1. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. © Artificial Neural Network Models For Identifying Flow Regimes And Predicting Liquid Holdup In Horizontal Multiphase Flow Osman, EA SOC PETROLEUM ENG, SPE PRODUCTION FACILITIES; pp: 33-40; Vol: 19 King Fahd University of Petroleum & Minerals http://www.kfupm.edu.sa Summary This paper presents two artificial neural network (ANN) models to identify the flow regime and calculate the liquid holdup in horizontal multiphase flow. These models are developed with 199 experimental data sets and with three-layer back-propagation neural networks (BPNs). Superficial gas and liquid velocities, pressure, temperature, and fluid properties are used as inputs to the model. Data were divided into three portions: training, cross validation, and testing. The results show that the developed models provide better predictions and higher accuracy than the empirical correlations developed specifically for these data groups. The developed flow-regime model predicts correctly for more than 97% of the data points. The liquid-holdup model outperforms the published models; it provides holdup predictions with an average absolute percent error of 9.407, a standard deviation of 8.544, and a correlation coefficient of 0.9896. References: ABDELWAHHAB O, 1997, PATTERN RECOGN, V30, P519 ABDULMAJEED GH, 1993, 26279 SPE ABDULMAJEED GH, 1996, J PETROL SCI ENG, V15, P271 ABDULMAJEED GH, 2000, J PETROL SCI ENG, V27, P27 BAKER A, 1988, OIL GAS J, V11, P55 BAKER O, 1954, OIL GAS J, V53, P185 BEGGS HD, 1973, STUDY 2 PHASE FLOW I, P607 BISHOP C, 1995, NEURAL NETWORKS PATT BRILL JP, AIME, V271 BRILL JP, 1978, 2 PHASE FLOW PIPES Copyright: King Fahd University of Petroleum & Minerals; http://www.kfupm.edu.sa

2. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 31. 32. 33. 34. 35. 36. 37. 39. 40. 41. © 11.BRILL JP, 1981, SPEJJUN, P363 BUTTERWORTH D, 1979, 2 PHASE FLOW HEAT TR CHEREMISINOFF NP, 1979, AICHE J, V25, P48 DUKLER AE, 1975, AICHE J, V17, P337 EATON BA, T AIME, V240 EATON BA, 1967, JPT, P815 FAUSET L, 1996, FUNDAMENTALS NEURAL GOMEZ LE, 1999 SPE ANN TECHN C GREGORY GA, 1978, INT J MULTIPHASE FLO, V4, P33 GUZHOV AI, 1967, P 10 INT GAS C HAMB HORNIK K, 1989, NEURAL NETWORKS, V2, P359 HUGHMARK GA, 1961, AICHE J, V7, P677 HUGHMARK GA, 1962, CHEM ENG PROGR, V58, P62 ISSA RI, 1988, INT J MULTIPHASE FLO, V14, P141 JAMES PW, 1987, INT J MULTIPHAS FLOW, V13, P173 KOKAL SL, 1989, CHEM ENG SCI, V44, P681 LAURINAT JE, 1985, INT J MULTIPHASE FLO, V6, P179 MANDHANE JM, 1986, INT J MULTIPHASE FLO, V12, P711 29. 30. MINAMI K, 1987, SPEPE MOHAGHEGH S, 2000, JPT MUKHERJEE H, T AIME, V275 MUKHERJEE H, 1983, JPT FEB, P36 SEP, P64 MAY, P1003 NICHOLSON MK, 1978, CAN J CHEM ENG, V56, P653 SCOTT DS, 1963, ADV CHEM ENG, V5, P200 SHOHAM O, 1984, AICHE J, V30, P377 TAITEL Y, 1976, AICHE J, V22, P47 TERNYIK J, 1995 E REG M MORG W 38.VANDERSPEK A, 1999, SEPREEDEC, P489 VAROTSIS N, 1999 SPE ANN TECHN C WALLIS GB, 1969, 1 DIMENSIONAL 2 PHAS XIAO JJ, 1990 SPE ANN TECHN E For pre-prints please write to: saosman@kfupm.edu.sa Copyright: King Fahd University of Petroleum & Minerals; http://www.kfupm.edu.sa