In this study, we use an ensemble Kalman filter (EnKF) to perform history matching of the PUNQ-S3 reservoir model using data from six production wells over an eight-year period. This is followed by well placement optimization using a genetic algorithm (GA) combined with pseudohistory matching, carried out over two years, following the placement of the first future well. Thus, this approach not only provides increased certainty in optimal well placement but also, using EnKF as a history matching method, requires only a single ¡°best estimate¡± realization for objective function evaluation during GA optimization. As a result, the total time taken to find the optimal well locations is significantly reduced. We illustrate this through comparison with the previous research.