The Ministry of Blue Economy and Fisheries and the Zanzibar Petroleum Regulatory Authority (ZPRA) have announced the Zanzibar 1st Licensing Round to promote oil and gas opportunities in the region. SLB has partnered with the ZPRA to be the exclusive provider of more than 10,000 linear km of 2D-seismic data, covering the eight offshore blocks on offer. This represents a unique opportunity to be one of the first to explore a largely untapped frontier region with significant hydrocarbon potential.

The offshore Pemba-Zanzibar sub-basin is located along the East African coast. There is significant evidence of a functioning petroleum system in the form of numerous oil seeps, as well as several exploration wells with hydrocarbon shows. Several different play types ranging in age, and with promising oil and gas potential, have been observed in the basin.

The eight bid round blocks range in size from 2,846 km² to 5,666 km², and are located in water depths ranging from 300 m to 2,500 m.

The licensing round application will be open from March 20, 2024 until September 16, 2024. The application proposals will be evaluated over the following months with the award announcements expected in November 2024.

The SLB prospectivity assessment of the Pemba-Zanzibar sub-basin has revealed numerous play types in the area, including turbidite fans and channels of early-to-late Cretaceous and Tertiary age. Source rocks appear to be Jurassic to Cretaceous in age, making these plays analogous to discoveries made in offshore Tanzania.

Eocene aged source rocks found within the northwest-southeast tending syncline are expected to be within maturity window, similar to those found in Lamu Basin, Kenya. Finally, basement reactivation in the region has created numerous four-way structural closures, resulting in improved trapping potential. SLB's available 2D-reprocessed seismic data and angle stacks are well suited to help delineate stratigraphic traps and identify AVO supported targets, while depth migrated products allow for further de-risking of traps by reducing structural uncertainty.

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