Developing a straightforward and robust approach for investigating reservoir compartmentalization based on chemical composition heterogeneities.

Reservoir compartmentalization restricts fluid flow, and failing to recognize or properly understand this phenomenon can significantly impact future decisions and designs in the field. Due to the importance of this issue, various methods have been developed in the literature, and there's an ongoing effort to develop new strategies for reducing uncertainties in recognizing reservoir compartmentalization. In this study, the moving window root mean square deviation method was developed and applied as a novel approach to evaluate reservoir compartmentalization in the Asmari-Jahrum reservoir of the Nargesi oil field, as a case study. By incorporating a moving-window concept, this method enhances the sensitivity of compositional comparison and provides a more detailed insight into reservoir heterogeneity. The proposed method revealed subtle differences in the crude oil fingerprints obtained from the FTIR spectroscopy of asphaltenes and those obtained from GC fingerprinting. This efficient approach disclosed some heterogeneities in the oil fingerprints across the studied field. The reservoir engineering data, such as bulk PVT properties (e.g., solution GOR and saturation pressure) and reservoir fluid composition, also confirmed these oil composition heterogeneities. The final decision regarding the connectivity between wells was made by integrating all individual data sets to provide a compartmentalization model for the studied field. This model demonstrated that the Asmari-Jahrum reservoir in the Nargesi oil field comprises two distinct zones with no flow communication during production. The activity of paleo highs in the Dezful Embayment, resulting from the reactivation of inherited basement faults, is likely the reason for the observed compartmentalization. Although the proposed method is straightforward for comparing every data set, the results are robust and reliable for inferring reservoir architecture and evaluating reservoir compartmentalization. This phenomenon is a key control on pressure communication, fluid flow behaviour, and the efficiency of field development and reservoir management strategies.