This study has developed a simulator for efficient production of geothermal energy and geological sequestration of CO2 simultaneously. The simulator developed in this research is combined with the program optimizing well locations and injection rates in order to maximize the cumulative production of geothermal energy. Thus, the reservoir performances have been predicted for water injection and CO2 injection. The results show that injecting CO2 instead of water as a recharge fluid achieves a higher energy production rate. The direct injection of gas phase suppresses the pressure decline in a reservoir and the temperature reduction through a wellbore. In order to efficiently optimize well locations and injection rates, several optimization algorithms: Iterative Latin Hypercube Sampling (ILHS), Particle Swarm Optimization (PSO), Cauchy Mutation Particle Swarm Optimization (CMPSO), and Genetic Algorithm (GA) have been used. This program is successfully applied to the search of the optimized well locations and recharge fluid rates.