Ramadani, Ramadani (2023) Optimasi Polymer Flooding Menggunakan Genetic Algorithm. Other thesis, Fakultas Teknik Perminyakan.

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Abstract

Polymer flooding is one of the EOR methods which is considered to have good effectiveness in increasing oil recovery by up to 50% or more. Seeing this success, it is important to conduct research to achieve optimum conditions to increase oil recovery by optimizing the parameters that influence the success of polymer flooding in order to provide information and be considered when determining a new scheme for implementing polymer flooding in the future. This research was conducted with the aim of obtaining the optimum value of the Recovery Factor and the best value of the parameters PV, Injection Rate, Injection Time, and Injection Pressure, Adsorption, Residual Resistance Factor (RRF), and Innacessible Pore Volume (IPV) produced through optimization using Genetic Algorithm with 3 ratios of Training and Testing 70 : 30, 80 : 20 and 90 : 10 using 1000 datasets. The best value obtained for each parameter is at a ratio of 90: 10 which is the best model with the lowest reference error value with RSME of 0.241104 and MAPE value of 19.1964 classified as good prediction with the value of each parameter are adsorption 0.1737 (g/l), injection rate 703 (Bpd), injection pressure 1816, IPV 0.2524, RRF 4.8319 and the optimum value for Recovery Factor is 53.9557..

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