Geostatistical Modelling of Reservoir Quality Over “Bright” Field, Niger Delta

Abe S. J (Department of Applied Geophysics, Federal University of Technology, Akure, Nigeria)
Olowokere M. T (Department of Applied Geophysics, Federal University of Technology, Akure, Nigeria)
Enikanselu P. A (Department of Applied Geophysics, Federal University of Technology, Akure, Nigeria)

Abstract


The quality of any hydrocarbon-bearing reservoir is vital for a successfulexploitation work.. The reservoir quality is a function of its petrophysicalparameters. Hence the need to model these properties geostatistically inorder to determine the quality away from well locations.Composite logsfor four wells and 3-D seismic data were used for the analysis. A reservoirnamed Sand X was mapped and correlated across wells 1 through 4. Thefour reservoir quality indicators - Effective porosity, permeability, volumeof shale and net-to-gross- were estimated and modelled across the field.Sequential Gaussian simulation algorithm was employed to distribute theseproperties stochastically away from well locations and five realizationswere generated. The volume of shale varied from 0.025 (Well 1, second realization) to 0.18(Well 2, first realization). The net-to-gross varied from 0.81 to 0.96 in wells 3 and 4 respectively, for the third realization, while the effective porosity varied from 0.125 to 0.295 for the fifth realization in Wells3 and 4 respectively. The permeability is above 5000mD at all the existingwell locations.These realizations were ranked using Lp norm statistical toolto pick the best for further evaluation. The reservoir quality deduced fromthe analyzed indicators was favourably high across the reservoir.The application of geostatistics has laterally enhanced the log data resolution away from established well locations.

Keywords


Probabilistic;Lp norm;Modelling;Gaussian;Stochastic

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References


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DOI: https://doi.org/10.30564/jgr.v3i1.2805

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