Afshari Moein, M. ; Somogyvari, M. ; Valley, B. ; Jalali, M. ; Loew, S. ; Bayer, P. (2018)
Fracture network characterization using stress-based tomography.
In: Journal of Geophysical Research - Solid Earth, 123
doi: 10.1029/2018JB016438
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Information on structural features of a fracture network at early stages of Enhanced Geothermal System (EGS) development is mostly restricted to borehole images and, if available, outcrop data. However, using this information to image discontinuities in deep reservoirs is difficult. Wellbore failure data provides only some information on components of the in‐situ stress state and its heterogeneity. Our working hypothesis is that slip on natural fractures primarily controls these stress heterogeneities. Based on this, we introduce stress‐based tomography in a Bayesian framework to characterize the fracture network and its heterogeneity in potential EGS reservoirs. In this procedure, first a random initial discrete fracture network (DFN) realization is generated based on prior information about the network. The observations needed to calibrate the DFN are based on local variations of the orientation and magnitude of at least one principal stress component along boreholes. A Markov Chain Monte Carlo (MCMC) sequence is employed to update the DFN iteratively by a fracture translation within the domain. The Markov sequence compares the simulated stress profile with the observed stress profiles in the borehole, evaluates each iteration with Metropolis‐Hastings acceptance criteria and stores acceptable DFN realizations in an ensemble. Finally, this obtained ensemble is used to visualize the potential occurrence of fractures in a probability map, indicating possible fracture locations and lengths. We test this methodology to reconstruct simple synthetic and more complex outcrop‐based fracture networks and successfully image the significant fractures in the domain.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Afshari Moein, M. ; Somogyvari, M. ; Valley, B. ; Jalali, M. ; Loew, S. ; Bayer, P. |
| Art des Eintrags: | Bibliographie |
| Titel: | Fracture network characterization using stress-based tomography |
| Sprache: | Englisch |
| Publikationsjahr: | 29 Oktober 2018 |
| Verlag: | Wiley - American Geophysical Union |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Journal of Geophysical Research - Solid Earth |
| Jahrgang/Volume einer Zeitschrift: | 123 |
| DOI: | 10.1029/2018JB016438 |
| Kurzbeschreibung (Abstract): | Information on structural features of a fracture network at early stages of Enhanced Geothermal System (EGS) development is mostly restricted to borehole images and, if available, outcrop data. However, using this information to image discontinuities in deep reservoirs is difficult. Wellbore failure data provides only some information on components of the in‐situ stress state and its heterogeneity. Our working hypothesis is that slip on natural fractures primarily controls these stress heterogeneities. Based on this, we introduce stress‐based tomography in a Bayesian framework to characterize the fracture network and its heterogeneity in potential EGS reservoirs. In this procedure, first a random initial discrete fracture network (DFN) realization is generated based on prior information about the network. The observations needed to calibrate the DFN are based on local variations of the orientation and magnitude of at least one principal stress component along boreholes. A Markov Chain Monte Carlo (MCMC) sequence is employed to update the DFN iteratively by a fracture translation within the domain. The Markov sequence compares the simulated stress profile with the observed stress profiles in the borehole, evaluates each iteration with Metropolis‐Hastings acceptance criteria and stores acceptable DFN realizations in an ensemble. Finally, this obtained ensemble is used to visualize the potential occurrence of fractures in a probability map, indicating possible fracture locations and lengths. We test this methodology to reconstruct simple synthetic and more complex outcrop‐based fracture networks and successfully image the significant fractures in the domain. |
| 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: | 31 Okt 2018 12:55 |
| Letzte Änderung: | 22 Jan 2019 06:56 |
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