8.11.2007ENGINE Leiden Combining Areal Underground and Infrastructure Data to Minimize Exploration and Economic Risks Thomas Kohl, GEOWATT AG Clément Baujard,

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Presentation transcript:

ENGINE Leiden Combining Areal Underground and Infrastructure Data to Minimize Exploration and Economic Risks Thomas Kohl, GEOWATT AG Clément Baujard, GEOWATT AG Example of West Switzerland  Geothermal Productivity  Economic Analysis  Societal Needs Engine: ENhanced Geothermal Innovative Network for Europe

ENGINE Leiden Investigation of National Swiss Geothermal Ressources

ENGINE Leiden Geothermal Potential Heat in Place  c P specific heat capacity of rock [J m ‑ 3 K ‑ 1 ], V Volume of resource [m 3 ], T prod Temperature of produced fluid [°C] T reinj Temperature of re-injected fluid [°C]. Transient Production (  c P ) f specific heat capacity of fluids [J m ‑ 3 K ‑ 1 ] Q produced flow rate [m 3 s ‑ 1 ].

ENGINE Leiden Utilization Scenario Doublet System: Negligible temperature drawdown over  t=30 yr Analytic solution (Gringarten, 1978):  Necessary surface area  Sustainable flow rate  Reservoir geometry  Utilizable heat energy = f(Tr, T, V, …) in individual reservoir zone  Dynamic approach: reservoir depletion Distance  x Transmissivity

ENGINE Leiden Resource Analysis: Workflow Data research  Geological data  Well data  Geophysical data (seismic profiles…)  Hydrogeological data (pumping tests, chemical…) 3D Geological model 3D Temperature model  Thermal properties from well data  Calibration of temperature on well data Extraction of temperature on aquifers Computation and mapping of geothermal potential for identified aquifer Identification of zones of great potential, cross-checking with surface data

ENGINE Leiden 3D Temperature field in domains  Conversion of the geological model into FE  Attribution of petrophysical data to units  Simulation of the temperature using FRACTure  Parameters: Surface temperature, geologic model, Thermal conductivity, Basal heat flow distribution

ENGINE Leiden Developing Thermal Calibration Model

ENGINE Leiden Thermal Calibration Model Temperature along Top 500m Crystalline

ENGINE Leiden Hydrogeological Parameters Crystalline Basement  Top 500m Depth dependencyBimodal Distribution

ENGINE Leiden Identifying aquifers AquiferHydraulic conductivity Thickness Upper Marine Molasse ms m Upper Muschelkalk ms -1 to ms -1 Altered Crystalline ms -1 to ms -1

ENGINE Leiden Potential Geothermal Energy West Switzerland (Upper Muschelkalk) Key Parameters:  Geometry of the aquifer  Temperature at depth  Hydraulic conductivity

ENGINE Leiden Economic modeling Concepts Parameters:  Heat production or electricity production Option 1: Pure Heat Production Option 2: Pure Electricity Production Option 3: Coupled Electricity & Heat Production  Depth of the borehole  Drilling costs Fixed at 1500€/m or 2200€/m Increasing with depth  Conversion efficiency: Increasing with depth  Operational efforts: pump energy needs  Market selling prices and buying prices of heat and electricity  Annuity of loans  …

ENGINE Leiden Economic modeling Results Typical results of a parameter study (not definitive) Electricity costs CHF/kWh

ENGINE Leiden Conclusion Resource analyses are a powerful tool to quantify and map the geothermal potential of a region  It allows to identify the most interesting regions  The geothermal potential can be easily integrated in GIS Planning tool for local authorities  The risk can be expressed in a probable cost model  The energy demand could be covered from geothermal, However: under realistic premises only to a small amount Don't overestimate the geothermal potential!