Well Placement Optimization Using Differential Evolution Algorithm

Document Type: Research Article


1 Chemical and Petroleum Engineering Department, Sharif University of Technology, Tehran, I.R. IRAN

2 Faculty of Petroleum Engineering, Amirkabir University of Technology, Tehran, I.R. IRAN

3 Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, I.R. IRAN


Determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. It is a computationally intensive task due to the large number of simulation runs required. Therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum number of function evaluations. In this study, the Differential Evolution (DE) algorithm is applied for the determination of optimal well locations. DE is a stochastic optimization algorithm that uses a population of solutions which evolve through generations to reach the global optimum. To investigate the performance of this algorithm, three example cases are considered which vary in dimension and complexity of the reservoir model. For each case, both DE algorithm and the widely used Genetic Algorithm (GA) are applied to maximize a Modified Net Present Value (MNPV) as the objective function. It is shown that DE outperforms GA in all cases considered, though the relative advantage of the DE vary from case to case. These results are very promising and demonstrate the applicability of DE for this challenging problem.


Main Subjects

[1] Afshari S., Aminshahidy B., Pishvaie M.R., Application of an Improved Harmony Search Algorithm in Well Placement Optimization Using Streamline Simulation, Journal of Petroleum Science and Engineering, 78(3-4), p. 664 (2011).

[2] Beckner B.L., Song X., Field Development Planning Using Simulated Annealing-Optimal Economic Well Scheduling and Placement, SPE 30650(1995).

[3] Bittencourt A.C., Horne R.N., Reservoir Development and Design Optimization, SPE 38895 (1997).

[4] Güyagüler B., Horne R.N., Rogers L., Rosenzweig J.J., Optimization of Well Placement in a Gulf of Mexico Waterflooding Project, SPE Reservoir Evaluation & Engineering, 5(3), p. 229 (2002).

[5] Yeten B., Durlofsky L.J., Aziz K., Optimization of Nonconventional Well Type, Location and Trajectory, SPE Journal, 8(3), p. 200 (2003).

[6] Bangerth W., Klie H., Wheeler M.F., Stoffa P.L., Sen M.K., On Optimization Algorithms for the Reservoir Oil Well Placement Problem, Computational Geosciences, 10(3), p. 303 (2006).

[7] Handels M., Zandvlier M.J., Brouwer D.R., Jansen J.D.,Adjoint-Based Well Placement Optimization under Production Constraints, SPE 105797 (2007).

[8] Wang C., Gaoming L., Reynolds A.C., Optimum Well Placement for Production Optimization, SPE 111154 (2007).

[9] Sarma P., Chen W.H., Efficient Well Placement Optimization with Gradient-Based Algorithms and Adjoint Models, SPE 112257 (2008).

[10] Onwunalu J.E., Durlofsky L.J., Application of a Particle Swarm Optimization Algorithm for Determining Optimum Well Location and Type, Computational Geosciences, 14(1), p. 183 (2010).

[11] Babu B.V., Munawar S.A., Differential Evolution Strategies for Optimal Design of Shell-and-Tube Heat Exchangers, Chemical Engineering Science, 62(14), p. 3720 (2007).

[12] Babu B.V., Angira R., Modified Differential Evolution (MDE) for Optimization of Non-Linear Chemical Processes, Computers & Chemical Engineering30(6-7), p. 989. (2006).

[13] Nolle L., Zelinka I., Hopgood A.A., Goodyear A., Comparison of a Self-Organizing Migration Algorithm with Simulated Annealing and Differential Evolution for Automated Waveform Tuning, Advances in Engineering Software, 36(10), p: 645-653, (2005).

[14] Onwubolu G., Davendra D., Scheduling Flow Shops Using Differential Evolution Algorithm, European Journal of Operational Research, 171(2), p. 674 (2006).

[15] Vasan A., Komaragiri S.R., Application of Differential Evolution for Irrigation Planning: An Indian Case Study, Water resources Management, 21(8), p. 1393 (2007).

[16] Foroughnia A., Pishvaie M.R., Aminshahidy B., Control and Optimization of Oil Production Using Natural Gas Lift, NashriehShimivaMohandesiShimi Iran (NSMSI), 30(1), p. 21 (2011).[In Persian]

[17] Seyedshenava J., Seyfi H., Sepasian M.S., Optimal Load Flow in HVAC/HVDC Transmission Networks Using a Combinatorial Heuristic Algorithm, NashriehMohandesiBarghva Computer Iran,7(4), p. 299 (2010). [In Persian]

[18] Storn R., Price K., "Differential Evolution-a Simple and Efficient Adaptive Scheme for Global Optimization Over Continues Spaces", Technical Report TR-95-012, Berkeley, CA, USA, (1995).

[19] Storn R. Price K., Differential Evolution-A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, Journal of Global Optimization, 11, p. 341 (1997).