Economical Evaluation of Injection Frequency in Surfactant and Water Flooding Using Genetic Algorithm

Waterflood operation is the most widely used secondary recovery method. Large reservoirs containing thousands of wells are operated under waterflood conditions to increase the ultimate recovery. Due to lack of resources and appropriate tools, waterflood optimization is often done on trial and error bases.  waterflooding is an effective process, surfactant flooding is used to recover oil from reservoirs by wettability alteration and interfacial tension reduction. Surfactants have been identified which can lower the IFT between oil and aqueous phase. The reduction of IFT leads to mobilization of the oil by buoyancy forces. In all the enhanced oil recovery processes, flow of displacing and displaced fluid in a petroleum reservoir is affected by the wettability of the reservoir rock. Economical effectiveness is a main challenge in feasibility of any EOR method. In this study, we investigate the economic efficiency of both surfactant and water flooding by algorithm genetic optimization. One of the important optimization variables is well placement. Determining of the location of new wells is a complicated problem which depends on reservoir and fluid properties. Various methods have been suggested for this problem. Among these, direct optimization, although accurate, is impossible due to the number of simulations required.   Optimal placement of up to three surfactant injection wells was studied at two fields. One of the Iranian conventional field and a hypothetic fractured field. Injection rate and injection time was also optimized. The net present value of the surfactant and water flooding projects was used as the objective function. Profits and costs during the time period of the project were taken into consideration.