ARTICLE

Fault detection using dip-steered multi-trace similarity extraction techniques: Case study using offshore Niger Delta 3D seismic data

BABANGIDA JIBRIN1 WASIU RAJI2
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1 School of Geography, Earth and Environmental Sciences, University of Birmingham, West Midlands B15 2TT, U.K.,
2 Department of Geophysics, Stanford University, Mitchell Building, Stanford, California, 94305-2215, U.S.A.,
JSE 2014, 23(1), 19–30;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Jibrin, B. and Raji, W., 2014. Fault detection using dip-steered multi-trace similarity extraction techniques: Case study using offshore Niger Delta 3D seismic data. Journal of Seismic Exploration, 23: 19-30. 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.

Keywords
Niger Delta
3D seismic data
dip-steering
steering volumes
multi-trace similarity
fault detection
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing