메뉴 건너뛰기




Volumn 29, Issue 8, 2011, Pages 804-816

The development of an artificial neural network model for prediction of crude oil viscosities

Author keywords

artificial neural network; correlation; dead; oil viscosity; saturated; undersaturated

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CORRELATION; DEAD; OIL VISCOSITY; SATURATED; UNDERSATURATED;

EID: 79952665748     PISSN: 10916466     EISSN: 15322459     Source Type: Journal    
DOI: 10.1080/10916460903485876     Document Type: Article
Times cited : (36)

References (17)
  • 1
    • 0344592292 scopus 로고
    • High pressure volumetric phase composition and viscosity data for a North Sea crude oil and NGL mixtures
    • Ahrabi, F., Ashcroft, S. J., and Shearn, R. B. (1987). High pressure volumetric phase composition and viscosity data for a North Sea crude oil and NGL mixtures. Chem. Eng. Res. Des. 67:329-334.
    • (1987) Chem. Eng. Res. Des. , vol.67 , pp. 329-334
    • Ahrabi, F.1    Ashcroft, S.J.2    Shearn, R.B.3
  • 2
    • 0008502173 scopus 로고
    • Viscosity of air, water, natural gas, crude oil and its associated gases at oil field temperature and pressures
    • Beal, C. (1946). Viscosity of air, water, natural gas, crude oil and its associated gases at oil field temperature and pressures. Trans. AIME 165:114-127.
    • (1946) Trans. AIME , vol.165 , pp. 114-127
    • Beal, C.1
  • 3
    • 0001757457 scopus 로고
    • Estimating the viscosity of crude oil systems
    • Beggs, H. D., and Robinson, J. R. (1975). Estimating the viscosity of crude oil systems. J. Petrol. Tech. 9:1140-1141.
    • (1975) J. Petrol. Tech. , vol.9 , pp. 1140-1141
    • Beggs, H.D.1    Robinson, J.R.2
  • 4
    • 0001834474 scopus 로고
    • Viscosity correlation for gas saturated crude oil
    • Chew, J., and Connally, C. A. (1959). Viscosity correlation for gas saturated crude oil. Trans. AIME 216:23-25.
    • (1959) Trans. AIME , vol.216 , pp. 23-25
    • Chew, J.1    Connally, C.A.2
  • 5
    • 0032637237 scopus 로고    scopus 로고
    • Models for predicting the viscosity of middle east crude oils
    • Elsharkawy, A. M., and Alikhan, A. A. (1999). Models for predicting the viscosity of Middle East crude oils. Fuel 78:891-903.
    • (1999) Fuel , vol.78 , pp. 891-903
    • Elsharkawy, A.M.1    Alikhan, A.A.2
  • 6
    • 0002292335 scopus 로고
    • Generalized pressure-volume-temperature correlation for crude oil system
    • Glaso, O. (1980). Generalized pressure-volume-temperature correlation for crude oil system. J. Petrol. Tech. 2:785-795.
    • (1980) J. Petrol. Tech. , vol.2 , pp. 785-795
    • Glaso, O.1
  • 8
    • 0028764322 scopus 로고
    • Large data bank improves crude physical property correlation
    • Kartoatmodjo, F., and Schmidt, Z. (1994). Large data bank improves crude physical property correlation. Oil Gas J. 4:51-55.
    • (1994) Oil Gas J. , vol.4 , pp. 51-55
    • Kartoatmodjo, F.1    Schmidt, Z.2
  • 9
    • 0026931398 scopus 로고
    • Improved correlations for predicting the viscosity of light crudes
    • DOI 10.1016/0920-4105(92)90035-Y
    • Labedi, R. (1992). Improved correlations for predicting the viscosity of light crudes. J. Petrol. Sci. Eng. 8:221-234. (Pubitemid 23601717)
    • (1992) Journal of Petroleum Science and Engineering , vol.8 , Issue.3 , pp. 221-234
    • Labedi Rafa1
  • 10
    • 0001999574 scopus 로고
    • Calculating the viscosity of hydrocarbon systems with pressure temperature and composition
    • Little, J. E., and Kennedy, H. T. (1968). Calculating the viscosity of hydrocarbon systems with pressure temperature and composition. Soc. Petrol. Eng. J. 6:157-162.
    • (1968) Soc. Petrol. Eng. J. , vol.6 , pp. 157-162
    • Little, J.E.1    Kennedy, H.T.2
  • 11
    • 0001159205 scopus 로고
    • Calculating viscosities of reservoir fluids from their composition
    • Lohrenz, J., Bray, B. C., and Clark, C. R. (1964). Calculating viscosities of reservoir fluids from their composition. J. Petrol. Tech. 10:1170-1176.
    • (1964) J. Petrol. Tech. , vol.10 , pp. 1170-1176
    • Lohrenz, J.1    Bray, B.C.2    Clark, C.R.3
  • 12
    • 0025490985 scopus 로고
    • Networks for approximation and learning
    • Poggio, T., and Girosi, F. (1990a). Networks for approximation and learning. Proc. IEEE 78:1481-1497.
    • (1990) Proc. IEEE , vol.78 , pp. 1481-1497
    • Poggio, T.1    Girosi, F.2
  • 13
    • 0025056697 scopus 로고
    • Regularisation algorithms for learning that are equivalent to multilayer networks
    • Poggio, T., and Girosi, F. (1990b). Regularisation algorithms for learning that are equivalent to multilayer networks. Science 247:978-982.
    • (1990) Science , vol.247 , pp. 978-982
    • Poggio, T.1    Girosi, F.2
  • 15
    • 0025387722 scopus 로고
    • Evaluation of empirically derived PVT properties for Gulf of Mexico crudes
    • Sutton, R. P., and Farshad, F. F. (1990). Evaluation of empirically derived PVT properties for Gulf of Mexico crudes. SPE Reservoir Eng. 5:79-86.
    • (1990) SPE Reservoir Eng. , vol.5 , pp. 79-86
    • Sutton, R.P.1    Farshad, F.F.2
  • 16
    • 0002083036 scopus 로고
    • Correlations for fluid physical property predictions
    • Vasquez, M. E., and Beggs, H. D. (1980). Correlations for fluid physical property predictions. J. Petrol. Tech. 32:968-970.
    • (1980) J. Petrol. Tech. , vol.32 , pp. 968-970
    • Vasquez, M.E.1    Beggs, H.D.2
  • 17
    • 0030421740 scopus 로고    scopus 로고
    • Designing a soft sensor for a distillation column with the fuzzy distributed radial basis function neural network
    • Wang, X., Luo, R., and Shao, H. (1996). Designing a soft sensor for a distillation column with the fuzzy distributed radial basis function neural network. Decis. Contr. 2:1714-1719.
    • (1996) Decis. Contr. , vol.2 , pp. 1714-1719
    • Wang, X.1    Luo, R.2    Shao, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.