Genetic algorithms for optimizing the remediation of contaminated aquifer

Produced water constitutes a large amount of waste fluids during the produc tion operation of an oil field. Underground injection for disposing the was tewater from hydrocarbon production is an engineering problem due to the po ssibility of leakage of injected pollutant material from receiving medium t o a drinking water source. This paper describes a method for optimization o f polluted aquifer remediation design using one of the artificial intellige nce optimization methods, namely Genetic Algorithms (GAs). As a case study, the contaminated area was created by using a groundwater transport simulat or, which is based on Method of Characteristics (MOC). Then, the developed computer program was run to find the optimum solution for remediation, and the solution yielded from the program was verified by using a groundwater s imulator. The plume was captured and the concentration level of chloride io n within the aquifer was diminished by using extraction wells. The analytic al model approach provided different alternatives for appropriate isolation of plume. GAs were used as an optimization technique for making a decision among the alternatives, by considering operation time, number of wells, pu mping rate and drawdown as decision variables and constraints.