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Multi-Directional and Multi-Scale Fault Detection Using the Random Wavelet Transform

Al-Dossary, Saleh *1; Al-Garni, Khalid M.1
(1) Saudi Aramco, Dhahran, Saudi Arabia.

We introduce a new and effective method of detecting discontinuities or “edges” such as faults in seismic data. This new algorithm detects faults based on both the directional derivatives and on the redundant wavelet transforms (RWT). Directional derivatives can detect azimuthally-varying fault trends and the RWT can detect these fault trends at different scales. Combining these two powerful techniques results into a new seismic attribute that allows easier mapping of faults whose trends are perpendicular to the directional derivative operator and faults which are small and below the imaging range of seismic data. We illustrate the value of our new method through the application to real datasets from Saudi Arabian fields where we witness an increased visibility of faults of different sizes and of different azimuth directions.


AAPG Search and Discovery Article #90141©2012, GEO-2012, 10th Middle East Geosciences Conference and Exhibition, 4-7 March 2012, Manama, Bahrain