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Combining numerical modeling with geostatistical analysis for an improved reservoir exploration

Rühaak, W. and Bär, K. and Sass, I. (2014):
Combining numerical modeling with geostatistical analysis for an improved reservoir exploration.
In: Energy Procedia, Elsevier, pp. 315-322, 59, [Online-Edition: http://www.sciencedirect.com/science/article/pii/S1876610214...],
[Article]

Abstract

Subsurface temperature is one of the key parameters in geothermal 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.

Item Type: Article
Erschienen: 2014
Creators: Rühaak, W. and Bär, K. and Sass, I.
Title: Combining numerical modeling with geostatistical analysis for an improved reservoir exploration
Language: English
Abstract:

Subsurface temperature is one of the key parameters in geothermal 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.

Journal or Publication Title: Energy Procedia
Volume: 59
Publisher: Elsevier
Divisions: 11 Department of Materials and Earth Sciences
11 Department of Materials and Earth Sciences > Earth Science
11 Department of Materials and Earth Sciences > Earth Science > Geothermal Science and Technology
Date Deposited: 11 Nov 2015 18:14
Official URL: http://www.sciencedirect.com/science/article/pii/S1876610214...
Additional Information:

European Geosciences Union General Assembly 2014, EGU Division Energy, Resources & the Environment (ERE)

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Alternative keywords:
Alternative keywordsLanguage
Subsurface temperaturesEnglish
Kriging with External DriftEnglish
Finite Element ModelingEnglish
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