[1] OPEC, “Annual Report,” 2019.
[5] S. I. Aanonsen, A. L. Eide, L. Holden, and J. O. Aasen, “Optimizing Reservoir Performance Under Uncertainty with Application to Well Location,” in SPE Annual Technical Conference and Exhibition, 1995, pp. 67–76.
[6] B. L. Beckner and X. Song, “Field Development Planning Using Simulated Annealing - Optimal Economic Well Scheduling and Placement,” in SPE Annual Technical Conference and Exhibition, 1995, pp. 209–221.
[7] O. Uysal and S. Bulkan, “Comparison of Genetic Algorithm and Particle Swarm Optimization for Bicriteria Permutation Flowshop Scheduling Problem,” Int. J. Comput. Intell. Res., vol. 4, p. 159+, Jan. 2008.
[8] A. C. Bittencourt and R. N. Horne, “Reservoir Development and Design Optimization,” in SPE Annual Technical Conference and Exhibition, 1997. [9] B. Güyagüler, “Optimization of Well Placement and Assessment of Uncertainty,” Stanford University, 2002.
[10] V. Johnson and L. Rogers, “Using artificial neural networks and the genetic algorithm to optimize well field design: phase I final report,” California, 1998.
[11] S. I. Aanonsen, A. L. Eide, L. Holden, and J. O. Aasen, “Optimizing Reservoir Performance Under Uncertainty with Application to Well Location,” in SPE Annual Technical Conference and Exhibition, 1995, pp. 67–76.
[12] L. L. Rogers and F. U. Dowla, “Optimization of groundwater remediation using artificial neural networks with parallel solute transport modeling has been successfully applied to a variety of optimization,” Water Resour., vol. 30, no. 2, pp. 457– 481, 1994.
[13] M. Sharifi, M. Kelkar, A. Bahar, and T. Slettebo, “Dynamic Ranking of Multiple Realizations By Use of the Fast-Marching Method,” SPE J., vol. 19, no. 06, pp. 1069–1082, 2014.
[14] I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning. The MIT Press, 2016.
[15] H. Nasrabadi, A. Morales, and D. Zhu, “A survey with special focus on application for gas / gascondensate reservoirs,” J. Nat. Gas Sci. Eng., vol. 5, pp. 6–16, 2012.
[16] R. Balamurugan, A. M. Natarajan, and K. Premalatha, “Stellar-mass black hole optimization for biclustering microarray gene expression data,” Appl. Artif. Intell., vol. 29, no. 4, pp. 353–381, 2015.
[17] L. Bianchi, Æ. M. Dorigo, Æ. L. Maria, and W. J. Gutjahr, “A survey on metaheuristics for stochastic combinatorial optimization,” Nat Comput, vol. 8, pp. 239–287, 2009.
[18] D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Boston: Addison-Wesley Longman Publishing Co., Inc, 1989.
[19] J. E. Onwunalu and L. J. Durlofsky, “Development and Application of a New Well Pattern Optimization Algorithm for Optimizing Large Scale Field Development,” in SPE Annual Technical Conference and Exhibition, 2009.
[20] S. Ding, H. Jiang, J. Li, and G. Tang, “Optimization of well placement by combination of a modified particle swarm optimization algorithm and quality map method,” Comput. Geosci., vol. 18, no. 5, pp. 747–762, 2014.
[21] E. Mohagheghian, L. A. James, and R. D. Haynes, “Optimization of hydrocarbon water alternating gas in the Norne fi eld : Application of evolutionary algorithms,” Fuel, vol. 223, no. January, pp. 86–98, 2018.
[22] T. D. Humphries, R. D. Haynes, and L. A. James, “Simultaneous and sequential approaches to joint optimization of well placement and control,” Comput. Geosci., vol. 18, no. 3–4, pp. 433–448, 2013.
[23] J. E. Onwunalu and L. J. Durlofsky, “Application of a particle swarm optimization algorithm for determining optimum well location and type,” Comput. Geosci., vol. 14, no. 1, pp. 183–198, 2009.
[24] O. Uysal and S. Bulkan, “Comparison of Genetic Algorithm and Particle Swarm Optimization for Bicriteria Permutation Flowshop Scheduling Problem,” Int. J. Comput. Intell. Res., vol. 4, p. 159+, Jan. 2008.
[25] S. Karimi and S. R. Shadizadeh, “A new equation for the determination of a well drainage area in naturally fractured reservoirs,” Pet. Sci. Technol., vol. 30, no. 18, pp. 1953–1964, 2012.
)