--> Prediction of Hydrocarbon Type and Quality: Geochemical Analyses of Gas, Oil, and Rock Samples, by Daniel M. Jarvie, C. Jiang, Hossein Alimi, Patrick Obot, and O. S. Adegoke; #90037 (2005)

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Prediction of Hydrocarbon Type and Quality: Geochemical Analyses of Gas, Oil, and Rock Samples

Daniel M. Jarvie1, C. Jiang1, Hossein Alimi1, Patrick Obot2, and O. S. Adegoke3
1 Humble Geochemical Services, Humble, TX
2 Global Energy Co. Ltd, Victoria Island, Nigeria
3 Mosunmolu Limited, Lagos City, Nigeria

Assessment of Nigerian petroleum and reservoir systems in onshore and offshore basins has generally been problematic as source rocks are seldom encountered during drilling. Tertiary source rocks have been reported (Haack et al., 2001). It is likely that a Neocomian system exists based on assessment of onshore tar sands. From analysis of onshore oil samples, it is also evident that multiple source lithofacies are present, which provides some predictive capabilities. Offshore and particularly deepwater systems have additional uncertainties in hydrocarbon charge and charge type as well as oil quality predictions due to limited characterization of available oils and any penetrated source horizons. However, while building an understanding of the petroleum systems, testing and completion operations can be aided by geochemical techniques. This includes determination of producible zones by oil type and quality as well as determination of reservoir continuity and commingled production allocation.

Available assets such as existing gas, oil, and rock samples should be characterized using geochemical inversion (Bissada, 1991). Evaluation of oil asphaltenes for kinetic parameters and compositional yields can be used in lieu of, and as an organofacies independent substitute for, effective source rock samples.

Mud gas and bottled cuttings samples can be used to evaluate both petroleum and reservoir systems. Combining gas and rock analyses permits determination whether a reservoir compartment is oil or gas as well as the type and quality of hydrocarbon products that are present even when oil-based mud is used. These predictions can be expanded as the knowledge-base is expanded.