Geothermal energy stands out as a sustainable and renewable energy source that is attractive to global energy transition. The great potential of geothermal resources in deep sedimentary basins in North Dakota makes it an attractive and alternative source of energy. Effective utilization of geothermal resources requires a good understanding of inherent uncertainties and variabilities. This study incorporates the application of geo-statistical methods on geothermal reservoir engineering principles for evaluating uncertainty parameters within a geothermal reservoir. Uncertainty analysis quantifies the variability and ambiguity of subsurface parameters to better evaluate resource utilization and project feasibility. This study accounts for uncertainties in field data inputs from the Red river formation and is essential to assess the geothermal energy potential, reduce risk associated with geothermal energy exploration and promote sustainable development of geothermal energy as a global renewable energy landscape. Probabilistic assessment and uncertainty quantification of geothermal resources is very crucial in informed decision making and successful exploitation of reservoirs. In this studies on the Beaver Lodge field in the Red river formation, the arithmetic mean for total geothermal resources, aquifer geothermal resources and producible geothermal resources are: 4.0 ×〖10〗^18 J, 2.5 ×〖10〗^17 J and 4.8 ×〖10〗^16 J respectively. Furthermore, the relative impact plot shows total geothermal resource is sensitive to the gross thickness and volume of the reservoir, aquifer geothermal resource is sensitive to the porosity and water saturation of the reservoir and lastly, the producible geothermal reservoir is sensitive to the fluid flowrate and formation permeability.

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