Well Placement Optimization Using a Particle Swarm Optimization Algorithm, a Novel Approach

被引：25
|
作者：
Afshari, S. [1 ]
Pishvaie, M. R. [1 ]
Aminshahidy, B. [2 ]
机构：
[1] Sharif Univ Technol, Tehran, Iran
[2] Univ Tehran, Inst Petr Engn, Tehran, Iran
来源：
PETROLEUM SCIENCE AND TECHNOLOGY | 2014年 / 32卷 / 02期
关键词：
genetic algorithm; particle swarm optimization; simulated annealing; streamline simulation; well placement optimization;
D O I：
10.1080/10916466.2011.585363
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Optimal well placement is a crucial step in reservoir development process. The key points in such an optimization process are using a fast function evaluation tool and development of an efficient optimization algorithm. This study presents an approach that uses particle swarm optimization algorithm in conjunction with streamline simulation to determine the optimum well locations within a reservoir, regarding a modified net present value as the objective. Performance of this algorithm was investigated through several different examples, and compared to that of genetic algorithm (GA) and simulated annealing (SA) methods. It was observed that particle swarm optimization algorithm outperformed both SA and GA in terms of efficiency and accuracy.
引用
收藏
页码：170 / 179
页数：10
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