In a future scenario, the successful development of geothermal industry will result in the large-scale deployment of new deep geothermal projects. In highly populated areas, such as the Netherlands, such a development will lead to a dense grid of neighbouring licenses. In such a situation a new project requires careful design and planning as the available subsurface space can become scarce, leading to the potential thermal interference with the neighbouring licenses and competing usage of the resources. Interference can cause the reduction of lifetime, produced energy, and the profitability of neighbouring projects. Therefore, it becomes important to consider the thermal interference while designing these systems in such dense areas to be able to obtain maximum energy and profit without hindering neighbours. This research project assesses the question of thermal interferences in neighbouring geothermal systems using a numerical simulation approach regarding what parameters are ideal for optimisation in neighbouring systems and what parameters should be monitored. To generate a numerical model capable of describing and predicting the effect of thermal interference the software package COMSOL Multiphysics 5.4 was used. The physics of fluid flow and heat transfer in porous media is applied to the reservoir model, and the finite element method is used to approximate the solution of these equations. Sensitivity analyses are performed on all input parameters as a post-processed simulation to control their influence on the output performance. The input parameters are divided into two categories; first, operational-controlled parameters: start time, injection temperature, injection/production flow rate, well spacing, well distance to the license border, and second, natural-controlled parameters including permeability and its anisotropy as kx/ky ratio. At the end of the parametric sensitivity analysis, an economic model is used as an instrument to evaluate how these input parameters can affect the long-term project feasibility. In this study, we present the results of global comparisons between each parameter while incorporating all measurement control (lifetime, cumulative energy and NPV). The results from the 3D qualification, the correlation between measurement controls and the reference base case study are used as background for this comparison. Our results show that the injection temperature and well spacing are ideal designed parameters to optimise profitability because the negative effect on the neighbour is only 1% for every 10°C reduction injection temperature and increasing 300 m of well spacing. On the other hand, injection / production flow rate is the most influential parameter that must be monitored in neighbouring production areas.