8.11.2007ENGINE Leiden Combining Areal Underground and Infrastructure Data to Minimize Exploration...
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Transcript of 8.11.2007ENGINE Leiden Combining Areal Underground and Infrastructure Data to Minimize Exploration...
8.11.2007 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 SwitzerlandGeothermal ProductivityEconomic AnalysisSocietal Needs
Engine: ENhanced Geothermal Innovative Network for Europe
8.11.2007 ENGINE Leiden
Investigation of National Swiss Geothermal Ressources
8.11.2007 ENGINE Leiden
Geothermal Potential
Heat in Place
cP specific heat capacity of rock [J m‑3 K‑1],
V Volume of resource [m3],
Tprod Temperature of produced fluid [°C]
Treinj Temperature of re-injected fluid [°C].
Transient Production
(cP)f specific heat capacity of fluids [J m‑3 K‑1]
Q produced flow rate [m3 s‑1].
)( reinjprodPHIP TTVcE
t
reinjprodfP
t
thut
dtTTQc
dtpE
)()(
8.11.2007 ENGINE Leiden
Utilization Scenario
Doublet System:Negligible temperature drawdown
over t=30 yrAnalytic 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
21 /3ln
4
wi
bi rztcQ
PTrQ
8.11.2007 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
8.11.2007 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
8.11.2007 ENGINE Leiden
Developing Thermal Calibration Model
-10000
-5000
0
640000
650000
660000
670000
680000
690000
700000
240000
250000
260000
270000
280000
Temp [°C]4003753503253002752502252001751501251007550250
Weiach
Benken
Lindau
Riniken
Leuggern
8.11.2007 ENGINE Leiden
Thermal Calibration Model
Temperature along Top 500m Crystalline
-10000
-5000
0
640000
650000
660000
670000
680000
690000
700000
240000
250000
260000
270000
280000
Temp. [°C]: 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210
8.11.2007 ENGINE Leiden
Hydrogeological Parameters
Crystalline Basement Top 500m
Depth dependency Bimodal Distribution
0
5
10
15
20
25
Hydraulische Leitfähigkeit [Log (K)]
An
zah
l [-]
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Anzahl
Kumulativ
Verteilung 1
Verteilung 2
8.11.2007 ENGINE Leiden
Identifying aquifers
Aquifer Hydraulic conductivity
Thickness
Upper Marine Molasse
2.10-7 ms-1 50-700m
Upper Muschelkalk
1.10-7 ms-1
to 1.10-4 ms-1
<70m>
Altered Crystalline
1.10-8 ms-1
to 1 10-6 ms-1
<500m>
8.11.2007 ENGINE Leiden
Potential Geothermal Energy West Switzerland (Upper Muschelkalk)
Key Parameters: Geometry of the aquifer Temperature at depth Hydraulic conductivity
8.11.2007 ENGINE Leiden
Economic modelingConcepts
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 …
8.11.2007 ENGINE Leiden
Economic modelingResults
Typical results of a parameter study (not definitive)
Electricity costs CHF/kWh
8.11.2007 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!