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MulT_predict - A Multicomponent Geothermometer optimized by Sensitivity Analysis

Ystroem, Lars Helge ORCID iD icon; Nitschke, Fabian; Held, Sebastian; Kohl, Thomas

Abstract (englisch):

For a successful geothermal reservoir exploration, an in-situ temperature estimation is essential. Since geothermometric reservoir temperature estimations using conventional solute geothermometers often entail high uncertainties, a new computational approach is proposed. The goal was to obtain high-accuracy multicomponent reservoir temperature estimations by only using standard geochemical data without the need of sophisticated gas analysis. Therefore, the new numerical tool MulT_predict is introduced. MulT_predict is a multicomponent geothermometer code with integrated sensitivity analyses to back calculate on in-situ conditions. The script is based on MATLAB, which interacts with IPhreeqc. The tool was calibrated and validated against in-situ reservoir temperature measurements. Hence, reservoir conditions are numerically reconstructed by varying various sensitive parameters (e.g. pH value, steam loss, aluminum concentration etc.) to reduce the uncertainties of the reservoir temperature estimation. The new method led to statistically robust and precise reservoir temperature estimations.
At first, a set of reservoir specific minerals is selected as the base of the multicomponent geothermometry. ... mehr


Volltext §
DOI: 10.5445/IR/1000100778
Veröffentlicht am 11.12.2019
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Geowissenschaften (AGW)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Poster
Publikationsdatum 09.10.2019
Sprache Englisch
Identifikator KITopen-ID: 1000100778
HGF-Programm 35.14.01 (POF III, LK 01) Effiziente Nutzung geothermisch. Energie
Veranstaltung 7th European Geothermal Workshop (EGW 2019), Karlsruhe, Deutschland, 09.10.2019 – 10.10.2019
Schlagwörter MulT_predict, multicomponent geothermometry, sensitivity analysis, reservoir temperature estimation
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