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Personen: Sell, Kathleen (Autor) 
Saenger, Erik H. (Autor) 
Falenty, Andrzej (Autor) 
Chaouachi, Marwen (Autor) 
Haberthür, David (Autor) 
Enzmann, Frieder (Autor) 
Kuhs, Werner F. (Autor) 
Kersten, Michael (Autor) 
  
Titel: On the path to the digital rock physics of gas hydrate-bearing sediments : processing of in situ synchrotron-tomography data
  
Quelle: Solid earth. Bd. 7. H. 4. Göttingen : Copernicus Publ. S. 1243 - 1258
Erscheinungsjahr:    2016
ISBN / ISSN: 1869-9529 ; 1869-9510
URL der Originalveröffentlichung doi:10.5194/se-7-1243-2016
  
Dokumentart:
Zeitschriftenaufsatz Zeitschriftenaufsatz
Sprache: Englisch
Open Access: OpenAccess
Person der Universität:    Enzmann, Frieder  In UnivIS suchen ; Kersten, Michael  In UnivIS suchen 
Einrichtung: Institut für Geowissenschaften
DDC-Sachgruppe:    Geowissenschaften
ID: 55528  Universitätsbibliothek Mainz
Hinweis:
Informationen zu den Nutzungsrechten unserer Inhalte Informationen zu den Nutzungsrechten unserer Inhalte
Abstract: To date, very little is known about the distribution of natural gas hydrates in sedimentary matrices and its influence on the seismic properties of the host rock, in particular at low hydrate concentration. Digital rock physics offers a unique approach to this issue yet requires good quality, high-resolution 3-D representations for the accurate modeling of petrophysical and transport properties. Although such models are readily available via in situ synchrotron radiation X-ray tomography, the analysis of such data asks for complex workflows and high computational power to maintain valuable results. Here, we present a best-practice procedure complementing data from Chaouachi et al. (2015) with data post-processing, including image enhancement and segmentation as well as exemplary numerical simulations of an acoustic wave propagation in 3-D using the derived results. A combination of the tomography and 3-D modeling opens a path to a more reliable deduction of properties of gas hydrate-bearing sediments without a reliance on idealized and frequently imprecise models.
   
  
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