Well Placement Optimization Using Firefly Algorithm and Crow Search Algorithm

Abstract

Optimization of well placement is one of the main difficult factors in the development process in the oil and gas industry. The well placement optimization is high dimensional, multi-modal and discontinuous. In previous research, conventional and non-conventional optimization techniques have been applied to resolve this problem. However, gradient-free optimization techniques such as genetic algorithm and particle swarm optimization which is considered as the most efficient algorithms in this area suffer from local optima. In this article, two new metaheuristic optimization techniques, namely, crow search algorithm and firefly algorithm are applied to the well placement optimization problem and their applications to maximize the net profit value are studied. To study the performance of the firefly and crow search algorithm, Eclipse and MATLAB environment are used. The proposed techniques are compared to popular established methods for optimizing well placement. Results show that the firefly algorithm is proved to be efficient and effective compared to other established techniques. However, the standard crow search algorithm is not suited to this problem. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.