Comparison of Stochastic Based Volumetric Heat in Place Methods for Predicting Power (Electricity) Generation Potential of Liquid-Dominated Geothermal Systems

Abstract

This paper focuses on review and comparison of three probability based volumetric heat in place methods which can be used for predicting a power (electricity) generation potential of a liquid-dominated geothermal system. These are the USGS (the United States Geologic Survey) method proposed in 1970, the MIT (Massachusetts Institute of Technology) proposed in 2006 and the Garg-Combs methods proposed in 2015. By considering synthetic and real geothermal field data from Turkey, all three methods were evaluated and compared by using both the Monte Carlo Simulation (MC) and the Analytic Uncertainty Propagation (AUP) Methods. The uncertainty in power generation potential estimation due to uncertainties in input parameters such as areal extent, thickness, resource temperature, porosity, density, isobaric, volumetric specific heat capacity of reservoir rock, etc., is assessed by using the statistical markers of P10 (proved), P50 (probable) and P90 (possible). One of the contributions of the paper is that new AUP equations for each of the three methods have been derived and presented. The results predicted by the new AUP equations derived in this work show excellent agreement with the results predicted by the MC method, yet do not require extensive MC simulations or commercial software use. Suggestions were made about the proper usage of USGS and MIT methods that usually give overestimated results by the usage of arbitrarily chosen reservoir input parameters. All three methods were applied to 25 geothermal fields of Turkey, which are amenable to power generation, by MCM and AUPM approximations. It is shown that the Garg and Combs (2015) method without any usage of arbitrary values and considering the installed power conversion system and thermodynamic properties of the produced water or the secondary fluid of the power conversion system appears to be the most appropriate method to eliminate the subjectivity in selecting the reference (or abandonment) temperature and conversion efficiency and hence to predict the power generation of a geothermal field or country more realistically.