This project was devoted to the extraction of more quantitative information by integrating the 3D seismic data with the wireline logs and cores from 10 exploration wells drilled through the Tay system, Gannet South, Central North Sea and by introducing the innovative body and seismic trace shape analysis to the interpretation process. The idea of analysing a seismic data based on variation of seismic trace shapes comes from the assumption that changes in lithology, rock properties and fluid content should affect seismic response in not only amplitude but the whole shape of the trace. This project utilizes the pattern recognition capability of the neural network technology to classify the seismic traces based on their shapes. Both supervised and unsupervised classifications were applied on the Gannet South seismic dataset. Maps produced have revealed subtle geological features only expressed in the shape of the seismic trace and thus substantially enhanced the understanding of the sand geometries of the turbidite system and the structural development and evolution of the basin, provided clues to the timing, nature and extent of factors controlling the sediment transport pathways in the area, and helped in the discovery of hydrocarbon pockets previously gone unnoticed. A set of body shape parameters that would enable a distinctive description of different turbidite sand bodies were established. No single parameter is enough to uniquely describe all shapes but a combination of parameters could be used. The study also showed that the normalised polar representation of any shape can be significant for its recognition as well as for matching purposes. Unfortunately, the body shape analysis was hampered by the lack of accepted general turbidite models in the literature as well as inaccessibility to subsurface seismic datasets on which body shape analysis could have been applied in order to use the results as a database.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:640279 |
| Date | January 2003 |
| Creators | Al-Aufi, Yousuf Muhammed Rashid |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/10965 |
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