Abstract
Rock typing is an essential tool used to distribute rock and fluid properties in reservoir models. It provides estimates of oil reserves that are more accurate during field studies and prediction of reservoir performance. However, geomodelers are frequently faced with challenges of integrating geological facies with rock characteristics and fluid flow to predict petrophysical properties due to limited correlation between geological features and engineering concepts. Therefore, in this study, petrophysical rock types (PRTs) were defined using both core and log data, and the relationship between capillary properties, hydraulic flow units, permeability and porosity correlations was enhanced. The PRTs were determined through quantitative methods using mercury injection capillary pressure information and a probabilistic approach to distinguish convoluted pore systems. Subsequently, various pore structure characteristics were defined to detect petrophysical variation among pore systems to enhance petrophysical rank of rock types. Furthermore, for a reservoir, consistency in J-function curves for saturation height above free water level was determined. Finally, permeability generated from other empirical equations was compared with log-derived permeability to recommend a suitable approach for clastic formations in the Sabah Fields. By using capillary data to derive saturation height functions, the hydraulic units demonstrated consistent results of rock types, reduced the uncertainties in reservoir models and integrated geological description with engineering hydraulic features. The Winland R35 approach was found to be susceptible to pore throat radius, and traditional neutron–density rock typing approach was dependent on the shale cutoff used.
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Notes
1 foot = 0.3048 m.
1 psia = 6.89476 kPa.
1 mD = 0.986923 × 10−15 m2.
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Acknowledgments
The authors would like to thank the Ministry of Higher Education (MOHE), Malaysia, and Universiti Teknologi Malaysia for supporting this research through Research Management Grant Nos. R.J130000.7851.5F030, Q.J1300003551.06G68, R.J1300007351.4B545 and PETRONAS for providing the subsurface dataset.
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Barach, B.A.B., Jaafar, M.Z., Gaafar, G.R. et al. Development and Identification of Petrophysical Rock Types for Effective Reservoir Characterization: Case Study of the Kristine Field, Offshore Sabah. Nat Resour Res 30, 2497–2511 (2021). https://doi.org/10.1007/s11053-021-09851-3
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DOI: https://doi.org/10.1007/s11053-021-09851-3