Within the presented case-study different disciplines worked together improving the knowledge of the developement of the North German Basin. We focus the area of a producing gas field with special respect to the analysis of seismic and sub-seismic deformation which requires a very detailed fault detection to bridge the information gap between seismic data and well data. Advanced coherency algorithms as Shaded-Relief take into account local dip and azimuth distribution of coherent energy. This leads to detect additional tectonic lineaments than could have been inferred from conventional amplitude images. Beside fracture attributes like fault density by length or connectivity, we show the attribute Fractal Dimension, which is an index for the relation of long to short fractures. Results are displayed in a map showing the areal distribution of the attribute. Correlation between FMI/FMS Log Data and FD values is linear. Using this relation, we end up with a predictive FMI-map (only based on seismic data) showing the spatial distribution of fracturation for undrilled areas. Neural Network analysis was used to classify the seismic data at reservoir depth. Plotting the results yields to a map of the seismic classes, each representing the quality of the reservoir.


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