@inproceedings{97255014d37d4b5e9daeba80a0eb953c,
title = "Optimal injector placement coupled multi-objective genetic algorithm with a black-oil simulator in waterflooding project",
abstract = "Well placement optimization is the process to search for the optimal operating conditions of infill wells for improving recovery. Infill drilling is expected to generate the additional revenue, but requires an enormous initial investment. This study determines the optimal number of injection wells and their locations in waterflooding project. Multi-objective genetic algorithm based on non-dominated sorting and crowding distance sorting is adapted to find Pareto-solutions which minimize the cost and maximize the revenue simultaneously. Non-dominated sorting guarantees the convergence and crowding distance sorting maintains the diversity of Pareto-solutions. The result shows that the suggested approach can obtain production scenarios of good quality satisfying given objectives successfully.",
author = "Min, {B. H.} and C. Park and Kang, {J. M.} and Ahn, {T. W.} and Chung, {S. H.} and Kim, {S. Y.}",
year = "2011",
language = "English",
isbn = "9781617829666",
series = "73rd European Association of Geoscientists and Engineers Conference and Exhibition 2011: Unconventional Resources and the Role of Technology. Incorporating SPE EUROPEC 2011",
publisher = "Society of Petroleum Engineers",
pages = "3651--3655",
booktitle = "Society of Petroleum Engineers - 73rd European Association of Geoscientists and Engineers Conference and Exhibition 2011 - Incorporating SPE EUROPEC 2011",
}