DOI: https://doi.org/10.36347/sjet.2026.v14i03.004

Pages: 153-160

The Niger Delta Basin represents one of Africa's most prolific hydrocarbon provinces, with complex structural and stratigraphic frameworks controlling petroleum accumulation. This study presents a geologic interpretation of seismic data from an X-field located in the southern Niger Delta, Nigeria, aiming to delineate structural features, identify hydrocarbon indicators, and establish the relationship between interpreted seismic signatures and the regional geological setting. Four inlines (5908–5932) were interpreted manually using basic seismic interpretation techniques, involving fault picking along vertical sections and horizon identification on laterally continuous reflections. The seismic sections revealed multiple fault systems comprising major, minor, and growth faults distributed across interpreted horizons (H0–H4). The results demonstrate that the area is structurally deformed, with fault density varying significantly across horizons, from zones with no faulting (H0–H1) to highly faulted intervals containing up to seven major faults (H1–H2 on inline 5916). Growth faults were identified, confirming the extensional tectonic regime characteristic of the Niger Delta's depobelts. Direct hydrocarbon indicators (DHIs), including bright spots and dim spots representing amplitude anomalies, were observed across all interpreted sections, suggesting possible hydrocarbon accumulations within fault-bounded traps. The interpreted horizons correspond to the three principal stratigraphic units of the Niger Delta: the Benin Formation (continental sands), Agbada Formation (paralic reservoir sequence), and Akata Formation (marine source rocks). Hydrocarbon potential appears concentrated within the Agbada Formation equivalents, where structural traps formed by growth fault-related rollover anticlines provide favorable accumulation conditions. This study demonstrates that manual seismic interpretation remains valuable for preliminary basin analysis, successfully identifying stru