. H.; Fazlali, A.; Richon, D. Phase equilibrium modeling of clathrate hydrates of methane, carbon dioxide, nitrogen, and hydrogen + water soluble organic promoters using Support Vector Machine algorithm Fluid Phase Equilib. 2012, 316, 34-45
    • (2012) Fluid Phase Equilib. , vol.316 , pp. 34-45
    • Eslamimanesh, A.1    Gharagheizi, F.2    Illbeigi, M.3    Mohammadi, A.H.4    Fazlali, A.5    Richon, D.6
  • 34
    • 34248389661 scopus 로고    scopus 로고
    • QSPR analysis for intrinsic viscosity of polymer solutions by means of GA-MLR and RBFNN
    • Gharagheizi, F. QSPR analysis for intrinsic viscosity of polymer solutions by means of GA-MLR and RBFNN Comput. Mater. Sci. 2007, 40 (1) 159-167
    • (2007) Comput. Mater. Sci. , vol.40 , Issue.1 , pp. 159-167
    • Gharagheizi, F.1
  • 38
    • 84862082216 scopus 로고    scopus 로고
    • Application of Artificial Neural Network and Wavelet Transform for Vibration Analysis of Combined Faults of Unbalances and Shaft Bow
    • Srinivas, H.; Srinivasan, K.; Umesh, K. Application of Artificial Neural Network and Wavelet Transform for Vibration Analysis of Combined Faults of Unbalances and Shaft Bow Adv. Theor. Appl. Mech. 2010, 3 (4) 159-176
    • (2010) Adv. Theor. Appl. Mech. , vol.3 , Issue.4 , pp. 159-176
    • Srinivas, H.1    Srinivasan, K.2    Umesh, K.3
  • 40
    • 80054712747 scopus 로고    scopus 로고
    • Phase equilibrium modeling of structure H clathrate hydrates of methane + water "insoluble" hydrocarbon promoter using QSPR molecular approach
    • Eslamimanesh, A.; Gharagheizi, F.; Mohammadi, A. H.; Richon, D. Phase equilibrium modeling of structure H clathrate hydrates of methane + water "insoluble" hydrocarbon promoter using QSPR molecular approach J. Chem. Eng. Data 2011, 56 (10) 3775-3793
    • (2011) J. Chem. Eng. Data , vol.56 , Issue.10 , pp. 3775-3793
    • Eslamimanesh, A.1    Gharagheizi, F.2    Mohammadi, A.H.3    Richon, D.4
  • 41
    • 0027624291 scopus 로고
    • Reliability optimization of communication networks using simulated annealing
    • Atiqullah, M. M.; Rao, S. Reliability optimization of communication networks using simulated annealing Microelectron. Reliab. 1993, 33 (9) 1303-1319
    • (1993) Microelectron. Reliab. , vol.33 , Issue.9 , pp. 1303-1319
    • Atiqullah, M.M.1    Rao, S.2
  • 42
    • 0030735069 scopus 로고    scopus 로고
    • Simulated annealing simulated
    • Fabian, V. Simulated annealing simulated Comput. Math. Appl. 1997, 33 (1) 81-94
    • (1997) Comput. Math. Appl. , vol.33 , Issue.1 , pp. 81-94
    • Fabian, V.1
  • 43
    • 53749107279 scopus 로고    scopus 로고
    • Comparative analysis of simulated annealing, simulated quenching and genetic algorithms for optimal reservoir operation
    • Vasan, A.; Raju, K. S. Comparative analysis of simulated annealing, simulated quenching and genetic algorithms for optimal reservoir operation Appl. Soft Comput. 2009, 9 (1) 274-281
    • (2009) Appl. Soft Comput. , vol.9 , Issue.1 , pp. 274-281
    • Vasan, A.1    Raju, K.S.2
  • 44
    • 0035537546 scopus 로고    scopus 로고
    • Intelligence and cooperative search by coupled local minimizers
    • Suykens, J. A.; Vandewalle, J.; De Moor, B. Intelligence and cooperative search by coupled local minimizers Int. J. Bifurcation Chaos 2001, 11 (08) 2133-2144
    • (2001) Int. J. Bifurcation Chaos , vol.11 , Issue.8 , pp. 2133-2144
    • Suykens, J.A.1    Vandewalle, J.2    De Moor, B.3
  • 46
    • 43149111187 scopus 로고    scopus 로고
    • Discovering multi-core: Extending the benefits of Moore's law
    • Koch, G., Discovering multi-core: Extending the benefits of Moore's law. Technology 2005, 1.
    • (2005) Technology , vol.1
    • Koch, G.1
  • 48
    • 0011890371 scopus 로고
    • Computation Using the QR decomposition
    • Goodall, C. R. Computation Using the QR decomposition Handb. Stat. 1993, 9, 467-508
    • (1993) Handb. Stat. , vol.9 , pp. 467-508
    • Goodall, C.R.1
  • 49
    • 34250628103 scopus 로고    scopus 로고
    • Principles of QSAR models validation: Internal and external
    • Gramatica, P. Principles of QSAR models validation: Internal and external QSAR Comb. Sci. 2007, 26 (5) 694-701
    • (2007) QSAR Comb. Sci. , vol.26 , Issue.5 , pp. 694-701
    • Gramatica, P.1
  • 50
    • 84864305292 scopus 로고    scopus 로고
    • A statistical method for evaluation of the experimental phase equilibrium data of simple clathrate hydrates
    • Eslamimanesh, A.; Gharagheizi, F.; Mohammadi, A. H.; Richon, D. A statistical method for evaluation of the experimental phase equilibrium data of simple clathrate hydrates Chem. Eng. Sci. 2012, 80, 402-408
    • (2012) Chem. Eng. Sci. , vol.80 , pp. 402-408
    • Eslamimanesh, A.1    Gharagheizi, F.2    Mohammadi, A.H.3    Richon, D.4
  • 51
    • 84861970125 scopus 로고    scopus 로고
    • A novel method for evaluation of asphaltene precipitation titration data
    • Mohammadi, A. H.; Eslamimanesh, A.; Gharagheizi, F.; Richon, D. A novel method for evaluation of asphaltene precipitation titration data Chem. Eng. Sci. 2012, 78, 181-185
    • (2012) Chem. Eng. Sci. , vol.78 , pp. 181-185
    • Mohammadi, A.H.1    Eslamimanesh, A.2    Gharagheizi, F.3    Richon, D.4
  • 52
    • 84860473131 scopus 로고    scopus 로고
    • Evaluation of thermal conductivity of gases at atmospheric pressure through a corresponding states method
    • Gharagheizi, F.; Eslamimanesh, A.; Sattari, M.; Tirandazi, B.; Mohammadi, A. H.; Richon, D. Evaluation of thermal conductivity of gases at atmospheric pressure through a corresponding states method Ind. Eng. Chem. Res. 2012, 51 (9) 3844-3849
    • (2012) Ind. Eng. Chem. Res. , vol.51 , Issue.9 , pp. 3844-3849
    • Gharagheizi, F.1    Eslamimanesh, A.2    Sattari, M.3    Tirandazi, B.4    Mohammadi, A.H.5    Richon, D.6
  • 53
    • 84864037297 scopus 로고    scopus 로고
    • Evaluation of experimental data for wax and diamondoids solubility in gaseous systems
    • Mohammadi, A. H.; Gharagheizi, F.; Eslamimanesh, A.; Richon, D. Evaluation of experimental data for wax and diamondoids solubility in gaseous systems Chem. Eng. Sci. 2012, 81, 1-7
    • (2012) Chem. Eng. Sci. , vol.81 , pp. 1-7
    • Mohammadi, A.H.1    Gharagheizi, F.2    Eslamimanesh, A.3    Richon, D.4
  • 54
    • 77953232183 scopus 로고    scopus 로고
    • Use of an artificial neural network algorithm to predict hydrate dissociation conditions for hydrogen + water and hydrogen + tetra- n -butyl ammonium bromide + water systems
    • Mohammadi, A. H.; Belandria, V.; Richon, D. Use of an artificial neural network algorithm to predict hydrate dissociation conditions for hydrogen + water and hydrogen + tetra- n -butyl ammonium bromide + water systems Chem. Eng. Sci. 2010, 65 (14) 4302-4305
    • (2010) Chem. Eng. Sci. , vol.65 , Issue.14 , pp. 4302-4305
    • Mohammadi, A.H.1    Belandria, V.2    Richon, D.3
  • 55
    • 77950627492 scopus 로고    scopus 로고
    • Hydrate phase equilibria for hydrogen + water and hydrogen + tetrahydrofuran + water systems: Predictions of dissociation conditions using an artificial neural network algorithm
    • Mohammadi, A. H.; Richon, D. Hydrate phase equilibria for hydrogen + water and hydrogen + tetrahydrofuran + water systems: Predictions of dissociation conditions using an artificial neural network algorithm Chem. Eng. Sci. 2010, 65 (10) 3352-3355
    • (2010) Chem. Eng. Sci. , vol.65 , Issue.10 , pp. 3352-3355
    • Mohammadi, A.H.1    Richon, D.2
  • 56
    • 79955637341 scopus 로고    scopus 로고
    • Artificial neural network modeling of solubility of supercritical carbon dioxide in 24 commonly used ionic liquids
    • Eslamimanesh, A.; Gharagheizi, F.; Mohammadi, A. H.; Richon, D. Artificial neural network modeling of solubility of supercritical carbon dioxide in 24 commonly used ionic liquids Chem. Eng. Sci. 2011, 66 (13) 3039-3044
    • (2011) Chem. Eng. Sci. , vol.66 , Issue.13 , pp. 3039-3044
    • Eslamimanesh, A.1    Gharagheizi, F.2    Mohammadi, A.H.3    Richon, D.4


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