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A multi-stage 3-D stress field modelling approach exemplified in the Bavarian Molasse Basin

  • The knowledge of the contemporary in situ stress state is a key issue for safe and sustainable subsurface engineering. However, information on the orientation and magnitudes of the stress state is limited and often not available for the areas of interest. Therefore 3-D geomechanical-numerical modelling is used to estimate the in situ stress state and the distance of faults from failure for application in subsurface engineering. The main challenge in this approach is to bridge the gap in scale between the widely scattered data used for calibration of the model and the high resolution in the target area required for the application. We present a multi-stage 3-D geomechanical-numerical approach which provides a state-of-the-art model of the stress field for a reservoir-scale area from widely scattered data records. Therefore, we first use a large-scale regional model which is calibrated by available stress data and provides the full 3-D stress tensor at discrete points in the entire model volume. The modelled stress state is usedThe knowledge of the contemporary in situ stress state is a key issue for safe and sustainable subsurface engineering. However, information on the orientation and magnitudes of the stress state is limited and often not available for the areas of interest. Therefore 3-D geomechanical-numerical modelling is used to estimate the in situ stress state and the distance of faults from failure for application in subsurface engineering. The main challenge in this approach is to bridge the gap in scale between the widely scattered data used for calibration of the model and the high resolution in the target area required for the application. We present a multi-stage 3-D geomechanical-numerical approach which provides a state-of-the-art model of the stress field for a reservoir-scale area from widely scattered data records. Therefore, we first use a large-scale regional model which is calibrated by available stress data and provides the full 3-D stress tensor at discrete points in the entire model volume. The modelled stress state is used subsequently for the calibration of a smaller-scale model located within the large-scale model in an area without any observed stress data records. We exemplify this approach with two-stages for the area around Munich in the German Molasse Basin. As an example of application, we estimate the scalar values for slip tendency and fracture potential from the model results as measures for the criticality of fault reactivation in the reservoir-scale model. The modelling results show that variations due to uncertainties in the input data are mainly introduced by the uncertain material properties and missing S-Hmax magnitude estimates needed for a more reliable model calibration. This leads to the conclusion that at this stage the model's reliability depends only on the amount and quality of available stress information rather than on the modelling technique itself or on local details of the model geometry. Any improvements in modelling and increases in model reliability can only be achieved using more high-quality data for calibration.zeige mehrzeige weniger

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Verfasserangaben:Moritz O. ZieglerORCiDGND, Oliver HeidbachORCiDGND, John Reinecker, Anna M. Przybycin, Magdalena Scheck-WenderothORCiDGND
URN:urn:nbn:de:kobv:517-opus4-409806
DOI:https://doi.org/10.25932/publishup-40980
ISSN:1866-8372
Titel des übergeordneten Werks (Englisch):Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
Schriftenreihe (Bandnummer):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (556)
Publikationstyp:Postprint
Sprache:Englisch
Datum der Erstveröffentlichung:29.01.2019
Erscheinungsjahr:2016
Veröffentlichende Institution:Universität Potsdam
Datum der Freischaltung:29.01.2019
Freies Schlagwort / Tag:alpine foreland; fault reactivation; geomechanical model; geothermal-reservoirs; in-situ stress; induced seismicity; km depth; map project; orientation; system
Ausgabe:556
Seitenanzahl:18
Quelle:Solid Earth 7 (2016) 5, S. 1365–1382 DOI: 10.5194/se-7-1365-2016
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
Publikationsweg:Open Access
Fördermittelquelle:Copernicus
Lizenz (Deutsch):License LogoCC-BY - Namensnennung 4.0 International
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