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

Document Type : Original Paper


1 Amirkabir University of Technology Tehran Polytechnic, Tehran, Iran

2 Research Institute Of Petroleum Industry, Tehran, Iran


Oil production optimization is one of the main targets of reservoir management. Smart well technology gives the ability of real time oil production optimization. Although this technology has many advantages; optimum adjustment or sizing of corresponding valves is still an issue to be solved. In this research, optimum port sizing of inflow control devices (ICDs) which are passive control valves is focused on by designing a neural network to simulate reservoir behavior and applying Particle Swarm Optimization algorithm to find optimum port size for ICDs. Indeed; this work eliminates the need for lots of expensive and time consuming iterations through reservoir simulator. The objective of the work is to maximize the oil production.


[1] Alhuthali, A.H., Gupta, A.D., Yeten, B. and Fontanilla, J.P. (2009). Field applications of waterflood optimization via optimal rate control with smart well. SPE, Woodlands conference.
[2] Alhuthali, A.H., Gupta, A.D., Yeten, B. and Fontanilla, J.P. (2008). Optimal rate under geologic uncertainty. SPE, Oklahoma conference.
[3] Al-Ghreeb, Z.M. (2009). Monitoring and control of smart wells. Thesis for MSc.
[4] Aitokhuehi, I. and Durlofsky, L.J. (2005). "Optimization the performance of smart well in complex reservoirs using continuously updated geological models."Pet. Sci. Eng., pp. 254-264.
[5] Beielstein, T.B., Chiarandini, M., Paquete, L. and Preuss, M. (2010). Experimental Methods for the analysis of optimization algorithms.Springer, Berlin.
[6] Eberhart, J. and Kennedy, R. (1995). Particle Swarm Optimization. IEEE, Conference on Neural Networks.
[7] Gao, c., Ranjeswaran, T., Curtin, U. and Nakagawa, E. (2007). A literature review on smart-well technology. SPE, Oklahoma, March-April.
[8] Graudenz, S. and Bornholdt, D. (1992). General asymmetric neural networks and structure design by genetic algorithms. NeuralNetw, Vol.5. pp. 327-334.
[10] Harrison, S.J. and Marshall, R.F. (1991). Optimization and training of feedforward neural network by Gas. IEEE Conference on Artificial Neural Network. 39-43.
[11] Kamali, M.R., Madadi F, A. and Fakhari, A. (2011). Application of intelligent methods in Petroleum Engineering and Geosciences. Research Institute of Petroleum Industry (RIPI).
[12] Kennedy, C. (2002). The particle swarm Explosion, stability and convergence in a multidimensional complex space. IEEE, Vol. on Evolutionary Computation, 2002.
[13] Moreno, J.C. (2006). Optimization workflow for designing complex wells. SPE, Vienna Conference.
[14] Meun, P., Tondel, P., Godhavn, J.M. and Aamo, O.M. (2008). Optimization of smart well production through nonlinear model predictive control. SPE, Amsterdam conference.
[15] Moselhi, T., Fazio, O. and Hegazy, P. (1994). "Developing practical neural network applications using back-propagation." Microcomput.Civ., Vol. 9. pp. 145-159.
[16] Naus, M.M.J.J., Dolle, N. and Jansen, J. (2005). "Optimization of commingled production using infinitely variable Inflow Control Valves." SPE, Houston conference.
[17] Oberwinker, C., Stundener, M. and Team, D. (2004). From real-time data to production optimization. SPE conference, March.
[18] Shuai, Y., White, C.D., Zhang, H. and Sun, T.(2011). using multiscale regularization to obtain realistic optimal control strategies. SPE, Woodlands Conference.
[19] Sobieski, G. and Venter, J. (2002). Particle Swarm Optimization. Structural Dynamics, and Materials Conference, Denver.
[20] Taware, S., Sharme, M., Alhuthali, A.H. and Gupta, A.D. (2010). Optimization water flood management under geological uncertainty using accelerated production strategy. SPE, Florence conference.
[21] Van Essen, G.M. (2009). Optimization of smart wells in the St.Joseph Field, SPE, Jakarta conference.
[22] Yeten, B., Brouwer, D.R., Durlofsky, L.J. and Aziz, K. (2004). "Decision analysis under uncertainty for smart well deployment."J. Pet. Sci.Eng., pp. 183-199.
[23] Yeten, B., Durlofsky, L.J. and Khalid, A. (2002). Optimization of smart well control. SPE, Alberta, November conference.