Permeability and initial saturation are two key reservoir parameters to be defined in subsurface reservoir models. The prediction of these parameters is particularly challenging since they cannot are not abtained directltly from downhole well logs. In this paper, we focus on characterization of pore systems at core plug scale to provide improved models for permeability and saturation prediction. The wider implication of the workflow presented is that they offer better integration between methods used for saturation prediction and methods used for permeability prediction.

We examine the use of Mercury Injection Capillary Pressures (MICP) for genetic unit classification and for predicting permeability and saturation. The method is based on a NORMALIZED PORE THROAT APPROACH (Rtot¯) with Niger Delta as case study. Petrographic observations of pore types are analysed alongside MICP data and air permeability for a number of genetic reservoir units. A correlation coefficient, R2 of 0.81 is obtained for permeability - Rtot¯ plot compared to R2 of 0.56 for the porosity-permeability plot. We also investigated Volotikin's method for generating primary drainage capillary pressure curves from NMR logs, to generate pore throat radius as input to Rtot¯.

Model Validation with reference to existing Flow Zone Indicator (FZI) based approach, NMR based methods by SDR and Coates, and the existing core derived permeability correlation for an Offshore Niger Delta Field.

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