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Multiphase Science and Technology

年間 4 号発行

ISSN 印刷: 0276-1459

ISSN オンライン: 1943-6181

SJR: 0.144 SNIP: 0.256 CiteScore™:: 1.1 H-Index: 24

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NEAR-WELLBORE SIMULATION OF AUTONOMOUS INFLOW CONTROL DEVICES COMPLETION: COMPARING COMPUTATIONAL FLUID DYNAMICS WITH CONVENTIONAL RESERVOIR SIMULATION

巻 32, 発行 2, 2020, pp. 93-112
DOI: 10.1615/MultScienTechn.2020031786
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要約

Computational fluid dynamics (CFD) was used to model the flow in a wellbore equipped with autonomous inflow control devices (AICDs) in the near-wellbore region and the results were compared with a conventional reservoir simulator. Unlike the reservoir simulator, CFD predicted the flow field not only in the porous domain, but also in the free-flow zones (micro-annulus and AICDs). This allowed the understanding of the flow field in the near-well region and the comprehension of the interactions between the water cone and the action of the AICDs. Some aspects of best practices of CFD simulations were proposed based on comparisons with empirical correlations and experimental data. Under laminar flow in the micro-annulus, the numerical model presented deviations below 40% compared with the reference data (most deviations below 20%). Furthermore, the mesh type at the reservoir domain revealed that the numerical diffusion can adversely affect the formation of the water cone. The best mesh structure among the studied in this work was the structured quad/hexahedral, whereas triangular/tetrahedral meshes should be avoided. Overall, CFD simulations revealed a complex flow pattern that cannot currently be adequately described by conventional reservoir modeling. However, computational cost of CFD simulation was at least 3 weeks in parallel computing (32 CPUs), while reservoir simulation solved the same numerical domain in few minutes in serial calculation.

参考
  1. Afuekwe, A. and Bello, K., Use of Smart Controls in Intelligent Well Completion to Optimize Oil & Gas Recovery, J. Eng. Res. Rep, vol. 5, pp. 1-14,2019.

  2. Al Marzouqi, A.A.R., Helmy, H., Keshka, A.A., Elasmar, M., and Shafia, S., Wellbore Segmentation Using Inflow Control Devices: Design and Optimisation Process, Proc. of Int. Petroleum Exhibition and Conf., Abu Dhabi, UAE, SPE-137992-MS, 2010.

  3. ANSYS, ANSYSDocumentation, Release 19, 2018.

  4. Birchenko, V., Bejan, A.I., Usnich, A., and Davies, D., Application of Inflow Control Devices to Heteroge-neous Reservoirs, J. Petrol. Sci. Eng., vol. 78, pp. 534-541, 2011.

  5. Brooks, R.J. and Corey, A.T., Hydraulic Properties of Porous Media, Vol. 3, Colorado State University, Fort Collins, CO, 1964.

  6. Cortes, G.C. and Fitzpatrick, J., Enhancing Oil Recovery with Autonomous Inflow Control Devices, Offshore World, vol. 12, pp. 22-24,2014.

  7. Dikken, B.J., Pressure Drop in Horizontal Wells and Its Effect on Production Performance, J. Petrol. Tech, vol. 42, pp. 1426-1434, 1990.

  8. Durlofsky, L.J., An Approximate Model for Well Productivity, Math. Geol., vol. 32, pp. 421-438,2000.

  9. Ellis, T., Erkal, A., Goh, G., and Jokela, T., Inflow Control Devices-Raising Profiles, Oilfield Rev. Winter, vol. 21, pp. 30-37, 2009.

  10. Erandi, D., Wijeratne, N., and Halvorsen, B.M., Computational Study of Heavy Oil Production, Proc. of the 56th SIMS, Linkoping, Sweden, 2015.

  11. Idel'chik, I.E., Handbook of Hydraulic Resistence, 3 ed., Mumbai, India: Jaico Publishing House, 1966.

  12. Least, B., Greci, S., Konopczynski, M., and Thornton, K., Inflow Control Devices Improve Production in Heavy Oil Wells, SPE Middle East Intelligent Energy Conf. and Exhibition, Manama, Bahrain, 2013.

  13. Li, H., Tan, Y., Jiang, B., Wang, Y., A Semi-Analytical Model for Predicting Inflow Profile of Horizontal Wells Inbottom-Water Gas Reservoir, J. Petrol. Sci. Eng., vol. 160, pp. 351-362, 2018.

  14. Menter, F.R., Two-Equation Eddy-Viscosity Turbulence Models for Engineering Applications, AIAA J, vol. 32, pp. 1598-1605, 1994.

  15. Molina, O.M., Application of Computational Fluid Dynamics to Near-Wellbore Modeling of a Gas Well, Master's, Louisiana State University, 2015.

  16. Nield, D. and Bejan, A., Convection in Porous Media, New York: Springer-Verlag, 2005.

  17. Schiller, L. andNaumann, A., A Drag Coefficient Correlation, Z. Ver. Deutsch. Ing., vol. 77, pp. 318-320, 1935.

  18. Szanyi, M.L., Hemmingsen, C.S., Yan, W., Walther, J.H., and Glimberg, S.L., Near-Wellbore Modeling of a Horizontal Well with Computational, J. Petrol. Sci. Eng., vol. 160, pp. 119-128, 2018.

  19. Thornton, K., Design of Autonomous Inflow Control Device Completions in Heavy Oil for Complex Reservoir Structures, SPE Latin America and Caribbean Heavy and Extra Heavy Oil Conf., Lima, Peru, 2016.

  20. Ugwu, A.A. and Moldestad, B.M.E., The Application of Inflow Control Device for an Improved Oil Recovery Using ECLIPSE, Proc. of the 9th EUROSIM & the 57th SIMS, Oulu, Finland, 2016.

  21. Wang, J., Liu, H., Liu, Y., Jiao, Y., Wu, J., and Kang, A., Mechanism and Sensitivity Analysis of an Inflow Control Devices (ICDs) for Reducing Water Production in Heterogeneous Oil Reservoir with Bottom Water, J. Petrol. Sci. Eng., vol. 146, pp. 971-982, 2016.

  22. Zhang, N., Li, H., Liu, Y., Shan, J., Tan, Y., and Li, Y., A New Autonomous Inflow Control Device Designed for a Loose Sand Oil, J. Petrol. Sci. Eng., vol. 178, pp. 344-355,2019.

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