Proceedings, 7h European Geothermal PhD Day, 2016
University of Bari, Italy
Uncertainty related risk for a Rotliegend geothermal installation (Groningen, NE Netherlands)
Alexandros Daniilidis1*andRien Herber1
1University of Groningen, Faculty of Mathematics and Natural Sciences, Energy and Sustainability Research Institute, Geo-energy group, Groningen, The Netherlands, *
Keywords:uncertainty, 3D reservoir model, rotliegend, risk
Abstract
Geothermal exploitation is subject to several uncertainties, which can stem from the reservoir’s initial state, as well as from the geological and operational parameters. The interrelation of these uncertainty aspects can heavily affect project related risks. Therefore comprehensive risk prioritization and quantification become more difficult to achieve at an early project stage, even in settings with high data availability. This work provides a methodology for classifying and quantifying risks of a geothermal project using a discrete parameter analysis. While the numerical values are field specific, the methodology can be adjusted and applied to different locations.
In the north part of the city of Groningen (NE Netherlands) a geothermal installation is envisioned as the baseload component of a heat network, serving some 10,000 households. The considered Permian Rotliegend Slochteren (ROSL) sandstone exhibits a top reservoir depth within the license at ca. 3400m, with an average thickness of ca. 250m.
Even though3D seismic and several wells data are available, some of the critical parameters for the performance of the geothermal doublet (e.g. permeability, pressure, compartmentalization, gas saturation) remain subject to various uncertainty levels, which cannot be reduced before the exploration well is drilled. Previous studies have researched the effect of uncertainties on geothermal output. For low enthalpy fields various aspects have been considered, such as thermal rock properties (Vogt et al., 2010; Mottaghy, Pechnig, & Vogt, 2011), well positioning (Vogt et al., 2013) and more recently flow rate, reservoir characteristics and temperature, injection temperature and well spacing (Saeid, Al-Khoury, Nick, & Hicks, 2015). The impact of different parameter uncertainties on power output has also been described analytically (van Wees et al., 2012). Pressure profiles in particular are known be especially difficult to simulate(Franco & Vaccaro, 2014).Methodologically different approaches have been applied to capture uncertainty, such as Monte Carlo (Mottaghy et al., 2011; Vogt et al., 2010; Vogt et al., 2013) and parameter analysis (Poulsen, Balling, & Nielsen, 2015; Saeid et al., 2015).
Figure 1. Temperature at the producer well for the whole ensemble of simulations.
This work focuses on the risk assessment of a low-enthalpy, direct use geothermal doublet in a Rotliegend aquifer, with consideration of the uncertainties at three different levels: initial aquifer state (pressure depletion and gas saturation), reservoir (rock and fault permeability) and lastly operational (flow rate and re-injection temperature) parameters. A comprehensive discrete parameter analysis makes it possible to consider all potential parameter combinations, mapping the interaction between them through a numerical model. With this approach the amount of data and simulation time needed is reduced compared to a full Monte Carlo simulation. Furthermore, the analysis is based on a realistic reservoir geometry derived from interpretation of 3D seismic data. The results in the form of risk classificationsillustrate how a detailed analysis at the exploration phase can direct future efforts to de-risk the most influential aspects.
Acknowledgements
This research was supported by the research grant Flexiheat (Ministerie van Economische Zaken, Landbouw en
Innovatie). The authors would further like to acknowledge Nederlandse Aardolie Maatschappij BV (NAM, a Shell
operated 50-50 joint venture with ExxonMobil) for providing the 3D seismic data and Schlumberger for the academic
Petrel license. We would also like to thank colleagues Herman van Os and Panteha Bolourinejad for their insightful input.
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