| Abstract |
Pursuit and use of geothermal energy in the Netherlands is developing steadily. However, in order to make sound decisions, investors and insurers are requesting the probability of success of each planned geothermal project. A methodological appraisal system was developed in order to achieve a meaningful probability of success of the expected flow rate and thermal capacity. The appraisal system follows a methodological workflow integrating the errors in raw data, uncertainties in the geological interpretation, and in projected design of the geothermal system. The designed appraisal system is capable of working with all data available within sedimentary basins and comprises three major steps. The first two steps comprise Monte Carlo simulations. In the first simulation every calculation of the petrophysical analysis, within predefined uncertainty or error bands, is redone to determine the uncertainties for all significant parameters. A sensitivity analysis has revealed that within this step a crucial parameter is the uncertainty in the derived porosity-permeability relationship. This first step will be applied to every single well and the resulting probability distributions of permeability, net-to-gross ratio and temperature are combined with the results of the seismic interpretation and spatially extrapolated to the proposed subsurface locations of the planned geothermal wells. A second Monte Carlo simulation provides the probability distributions of the desired variables: net reservoir thickness, reservoir temperature, reservoir depth, and transmissivity. The third and final step delivers the information investors and insurers are actually interested in: the probability distributions of the feasible thermal capacity and the feasible flow rate, which are calculated by running the results of the second step through a simple analytical reservoir model. This reservoir model includes reservoir properties, properties of formation water, and well design. One parameter with significant influence on the feasible flow/installed thermal capacity and thus economics of the project is the coefficient of performance (COP). The COP can be adjusted within the model to meet client requirements. Although it is realized that this model may need some refinement, in particular when it comes to spatial extrapolation of well data, it is believed that this is the best practice at the moment, yielding a solution that covers the most significant uncertainties for geothermal reservoir feasibility studies in sedimentary rock. |