Multi-Field Integrated Rock Type Framework Optimisation in Thrusted Carbonates of The Thamama Group to Reduce Modelling Uncertainty and Improve Reservoir Characterisation

Abstract

AbstractObjectives/ScopeThis study aims to use modern techniques to re-characterise the diagenetically altered Thamama Group reservoir units of multiple gas-condensate fields in Sharjah, UAE and determine robust rock-typing framework from the full dataset and recent core analysis program. This would be used to reduce mismatches observed in static and dynamic properties and demonstrate that a matched-outcome can be achieved with less model manipulation by focusing on textural variances within the units.Methods, Procedures, ProcessResults, Observations, ConclusionsFour petrophysical rock types were identified and found good equivalence to the identified petrographical rock types; the algorithm separated mono-modal micritic packstones from highly diagenetically altered grainstone-wackestone rudstone facies, with the rock-type clusters also being defined by Winland-r35 and Lucia poro-perm threshold lines. A single rock-typing framework, suitable for all studied fields with observed differences being explained by variability in the rock type proportions.When compared to the previous rock typing framework and reservoir models, better matches were achieved between predicted properties and core data in QC wells. Static model property distributions were more realistic in achieving a volumetric match with produced gas. Better saturation distribution with realistic Swcr and Socr were observed by using the new Rock Typing Sw equations. Rel-perm modification for increasing water production to match the observed data was negligible due to presence of more water saturation in the crest of the reservoir. Multipliers for permeability and porosity were significantly reduced to match the well productivities and tubing head pressure estimations were improved due to less mismatch with liquid production rates.Novel/Additive InformationThis work represents the first time petrophysical and petrological rock typing was conducted for several gas-condensate fields in Sharjah, UAE. Newly acquired core data, petrographical information and core descriptions were integrated in the study.The previous workflow, established in 1993, was updated using modern machine-learning techniques incorporating new data and a wider range of data than the previous rock typing model that was based solely on porosity measurements, remaining consistent to pore-scale and textural changes.