--> --> Interpreted MOHO of West Africa from New Pre-Stack Depth Migrated (PSDM) Reflection Seismic, by Steven G. Henry, Al Danforth, and Sujata Venkatraman; #90052 (2006)

Datapages, Inc.Print this page

Interpreted MOHO of West Africa from New Pre-Stack Depth Migrated (PSDM) Reflection Seismic

Steven G. Henry1, Al Danforth2, and Sujata Venkatraman3
1 Innovative Exploration Services, LP, Houston, TX
2 Consulting Exploration Geologist, Houston, TX
3 GX Technology Corporation, Houston, TX

Results from an interpretation that determined the thickness and associated structure of the crust using deep reflection seismic profiles, in the offshore areas of Angola, Congo and Gabon, will be shown. The study utilized the CongoSpan Pre-Stack Depth Migrated (PSDM) data, which consists of long lines (300 km) that cross the continental margin to the ultra-deepwater, that was acquired to obtain images to a depth of 25 km. Deep reflectors, generally observed between 15–25 km, have been interpreted as the Moho, with refraction studies and gravity modeling supporting this interpretation.

The base of the crust consists of a series of elongated (400-750 km) highs and lows with an average relief of 2-3 km (5 km max). The mapped pattern of these structures appears to be controlled by en echelon normal faults, where large segments (~500x50 km and 5-15 km thick) of the crust have been slightly rotated. These rotations generally post-date the initial crustal rifting, all dipping to the east, and may have formed in response to mantle flow. The movements of these segments provide a viable mechanism for generating the Sag basin, which is observed to directly overly the lows generated by the eastern most rotations.

The interpretation of the base crust has not been considered an important part of perfecting the search for hydrocarbons. In this study, however, crustal thickness placed constraints on determining top basement, provided insights into basin formation and timing, improved the gravity modeling, and provided a basal boundary condition for maturation modeling.