Strategies for the Interpretation of the Malm in the Bavarian Molasse Basin based on 3D Seismic Data – Comparison with Outcrop Analogues
Research output: Thesis › Master's Thesis
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Abstract
Seismic data, acquired west of Munich in the Bavarian Molasse Basin, were used for the investigation of the Upper Malm. This is of interest as a potential target for hydrocarbon accumulations and geothermal projects. The Upper Malm is characterized by deeper water carbonate and sponge reef mounds, alternating with marly basins. The aim of the study was to identify seismic attributes which allow a differentiation between those two facies types. Further, a workflow using most suitable attributes was established for future exploration in similar geological settings. As a first step the seismic data was noise reduced and spectrally enhanced. A colored inversion was performed to support and improve the seismic horizon interpretation. 3D auto-tracking was used for interpretation of top and base Upper Malm. The results obtained from tracking of different seismic features/data, like peak/trough or zero-crossing in amplitude seismic, or acoustic impedance, were compared. Finally, several seismic attributes were evaluated and a combination of envelope and variance came out to give best results to differentiate between reef mound and basin facies. Further, the potential influence of faults on reef mound growth was investigated, indicating no correlation. The Upper Malm was subject to aerial exposure and erosion in Cretaceous and Paleogene times. In this study, a method for detecting karst features in seismic data was developed and compared to literature analogues from the Franconian and Swabian Jura. Karstification can be detected by comparing the RMS amplitude of time windows below the top of Malm.
Details
Translated title of the contribution | Strategien für die Interpretation des Malms im bayrischen Molassebecken auf Basis 3D seismischer Daten – Vergleich mit Aufschlussanalogen |
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Original language | English |
Qualification | Dipl.-Ing. |
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Award date | 30 Jun 2017 |
Publication status | Published - 2017 |