Optimization of Polymer Flooding Using Genetic Algorithm

One of the methods to achieve optimal conditions in increasing oil recovery through injecting polymers is by optimizing parameters that influence success provide information and be considered when determining new schemes for implementation future. Optimization obtain optimum value factor best PV, injection rate, time, pressure, adsorption, residual resistance (RRF), inaccessible pore volume (IPV) using a genetic algorithm with three training ratios testing 70: 30, 80: 20 90: 10 1000 datasets. The obtained each parameter at ratio 10, which model lowest reference error RSME 0.241104 MAPE 19.1964 classified as good prediction adsorption 0.1737 (g/l), rate 703 (bpd), pressure 1816, IPV 0.2524, RRF 4.8319 finally 53.9557.