(untitled) (Journal of Engineering, 2024)
Accurate permeability prediction is essential for reservoir characterization, especially in building three-dimensional reservoir models. However, predicting permeability in the complex Tertiary reservoir/Ajeel oil field, with its different rock types and multi-layered formations, poses significant challenges. This paper utilizes well logs and core data from cored wells to predict permeability for uncored wells and intervals, uses an approach integrating rock typing by cluster analysis techniques and the Flow Zone Indicator (FZI) method by categorizing reservoirs into hydraulic flow units(HFUs) based on a reservoir quality index(RQI). This approach includes classifying reservoir rocks and zonation based on comparable petrophysical properties in horizontal and vertical dimensions. Through cluster analysis, four distinct rock types in the Tertiary reservoir are identified, and four hydraulic flow units are defined by correlating core permeability and porosity using the FZI method. The correlation coefficient (R² = 0.81) is acceptable and supports the relationship reliability between FZI-derived permeability and core permeability. Then, four different rock types are linked to their corresponding permeability equations derived from the FZI method and the compensation of effective porosity values in these equations for permeability prediction. Ultimately, the permeability of uncored wells and intervals, depending on this approach, will be predicted using well-log data.