Development of an advanced multi-objectives approach to optimise the long-term performance of enhanced geothermal system (EGS) reservoirs

Enhanced geothermal system (EGS) reservoirs are artificial deep reservoirs designed to exploit geothermal power accumulated within hot dry rocks in order to generate electricity. EGS reservoirs have large potential to be exploited as a renewable source of energy. However, currently commercial exploitation is still not feasible and despite research that has attempted to achieve a cost-effective EGS reservoir design with high performance over long periods of exploitation. Previous studies have focused on investigating the impact of single or multi design parameters on EGS reservoir performance without considering their interdependency during heat extraction processes and impacts on reservoir total cost associated with creation and operation costs. This research has conducted an optimisation assessment taking into consideration many design parameters and their interdependency during optimisation process. The key contribution of the research is associated with the development of numerical analysis for both doublet and multi-wells reservoirs integrated with an artificial intelligence application, generated from genetic algorithm GA. During parametric study of doublet well reservoirs, results revealed that the maximum mass flow rate production was 30 kg/s, and this value was achieved during the parametric study of injection pressure and reservoir permeability. It was also observed that different designs of doublet well EGS reservoirs still could not maintain commercial mass flow rate (80 kg/s). However, commercial mass flow rate was achieved with multi wells reservoir through increasing injection pressure and number of wells. The results of two optimisation scenarios (with and without improving reservoir permeability) of doublet EGS reservoirs revealed that the permeability of the reservoir has a significant influence on selecting the other artificial design parameters. The proposed methodology established in this research can be used to transform the way EGS reservoirs are currently designed to be exploited leading to a cost-effective power source. In addition, the methodology has the flexibility and potential to be adapted during and post design of EGS reservoirs.