Forecasting Low Enthalpy Geothermal Heat Extraction from Saline Aquifers Under Uncertainty

Abstract

Abstract District heating can be decarbonized by using low enthalpy geothermal heat. In this case study, water from a deep saline aquifer with a temperature of 90-110 °C is produced, heat extracted for district heating and the cold water re-injected into the aquifer. There are substantial subsurface uncertainties in the structure as well as porosity and permeability distribution of the saline aquifer that need to be addressed to optimize heat extraction under uncertainty. The deep saline aquifer characterization is based on 3D seismic and a limited number of wells. Hence, substantial uncertainty exists in porosity/permeability distribution and dynamic and thermal properties. To address the uncertainty, different geological concepts need to be evaluated and parameter ranges for geostatistical and poro-perm relationships need to be used. To cover the uncertainty range, we constructed 600 geological models all honoring the limited existing data. However, dynamically simulating all the geological models including the ranges for the thermal properties is usually too costly. We utilize a geo-screening workflow, which selects a subset of representative models based on dynamic (proxy) response, the workflow aims at keeping the same variability of the subset as for the full ensemble. This is achieved via a dimensionality reduction of the problem, by clustering of the models in multi-dimensional space. The centroids of these clusters are selected as representative models used for full-physics simulations to forecast heat extraction under uncertainty. To define a consistent method for selecting a representative subset of geologic realization we simulated the full ensemble and compared it to (i) subsets of different clustering approaches using static (heat in-place) and dynamic (tracer rate & flux pattern) proxy responses and (ii) subset sizes. The results of the workflow show that the tracer rate is a better metric for the selection of the cluster centroids compared with flux-pattern and in particular heat in place. For this case 20-40 geological realizations were sufficient to cover the uncertainty space for forecasting low enthalpy heat extraction. The suggested workflow allows for addressing the subsurface uncertainty in static and dynamic parameters making use of streamline simulation to reduce simulation costs. The resulting model ensemble can be used for field development planning of low enthalpy heat extraction under uncertainty.