This study addresses challenges in characterizing the unconsolidated reservoirs of the Tambaredjo Oilfield, Suriname, focusing on core porosity and permeability data from eight wells to improve reservoir modeling accuracy. The study employed a two-phase approach: 1. Core re-evaluation and well log calibration: Permeability to air (ka) gathered was found in two measured sets: at 400 psi net confining stress (NCS) and at 800 psi NCS. The two sets of measurements were plotted against log estimated porosity, observing that some samples measured at 400 psi tend to follow the total porosity (PHIT) from logs and that some measured at 800 psi follow the effective porosity (PHIE). Cross plots were created to convert the measurements of porosities and permeabilities from 400 to 800 psi. Distribution of Rock Types (RT) were re-estimated. 2. Rock type-specific kv/kh ratios: The data was aggregated and porosity vs permeability (vice versa) correlations were created to fill missing data for either porosity or permeability and to remove outliers. From the actual core data, kv was available only for distinguishing the defined RT1, RT4 and RT5. Simple interpolation was applied to estimate the missing RT associations. kv/kh ratios were found by using the minimum value of different averaging methods. Then the final ratios were upscaled by weighted average for kh and harmonic for kv. Phase 1: The observed inconsistencies in core data could not be definitively explained. However, a 2013 assessment identified the core plug preparation method as potentially affecting clay content and pore structure, impacting porosity measurements. The conversion of porosities to 800 psi equivalents and the re-estimated rock type distribution better aligns with expectations for unconsolidated sandstones, with a higher proportion of clay rich rock types. This approach offers a solution for situations where core data quality is limited and acquiring new data is not feasible. Phase 2: Data quality checks ensured the removal of inaccuracies from the aggregated dataset. Missing kv data were estimated using correlations, and kv/kh ratios were determined for various rock types. This methodology addresses the previous limitations of using constant kv/kh values and is expected to improve the accuracy of vertical flow representation in reservoir models. This combined approach is expected to enhance permeability estimates, improve core-log calibration, and address inaccurate vertical flow observed in previous simulations. It offers a valuable solution for heterogeneous, unconsolidated reservoirs with limited core data quality. Considering rock type variations and improving vertical flow characterization are crucial steps towards more realistic reservoir models for the Tambaredjo Oilfield.