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Combining numerical modeling with geostatistical analysis for an improved basin analysis

Rühaak, W. ; Bär, K. ; Sass, I. (2015)
Combining numerical modeling with geostatistical analysis for an improved basin analysis.
European Geothermal Workshop 2015. Strasbourg (19.-20.10.2015)
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Subsurface temperature is one of the key parameters in the analysis of a sedimentary basin, for instance with respect to geothermal or oil and gas exploration. The estimation of the reservoir temperature is of high importance and usually done either by interpolation of temperature data or numerical modeling. However, temperature measurements of depths larger than a few hundred meters are generally very sparse. A pure interpolation of such sparse data always involves big uncertainties and usually neglects knowledge of the reservoir geometry or reservoir properties. Kriging with trend does allow including secondary data to improve the interpolation of the primary one. Using this approach temperature measurements of depths larger than 1,000 m of the federal state of Hessen/Germany have been interpolated in 3D. A conductive numerical 3D temperature model was used as secondary information. This way the interpolation result reflects also the geological structure. As a result the quality of the estimation improves considerably.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2015
Autor(en): Rühaak, W. ; Bär, K. ; Sass, I.
Art des Eintrags: Bibliographie
Titel: Combining numerical modeling with geostatistical analysis for an improved basin analysis
Sprache: Englisch
Publikationsjahr: 6 November 2015
Veranstaltungstitel: European Geothermal Workshop 2015
Veranstaltungsort: Strasbourg
Veranstaltungsdatum: 19.-20.10.2015
Kurzbeschreibung (Abstract):

Subsurface temperature is one of the key parameters in the analysis of a sedimentary basin, for instance with respect to geothermal or oil and gas exploration. The estimation of the reservoir temperature is of high importance and usually done either by interpolation of temperature data or numerical modeling. However, temperature measurements of depths larger than a few hundred meters are generally very sparse. A pure interpolation of such sparse data always involves big uncertainties and usually neglects knowledge of the reservoir geometry or reservoir properties. Kriging with trend does allow including secondary data to improve the interpolation of the primary one. Using this approach temperature measurements of depths larger than 1,000 m of the federal state of Hessen/Germany have been interpolated in 3D. A conductive numerical 3D temperature model was used as secondary information. This way the interpolation result reflects also the geological structure. As a result the quality of the estimation improves considerably.

Fachbereich(e)/-gebiet(e): 11 Fachbereich Material- und Geowissenschaften
11 Fachbereich Material- und Geowissenschaften > Geowissenschaften
11 Fachbereich Material- und Geowissenschaften > Geowissenschaften > Fachgebiet Angewandte Geothermie
Hinterlegungsdatum: 06 Nov 2015 15:46
Letzte Änderung: 03 Jun 2018 21:26
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