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Dissertation zugänglich unter
URN: urn:nbn:de:gbv:18-73458
URL: http://ediss.sub.uni-hamburg.de/volltexte/2015/7345/


Microtremor localisation based on cross-correlation stacking

Microtremor Lokalisierung basierend auf Kreuzkorrelations Stacking

Behzadi, Mehrnoosh

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 Dokument 1.pdf (17.927 KB) 


Freie Schlagwörter (Deutsch): Seismische Prospektion , Tremor , Modellierung
Basisklassifikation: 38.70
Institut: Geowissenschaften
DDC-Sachgruppe: Geowissenschaften
Dokumentart: Dissertation
Hauptberichter: Gajewski, Dirk (Prof. Dr.)
Sprache: Deutsch
Tag der mündlichen Prüfung: 01.04.2015
Erstellungsjahr: 2015
Publikationsdatum: 05.06.2015
Kurzfassung auf Englisch: Passive seismic methods are of high interest to the petroleum industry. Reservoir monitoring, hydro-fracture mapping and imaging enhanced oil recovery are only a few applications of passive seismic methods in exploration seismics. Passive seismic methods reduce the number of unnecessary wells and contribute to a cleaner and environmentally friendlier exploration process. In this case exploration teams can identify reservoir prospects easier, reduce the number of holes drilled, reduce drilling costs, and cut exploration time. This leads to economic and environmental benefits: a reliable, affordable environmentally sustainable technology in the oil and gas exploration is one of the major challenges facing society. In this study, a new passive seismic method based on cross-correlation and stacking is introduced to localise the elastic emissions. The new method is applied to synthetic and field data, in order to highlight some of its advantages and disadvantages. The method does not require picking of events and uses all recorded channels simultaneously, which allows detecting even very small events. The method has similarities to the diffraction stacking method and differs particularly in the way the time axis is collapsed in the imaging process which is performed by zero lag cross-correlation. The maximum value of the image obtained by this method provides the source location. The localisation results obtained by cross-correlation stacking demonstrate the new method’s robustness and its potential for real time
monitoring of the subsurface.

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