Despite being penetrated by over 100 wells, and more than a century of studies, the in-place and recoverable volumes of oil resources within Nigeria's bituminous belt are still inconclusive. Noteworthy is the misleading appropriation of "reserves" to the deposit. While there is an obvious motivation to improve the current situation, credibility requires that such efforts are premised on a combination of reliable dataset and robust method of study.
This article is an attempt at reconciling and improving current estimates of the hydrocarbon potentials of the Nigerian bituminous belt. It reviews and integrates numerous datasets on the belt. Reasonable assumptions, empirical correlations and analogue information are used to mitigate identified data gaps while recognising uncertainties. With estimated input data and associated uncertainties, deterministic and probabilistic techniques are employed for robust volumetrics. Unlike previous studies, we consider solution gas.
Using performances of some proven exploitation technologies in provinces of comparable reservoir and fluid characteristics as Nigeria's, we make reasonable estimates of recovery factors, and establish cumulative distribution curves for recoverable (not reserves) volumes of discovered bitumen, heavy oil and oil shale deposits, including the dissolved gas content.
From the analyses, we estimate 71, 207 and 415 billion barrels as the P90, P50 and P10 stock-tank oil in-place volumes, respectively. Corresponding solution-gas quantities are 1.4, 5.0, and 13.6 Tscf, respectively. Compared to current official record of about 43 billion barrels, which does not account for the field-proven solution gas, potentials of Nigeria's bituminous belt may be significantly underestimated at present. Although the volumetric ranges in this study reflect the relative magnitude and impact of uncertainties, sensitivity analysis indicates that reservoir extent and thickness as well as solution gas-oil ratio are the main uncertainties. Consequently, a key objective of future appraisal programs should be to narrow the current range of (static) uncertainties.