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Final Conference - Vilnius, Lithuania
Final Conference - Vilnius, Lithuania
12-15 February 2008 Le Méridien Villon
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Using Decision support models to analyse the performance of deep geothermal projects
In this study we present a techno-economic models for deep geothermal projects using best practices for asset evaluation from the Oil&Gas industry, taking into account natural uncertainties and decision trees to evaluate sensitivities and different scenarios (cf. Floris and Peersmann, 2002). In this approach Fast model calculations for the techno-economic evaluation are used  to calculate the performance of the geothermal systems, investigating sensitivities of the performance due to both natural uncertainties beyond control (e.g. flow characteristics, subsurface temperatures), engineering options (bore layout and surface facilities options) and economic uncertainties (e.g. electricity price, tax regimes). 

We developed the methodology first for  the re-use of deep boreholes drilled by oil and gas industry for a Deep Borehole Heat Exchanger (DBHE). A DBHE is based on the principle of a fluid migrating through a coaxial pipe in the subsurface, heated gradually by migrating downwards in the outer pipe, whereas the inner pipe acts as the return path for the heated fluid. The energy performance of the DBHE is proportional to the temperature difference between injected and produced water multiplied by the injection rate (m3/h). Kohl et al, 2002 have presented a full numerical performance analysis of such systems. In our decision support approach we use fast models for the temperature evolution of the water in the well based on fast analytical solutions of Kujawa and Nowak (2000a, 2000b). This allows to calculate in a matter of seconds the performance and its sensitivity to uncertainties and the effect of various engineering options.

For doublet systems in deep (enhanced) geothermal systems we use analytical methodologies developed for the Soultz project (Heindiger et al., 2006). Preliminary results indicate that the performance of the system is primary sensitive to subsurface temperature, flow rates which can be sustained in the fractured rock, and the fracture area involved in the fluid flow.

Fig. 1 fastmodel components for deep Geothermal systems.

Heidinger, P., Dornstadter, J., Fabritius, A., 2006. HDR economic modelling: HDRec software. Geothermics, 35, 683-710.
Kohl T., R. Brenni., W. Eugster. [2002] System performance of a deep borehole heat exchanger. Geothermics, v. 31, 687-708.
Kujawa T., W. Nowak. [2000a] Shallow and deep vertical Geothermal heat exchangers as low temperatures sources for heat pumps. Proceedings World Geothermal Congress 2000 Kyushu, Tohoku, Japan, May 28 - June 10.
Kujawa T., W. Nowak [2000b] Thermal Calculations of geothermal heat utilizing one-well systems with both injection and production. Proceedings World Geothermal Congress 2000 Kyushu,Tohoku, Japan, May 28 - June 10.
Id: 44
Place: Le Méridien Villon
Vilnius, Lithuania
Starting date:
13-Feb-2008   11:30
Duration: 30'
Contribution type: talk
Primary Authors: Dr. VAN WEES, Jan-Diederik (TNO)
Co-Authors: Mr. BONTE, Damien (VUA)
Mr. GENTER, Albert (VUA)
Presenters: Dr. VAN WEES, Jan-Diederik
Material: slides Slides
Included in track: Oral Session - Synthesis and Best Practices, Priorities, Research needs

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