Assessing Reservoir Uncertainty with Stochastic Facies Modeling of a Hydrothermal Medium Enthalpy Reservoir (Upper Jurassic Carbonates of the Southern German Molasse Basin)

Abstract

The up to 600 m thick Upper Jurassic carbonates (Malm) at the base of the Molasse Basin in Southern Bavaria (Germany) provide favorable conditions for geothermal energy usage. The hot aquifer (up to 165°C) has so far been explored by 46 geothermal wells reaching depths of up to 5.000 m (TVD) with an overall high success rate of 95%. Typically for carbonates the Malm is a complex and heterogeneous geothermal reservoir with considerably varying reservoir properties in exploration relevant scales. Recent studies showed that reservoir potential (yield) is highly dependent on carbonate facies and diagenetic overprint (e.g. dolomitization and karstification). Reservoir characterization on the basis of borehole data (e.g. cuttings, image logs, etc.) and the correlation to seismic data can improve the predictability of the reservoir in areas with sparse or no well data. To forecast reservoir heterogeneity on an exploration scale and to assess uncertainty, a multi scenario geocellular facies model is set. A stochastic modeling approach (MPS) is used to incorporate inputs from seismic and borehole data as well as outcrop analogues. We present a case study in the greater area of Munich (30x33 km model area) which has the highest density of deep geothermal wells in the Eastern Molasse Basin. Multi equiprobable realizations of the model offer the possibility to assess probability and uncertainty of present reservoir facies. The aim is to minimize exploration risks and in the case of a subsequent flow simulation to forecast more (realistic) production scenarios.