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The detailed characterization of complex reservoir units, typical of the thin-bedded canyon turbidites system within the clastic environment is essential for accurate reservoir modelling. The sedimentary architecture usually overprinted by late diagenesis results in the intrinsic complexities which poses major problems in modelling these systems. Although the average permeabilities exhibited by most clastic reservoirs is relatively high, the low permeabilities of the component shale strata results in low sweep efficiency and transmissibilities, and may form effective flow baffles. Recent advances in petrophysical modelling and formation evaluation studies demonstrate the applicability of normalized pore throat radius $$\overline{{R_{\text{tot}} }}$$Rtot¯ methodology for improved reservoir characterization and production optimization in challenging systems. This paper presents a modification of the reservoir quality indicator (RQI) methodology for hydraulic flow unit characterization using the normalized pore throat concept. Result of the analysis for the various genetic reservoir units demonstrates an improvement with a correlation coefficient of 78% for the proposed modified RQI over 31% for the existing RQI method in defining the unit slope line for the Channel Storey Axis unit. In addition, regression analysis between the irreducible water saturation from mercury injection capillary pressures and FZI depicts a higher correlation coefficient of 76% for the modified RQI over 64% for the existing method. The higher correlation coefficient indicates an improved efficacy of the proposed model for hydraulic flow zone characterization. The efficacy of the proposed methodology was also validated with a numerical flow simulation model. This demonstrates improved efficient for reservoir characterization studies.

journal of petroleum exploration and production technology

Modified reservoir quality indicator methodology for improved hydraulic flow unit characterization using the normalized pore throat methodology (Niger Delta field as case study)