The Application of Seismic Attributes in Fault Detection and Direct Hydrocarbon Indicator in Tomboy Field, Western-Offshore Niger Delta Basin
Kelechi N. Ibekwe, Chinazaekpere M. Arukwe, Chibuzo V. Ahaneku, Evangeline Onuigbo, Jerry O. Omoareghan, Ademola Lanisa, Vivian O. Oguadinma
Journal of Energy Research and Reviews · pp. 9–23 · Published 9 Jun 2023
10.9734/jenrr/2023/v14i2279Abstract
Seismic attribute analysis is important in subsurface data interpretation, such as seismic interpretation, which could involve seismic stratigraphic and structural interpretation. This interpretation is often hampered by seismic resolution and, sometimes, human inability to identify a subtle feature on the seismic. These factors have frequently led to the poor seismic interpretation of geologic features. Thus, an integral approach to studying structural patterns and hydrocarbon bearing zones using seismic attributes was carried out on the Tomboy field using 3D seismic data covering approximately 56 km2 of the western belt of the Niger Delta. The seismic volume underwent post-stack processing, which enhanced seismic discontinuities. A deep steering volume was first created, and several dip filters were applied to enhance faults in the study area. After that, curvature and similarity attributes were calculated on the dip-steered and fault-enhanced volume. These calculations show detailed geometry of the faults and zones of subtle lineaments. Six faults (F1, F2, F3, F4, F5 and F6) were identified and mapped. These faults range from antithetic to crest growth faults. Two major growth faults (F5 and F6) were revealed to dip in the northeast to southwest directions. A near-extensive crest fault (F4) appeared beneath the major faults. Although several minor fractures were displayed in the southern and central portions of the crest fault of the dipping seismic data, the southwest (F4) and growth fault, F6, are responsible for holding the hydrocarbon found within the identified closures. Using attributes on the seismic data increased confidence in mapping and interpreting structural features. Furthermore, energy attributes were used as Direct Hydrocarbon Indicators (DHI) to visualize viable areas within the study, which allows a more robust interpretation. Time slices were taken in regions of flat and bright spots. The spectral decomposition attribute was run on these slices to display areas of high amplitude reflection typical of hydrocarbon-bearing regions trapped mainly by regional to sub-regional growth faults. The surface attribute calculated on the generated surface shows that the field is predominantly controlled by faults serving as traps for hydrocarbon.
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