Seismic attribute-based fault detection and structural mapping in 3D seismic data for hydrocarbon exploration

Accurate identification of subsurface fault systems is critical for hydrocarbon exploration and reservoir management. Fault structures influence hydrocarbon migration, reservoir compartmentalization, and structural trap formation. Traditional seismic interpretation techniques often rely on manual analysis of seismic sections, which may overlook subtle fault features within complex geological settings. This study proposes an attribute-based seismic interpretation approach for improved fault detection and structural mapping in 3D seismic datasets. Several seismic attributes, including coherence, variance, and curvature, are analyzed to enhance the visibility of fault structures within the seismic volume. Structural interpretation is performed to map fault networks and evaluate their impact on reservoir geometry and hydrocarbon trapping mechanisms. Results demonstrate that seismic attribute analysis significantly improves the detection of small-scale faults and structural discontinuities that are not clearly visible in conventional seismic sections. The proposed workflow enhances the accuracy of structural interpretation and supports more reliable hydrocarbon exploration strategies.