Uncertainty Quantification of a Realistic Geothermal Reservoir

Abstract

The efficient development of a geothermal field can be largely affected by the inherent geological and physical uncertainties. In addition, uncertain operational and economic parameters will impact the profitability of a project. Systematic uncertainty quantification involving these parameters helps to determine the probability of reaching the economic targets (e.g., energy production, Net Present Value (NPV), etc.). In this study, a low-enthalpy geothermal reservoir with strong heterogeneity, located in the West Netherlands Basin, is selected as the research area. Although a detailed geological model is constructed based on various static data including seismic and log interpretation, significant uncertainties exist in the definition of the model parameters, mainly the spatial distribution of reservoir permeability and porosity. Moreover, the fluids have not been sampled in this field and can vary from brackish to highly saline brine due to the salt concentration. Also, the heat price and operational expenditures fluctuate with the market and add up to uncertainties of the physical model when an economic analysis needs to be performed. Taking all uncertain parameters into consideration, the input data set is sampled within predefined distributions or ranges using the Monte Carlo method. Ensembles of forward simulations are powered by the GPU version of the Delft Advanced Research Terra Simulator (DARTS), which has been proven to provide high computational performance with the studied model. The uncertainty of energy production and NPV with different parameters is comprehensively investigated. The observed uncertainty inside the complex subsurface system will never be unveiled without such a detailed quantification.