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A multicomponent geothermometer for high-temperature basalt settings

Ystroem, Lars H.; Nitschke, Fabian; Held, Sebastian; Kohl, Thomas

Abstract (englisch):
For successful geothermal reservoir exploration, accurate temperature estimation is essential. Since reservoir temperature estimation frequently involves high uncertainties when using conventional solute geothermometers, a new statistical approach is proposed. The focus of this study is on the development of a new multicomponent geothermometer tool which requires a significantly reduced data set compared to existing approaches. The method is validated against reservoir temperature measurements in the Krafla and the Reykjanes geothermal systems. A site-specific basaltic mineral set was selected as the basis to compute the equilibrium temperatures. These high-enthalpy geothermal reservoirs are located in the neo-volcanic zone of Iceland where the fluid temperatures are known to reach up to 350 °C at a depth of 2000 m. During ascent, the fluid composition is prone to changes as well as possible phase segregation due to depressurization and boiling. Therefore, to reduce the uncertainty of temperature estimations, reservoir temperature conditions are numerically reconstructed with sensitivity analyses considering pH, aluminium concentration, and steam loss. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000105778
Veröffentlicht am 18.02.2020
Originalveröffentlichung
DOI: 10.1186/s40517-020-0158-z
Scopus
Zitationen: 1
Web of Science
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Geowissenschaften (AGW)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2195-9706
KITopen-ID: 1000105778
HGF-Programm 35.14.01 (POF III, LK 01)
Effiziente Nutzung geothermisch. Energie
Erschienen in Geothermal Energy
Band 8
Heft 1
Seiten Art. Nr.: 2
Vorab online veröffentlicht am 27.01.2020
Schlagwörter multicomponent geothermometry, geochemical exploration, reservoir temperature estimation, sensitivity analysis, Krafla geothermal system, Reykjanes geothermal system, MulT_predict
Nachgewiesen in Scopus
Web of Science
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