Abstract
Accurate prediction of multiphase flow rate is of prime importance in controlling production of oil fields. Direct measurements using multiphase meters are time-consuming and very costly. On the other hand, none of the published models can be considered as a universal model and most of these models are designated only for the critical flow. The aim of this study is to develop and validate practical models for the Algerian Hassi Messaoud (HMD) oil field covering both critical and subcritical multiphase flows through chokes of naturally flowing and gas lift wells. The new choke models are developed on the basis of the Gilbert model by incorporating the downstream pressure of the choke under the subcritical conditions. A large data set is used to evaluate the new models and to compare their performance with previously published prediction models. These data are divided, for each flow regime, into five selected categories based on the gas–oil ratio and a nonlinear regression algorithm is implemented to validate the new models. The comparison revealed the accuracy of two new models that improved the predicted production rates of the current model of HMD field in 130 wells out of 174 and the sum of absolute differences between the measured and the predicted oil flow rates (SAD) was reduced by 16.68% on 6,786 measurements. For the wells that are assisted with gas lift, the predictability was improved considerably: There was improvement in 85 wells out of 93 and the SAD was reduced by 42.11% on 2,317 measurements.
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Abbreviations
- Q :
-
Gross liquid rate (bbl/day [m\(^3\)/h])
- \(Q_\mathrm{o}\) :
-
Oil flow rate (bbl/day [m\(^3\)/h])
- \(P_\mathrm{u}\) :
-
Wellhead (or upstream) pressure (psig [bar])
- \(P_\mathrm{d}\) :
-
Flowline (or downstream) pressure (psig [bar])
- \(\phi \) :
-
Choke size (1/64 inch [m])
- GLR:
-
Gas–liquid ratio (MSCF/BBL)
- GOR:
-
Gas–oil ratio (MSCF/BBL \([\mathrm{sm}^3/\mathrm{m}^3]\))
- \(\varDelta P\) :
-
Pressure drop across the choke (psig [bar])
- \(Q_\mathrm{e}\) :
-
Estimated oil flow rate (bbl/day [m\(^3\)/h])
- \(Q_\mathrm{m}\) :
-
Measured oil flow rate (bbl/day [m\(^3\)/h])
- SAD:
-
Sum of absolute differences (bbl/day [m\(^3\)/h])
- SD:
-
Sum of differences (bbl/day [m\(^3\)/h])
- RAE:
-
Relative absolute error
- RE:
-
Relative error
- \(W_i\) :
-
Well i
- Nb data:
-
Number of measurements
- a, b, c and d :
-
Empirical constants
References
Guo, B.; Lyons, W.C.; Ghalambor, A.: Petroleum Production Engineering: A Computer-Assisted Approach. Gulf Professional Publishing, Burlington (2007)
Sachdeva, R.; Schmidt, Z.; Brill, J.P.; Blais, R.M.: Two-phase flow through chokes. In: The SPE Annual Technical Conference and Exhibition, New Orleans, 5–8 October (1986)
Seidi, S.; Sayahi, T.: A new correlation for prediction of sub-critical two-phase flow pressure drop through large-sized wellhead chokes. J. Nat. Gas Sci. Eng. 26, 264–278 (2015)
Babelli, I.M.M.: In search of an ideal multiphase flow meter for the oil industry. Arab. J. Sci. Eng. 27(2), 113–126 (2002)
Thorn, R.; Johansen, G.A.; Hjertaker, B.T.: Three-phase flow measurement in the petroleum industry. Meas. Sci. Technol. 24(1), 012003 (2012)
Mwalyepelo, J.; Stanko, M.: Improvement of multiphase flow rate model for chokes. J. Pet. Sci. Eng. 145, 321–327 (2016)
Shao, H.; Jiang, L.; Liu, L.; Zhao, O.: Modeling of multiphase flow through chokes. Flow Meas. Instrum. 60, 44–50 (2018)
Choubineh, A.; Ghorbani, H.; Wood, D.A.; RobabMoosavi, S.; Khalafi, E.; Sadatshojaei, E.: Improved predictions of wellhead choke liquid critical-flow rates: modelling based on hybrid neural network training learning based optimization. Fuel 207, 547–560 (2017)
Gilbert, W.E.: Flowing and gas-lift well performance. API Drill. Prod. Pract. 20, 126–157 (1954)
Tangren, R.F.; Dodge, C.H.; Seifert, H.S.: Compressibility effects in two-phase flow. J. Appl. Phys. 20(7), 637–645 (1949)
Ros, N.C.J.: An analysis of critical simultaneous gas/liquid flow through a restriction and its application to flowmetering. Appl. Sci. Res. 9(Section A), 374–388 (1960)
Poettmann, F.E.; Beck, R.L.: New charts developed to predict gas–liquid flow through chokes. Word Oil 184(3), 95–100 (1963)
Omana, R.A.: Multiphase flow through chokes. M.S. Thesis, University of Tulsa (1968)
Ashford, F.E.; Pierce, P.E.: Determining multiphase pressure drops and flow capacities in down-hole safety valves. J. Pet. Technol. 27(9), 1145–1152 (1975)
Perkins, T.K.: Critical and subcritical flow of multiphase mixtures through chokes. SPE Drill. Complet. 8(4), 271–276 (1993)
Al-Safran, E.M.; Kelkar, M.G.: Predictions of two-phase critical flow boundary and mass flow rate across chokes. SPE Prod. Oper. 24, 249–256 (2009)
Selmer-Olsen, S.; Holm, H.; Haugen, K.; Nilsen, P.; Sandberg, R.: Subsea chokes as multiphase flowmeters: production control at troll olje. In: Proceedings of the BHR Group 7th International Conference on Multiphase Production, Cannes, France, 7–9 June (1995)
Schüller, R.B.; Solbakken, T.; Selmer-Oslen, S.: Evaluation of multiphase flow rate models for chokes under subcritical oil/gas/water flow conditions. SPE Prod. Facil. 18(3), 170–181 (2003)
Schüller, R.B.; Munaweera, S.; Selmer-Olsen, S.; Solbakken, T.: Critical and subcritical oil/gas/water mass flow rate experiments and predictions for chokes. SPE Prod. Oper. 21(3), 372–380 (2006)
Rastoin, S.; Schmidt, Z.; Doty, D.R.: A review of multiphase flow through chokes. J. Energy Res. Technol. 119(1), 1–10 (1997)
Al-Attar, H.H.; Abdul-Majeed, G.H.: Revised bean performance equation for east Baghdad oil wells. SPE Prod. Eng. 3(1), 127–131 (1988)
Ashford, F.E.: An evaluation of critical multiphase flow performance through wellhead chokes. J. Pet. Technol. 26(8), 843–850 (1974)
Abdul-Majeed, G.H.; Maha, R.A.A.: Correlations developed to predict two-phase flow through wellhead chokes. J. Can. Pet. Technol. 30(06), 47–55 (1991)
Achong, I.: Revised bean performance formula for lake maracaibo wells. Internal Company Report, Shell Oil Co., Houston, TX (1961)
Elgibaly, A.A.M.; Nashawi, I.S.: New correlations for critical and subcritical two-phase flow through wellhead chokes. J. Can. Pet. Technol. 37(06), 36–43 (1998)
Abdul-Majeed, G.H.; Aswad, Z.A.: A new approach for estimating the orifice discharge coefficient required in the Ashford–Pierce correlation. J. Pet. Sci. Eng. 5(1), 25–33 (1990)
Al-Marhoun, M.A.: Pvt correlations for middle east crude oils. J. Pet. Technol. 40(05), 650–666 (1988)
Dranchuk, P.M.; Purvis, R.A.; Robinson, D.B.: Computer calculation of natural gas compressibility factors using the standing and Katz correlation. In: Annual Technical Meeting, Edmonton, May 8–12 (1973)
Mirzaei-Paiaman, A.; Salavati, S.: A new empirical correlation for sonic simultaneous flow of oil and gas through wellhead chokes for Persian oil fields. Energy Sour., Part A: Recover., Util., Environ. Eff. 35(9), 817–825 (2013)
Baxendell, P.B.: Bean performance-lake wells. Shell Internal Report (1957)
Pilehvari, A.A.: Experimental study of critical two-phase flow through wellhead chokes. Fluid Flow Projects Report, University of Tulsa (1981)
Fortunati, F.: Two-phase flow through wellhead chokes. In: SPE European Spring Meeting, Amsterdam, Netherlands, 16–18 May (1972)
Surbey, D.W.; Kelkar, B.G.; Brill, J.P.: Study of multiphase critical flow through wellhead chokes. SPE Prod. Eng. 4(02), 142–146 (1989)
Al-Attar, H.H.: Performance of wellhead chokes during sub-critical flow of gas condensates. J. Pet. Sci. Eng. 60(3), 205–212 (2008)
AlAjmi, M.D.; Alarifi, S.A.; Mahsoon, A.H.: Improving multiphase choke performance prediction and well production test validation using artificial intelligence: a new milestone. In: SPE Digital Energy Conference and Exhibition, TX, USA, 3–5 March (2015)
Nasriani, H.R.; Kalantariasl, A.: Choke performance in high-rate gas condensate wells under subcritical flow condition. Energy Sour., Part A: Recover., Util., Environ. Eff. 37(2), 192–199 (2015)
Ghorbani, H.; Wood, D.A.; Moghadasi, J.; Choubineh, A.; Abdizadeh, P.; Mohamadian, N.: Predicting liquid flow-rate performance through wellhead chokes with genetic and solver optimizers: an oil field case study. J. Pet. Exp. Prod. Technol. 9, 1355–1373 (2019)
Safar Beiranvand, M.; Mohammadmoradi, P.; Aminshahidy, B.; Fazelabdolabadi, B.; Aghahoseini, S.: New multiphase choke correlations for a high flow rate Iranian oil field. Mech. Sci. 3(1), 43–47 (2012)
Mirzaei-Paiaman, A.; Salavati, S.: The application of artificial neural networks for the prediction of oil production flow rate. Energy Sour., Part A: Recover., Util., Environ. Eff. 34(19), 1834–1843 (2012)
Levenberg, K.: A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 2(2), 164–168 (1944)
Marquardt, D.W.: An algorithm for least-squares estimation of nonlinear parameters. J. Soc. Ind. Appl. Math. 11(2), 431–441 (1963)
Smyth, G.K.: Nonlinear regression. Encycl. Environ. 4, 1405–1411 (2002)
Murthy, Z.V.P.: Nonlinear Regression: Levenberg–Marquardt Method, pp. 1–3. Springer, Berlin, Heidelberg (2015)
Acknowledgements
The authors gratefully wish to thank Farid CHEMIL, Aissa DAHMOUNE and Boutheyna FARTAS (Production Division, Sonatrach, Hassi-Messaoud) for their support to achieve this work.
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Tellache, N.E., Hassen, M.W., Otmanine, M. et al. Improved Multiphase Flow Rate Models for Chokes in the Algerian HMD Oil Field. Arab J Sci Eng 46, 6817–6833 (2021). https://doi.org/10.1007/s13369-020-04971-z
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DOI: https://doi.org/10.1007/s13369-020-04971-z