FAULT DETECTION USING DIP-STEERED MULTI-TRACE SIMILARITY EXTRACTION TECHNIQUES: CASE STUDY USING OFFSHORE NIGER DELTA 3D SEISMIC DATA

Techniques for detecting faults have been applied to a 3D seismic data acquired in the shallow offshore Niger Delta. A volume containing the dip and azimuth of the traces was first computed directly from the data. The data was enhanced by applying filters to compute two structurally-improved volumes containing localized and sub-regional seismic dips respectively. Multi-trace similarity was then computed using the seismic reflection and sub-regional dip data as input. The data highlighted discrete zones of dip and similarity anomalies representing listric normal and counter regional faults with improved visibility of wall-rock volumes. The case study demonstrates the potential benefits of applying dip-steering techniques for the enhanced detection of faults and improved visibility of wall-rock volumes next to the faults.