ACES  Vol.3 No.4 A , October 2013
A Comparison between Evolutionary Metaheuristics and Mathematical Optimization to Solve the Wells Placement Problem
ABSTRACT
The Wells Placement Problem (WPP) consists in choosing well locations within an oil reservoir grid to maximize the reservoir total oil production, subject to distance threshold between wells and number of wells cap constraints. A popular approach to WPP is Genetic Algorithms (GA). Alternatively, WPP has been approached in the literature through Mathematical Optimization. Here, we conduct a computational study of both methods and compare their solutions and performance. Our results indicate that, while GA can provide near-optimal solutions to instances of WPP, typically Mathematical Optimization provides better solutions within less computational time.

 


Cite this paper
G. AlQahtani, A. Alzahabi, E. Kozyreff, I. Farias and M. Soliman, "A Comparison between Evolutionary Metaheuristics and Mathematical Optimization to Solve the Wells Placement Problem," Advances in Chemical Engineering and Science, Vol. 3 No. 4, 2013, pp. 30-36. doi: 10.4236/aces.2013.34A1005.
References
[1]   G. AlQahtani, R. Vadapalli, S. Siddiqui and S. Bhattacharya, “Well Optimization Strategies in Conventional Reservoirs,” Proceedings of SPE Saudi Arabia Section Technical Symposium and Exhibition, Al-Khobar, 8-11 April 2012, 13 Pages.
http://dx.doi.org/10.2118/160861-MS

[2]   O. Badru and C. S. Kabir, “Well Placement Optimization in Field Development,” SPE Annual Technical Conference and Exhibition, Denver, 5-8 October 2003, 9 Pages.

[3]   W. Bangerth, H. Klie, M. F. Wheeler, P. L. Stoffa and M. K. Sen, “On Optimization Algorithms for the Reservoir Oil Well Placement Problem,” Computational Geosciences, Vol. 10, No. 3, 2006, pp. 303-319.
http://dx.doi.org/10.1007/s10596-006-9025-7

[4]   A. S. Cullick, S. Vasantharajan and M. W. Dobin, “Determining Optimal Well Locations from a 3D Reservoir Model,” US Patent No. US6549879 B1, 2003.

[5]   D. Y. Ding, “Optimization of Well Placement Using Evolutionary Algorithms,” SPE EAGE Annual Technical Conference and Exhibition, Rome, 9-12 June 2008, p. 912.

[6]   B. Guyaguler, R. N. Horne, L. L. Rogers and J. J. Rosenzweig, “Optimization of Well Placement in a Gulf of Mexico Waterflooding Project,” SPE Annual Technical Conference and Exhibition, Vol. 5, No. 3, 2000, pp. 110-118.

[7]   J. Onwunalu, M. Litvak, L. J. Durlofsky and K. Aziz, “Application of Statistical Proxies to Speed up Field Development Optimization Procedures,” International Conference and Exhibition, Abu Dhabi, 3-6 November 2008, 14 Pages.

[8]   G. W. Rosenwald and D. W. Green, “A Method for Determining the Optimum Location of Wells in a Reservoir Using Mixed-Integer Programming,” SPE Journal, Vol. 14, No. 1, 1974, 12 Pages.

[9]   S. Vasantharajan and A. S. Cullick, “Well Site Selection Using Integer Programming Optimization,” Proceedings of IAMG’97, 22-26 September 1997, pp. 421-426.

[10]   R. Haupt and S. Haupt, “Practical Genetic Algorithms,” John Wiley and Sons, Hoboken, 2004.

[11]   G. L. Nemhauser and L. A. Wolsey, “Integer and Combinatorial Optimization,” John Wiley and Sons, Hoboken, 1988.

[12]   P. S. Cruz, R. N. Horne and C. V. Deutsch, “The Quality Map: A Tool for Reservoir Uncertainty Quantification and Decision Making,” SPE Annual Technical Conference and Exhibition, Vol. 7, No. 1, 2004, 9 Pages.

 
 
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