Optimization of ICDs' Port Size in Smart Wells Using Particle Swarm Optimization (PSO) Algorithm through Neural Network Modeling

Document Type : Research Article


1 Amirkabir University of Technology, Tehran, I.R. IRAN

2 Research Institute of Petroleum Industry (RIPI), Tehran, I.R. IRAN


Oil production optimization is one of the main targets of reservoir management. Smart well technology gives ability of real time oil production optimization. Although this technology has many advantages; optimum adjustment or sizing of corresponding valves is its issue. In this research optimum sizing of ICDs which are passive control valves has been focused on by designing a neural network to simulate reservoir behavior and applying Particle Swarm Optimization (PSW) algorithm to find optimum port size for ICDs. Indeed; this work eliminates the need for lots of expensive and time consuming iteration through reservoir simulator. The achieved objectives of the work were oil production maximization and water production minimization.  


Main Subjects

[1] Gao c., Ranjeswaran T., Surtin U., Nakagawa E., "A Literature Review on Smart-Well Technology," in SPE, Oklahoma, March-April (2007).
[2] Oberwinker C., Stundener M., Team D., "From Real Time Data to Production Optimization," in SPE, March (2004).
[3] Naus M.M.J.J., Dolle N., Jansen J., "Optimization of Commingled Production Using Infinitely Variable Inflow Control Valves," in SPE, Houston, (2005).
[4] Yeten B., Brouwer D.R., Durlofsky L.J., Aziz K., Decision Analysis Under Uncertainty for Smart Well Deployment, Journal of petroleum Science & Engineering, 43, p. 183 (2004).
[5] Yeten B., Durlofsky L.J., Khalid A., "Optimization of Smart Well Control," in SPE, Alberta, November (2002).
[6] Aitokhuehi I., Durlofsky L.J., Optimization the Performance of Smart Well in Complex Reservoirs Using Continuously Updated Geologcal Models, Petroleum Science & Engineering, 48(3-4), p. 254 (2005).
[7] Taware S., Sharme M., Alhuthali A.H., Gupta A.D., "Optimization Water flood Management Under Geological Uncertainty Using Accelerated Production Strategy," in SPE, Florence, (2010).
[8] Alhuthali A.H., Gupta A.D., Yeten B., Fontanilla J.P., "Field Applications of Waterflood Optimization via Optimal Rate Control with Smart Well," in SPE, Woodlands, (2009).
[9] Van Essen G.M., Jansen J.D., Brouwer D.R., Douma S.G., Zandvliet M.J., Rollett K.I., Harris D.P., "Optimization of Smart Wells in the St. Joseph Field," in SPE, Jakarta, (2009).
[10] Alhuthali A.H., Gupta A.D., Yeten B., Fontanilla J.P., "Optimal Rate Under Geologic Uncertainty," in SPE, Oklahoma, (2008).
[11] Shuai Y., White C.D., Zhang H., Sun T., "Using Multiscale Regularization to Obtain Realistic Optimal Control Strategies," in SPE, Woodlands, (2011).
[12] Moreno J.C. et al., "Optimization Workflow for Designing Complex Wells," in SPE, Vienna, (2006).
[13] Meun P., Tondel P., Godhavn J.M., Aamo O.M., "Optimization of Smart well Production Through Nonlinear Model Predictive Control," in SPE, Amsterdam, (2008).
[14] Al-Ghreeb Z.M., "Monitoring and Control of Smart Wells," in Monitoring and Control of Smart Wells.: Copy by Zeid Al-Ghreeb , (2009).
[15] Conejeros R., Lenoach B., Model-Based Optimal of Dual Completion Wells, Petroleum Science & Engineering, 42(1), p. 1 (2004).
[16] Harrison S.J., Marshall R.F., "Optimization and Training of Feedforward Neural Network by GAs," in Proceeding of IEE Second International Conference on Artificial Neural Networks, pp. 39-43 (1991).
[17] کمالی، محمد رضا؛ علی­مددی، فاطمه؛ فخری، امین؛ کاربرد روش­های هوشمند در مهندسی نفت و علوم زمین ایران, تهران، پژوهشگاه صنعت نفت, (1390).
[18] Graudenz S., Bornholdt D., General Asymmetric Neural Networks and Structure Design by Genetic Algorithms, Neural Netw, 5, p. 327 (1992).
[19] Moselhi T., Fazio O., Hegazy P., Developing Practical Neural Network Applications Using Back-Propagation, Microcomput. Civ. Eng, 9, p. 145 (1994).
[20] Anderson M.J., Whitcomb P.J., "DOE Simplified", INC, (2000).
[21] Beielstein T.B., Chiarandini M., Paquete L., Preuss M., "Experimental Mrthods for the Analysis of Optimization Algorithms", Berlin: Springer, (2010).
[22] Montgomery D.C., "Design and Analysis of Experimental", Jone Wiley & Sons, (2001).
[23] Aggarwal A., Singh H., Kumar P., Singh M., Optimization Power Consumption for CNC Turned Parts Using Response Surface Methodology and Taguchi Techniqu-A Comparative Analysis, Material Processing Technology, 200(1-3), p. 373 (2008).
[24] Kennedy Clerc, "The Particle Swarm Explosion, Stability and Convergence in a Multideimentional Complex Space," IEEE, Vol. on Evolutionary Computation, 6(1), p. 58 (2002).
[25] Eberhart J., Kennedy R., "Particle Swarm Optimization," in Proceedings IEEE International Conference on Neural Networks, (1995).
[26] شالکف، رابرت جی؛ مترجم: جورابیان، محمود؛ شبکه های عصبی مصنوعی، دانشگاه شهید چمران اهواز, (1384).