The Rumaila Field is in southeast Iraq and contains multiple reservoir intervals, including the Upper Cretaceous Mishrif carbonate reservoir, one of the major reservoirs in the world, that has been producing for more than 50 years. One of the key challenges in the Mishrif is to characterize the pore-structure distinction between primary and secondary porosity. The secondary porosity in the form of large pores, if present, dominates the petrophysical properties, especially permeability. Advanced logs, e.g., nuclear magnetic resonance (NMR) and image logs, can be used to understand the variations in pore structure, both qualitatively and quantitatively. In this paper, we focused primarily on four new wells with very comprehensive logging and coring programs.

NMR logs were acquired using different tools and pulse sequences. This resulted in uncertainty in porosity and T2 distributions and, consequently, complications in the NMR interpretation. We observed two key issues: porosity deficit due to lack of polarization and T2 distribution truncation due to the low number of echoes. We used a single pore model to reproduce the NMR response in different pore sizes and fluid types for different pulse sequences. The results showed that the NMR response, especially in water-filled (water-based-mud filtrate) large pores, is sensitive to polarization time, echo spacing, and tool gradient strength. NMR log data confirmed the modeling results. We recommended an optimum pulse sequence and tool characteristics to fully capture the heterogeneous rock and fluid system in this carbonate reservoir.

NMR logs, when available, were the primary tools to identify the large pores. We present a consistent workflow for NMR log analysis that was developed to identify and quantify large pores and extended to all wells in the field. We used advanced NMR interpretation techniques, e.g., factor analysis (NMR FA) (Jain et al., 2013), in a series of oil wells drilled with water-based mud. Using factor analysis, we identified a cutoff value of 847 ms for large pore volumes. In this manuscript, we also present an integration of laboratory measurements, e.g., NMR, mercury intrusion capillary pressure (MICP) data, whole-core CT scanning, and thin-section analysis, in our interpretation workflow. We also compared the large pore volume from image logs with NMR logs and other laboratory data and observed very consistent results. All the available information was integrated to build an “NMR-based” petrophysical model for porosity, rock type, permeability, and saturation determination. The NMR-based model was very comparable with the classic flow zone indicator (FZI) rock typing. The results of this study were used to modify the NMR acquisition program in the field and to build a petrophysical model based on only NMR and image log measurements for carbonate reservoirs.

In this paper, we will discuss NMR modeling and corresponding log data from various wells to confirm the results. Furthermore, we will present a novel interpretation workflow integrating laboratory measurements and log data, which led to the modification of the NMR acquisition program in the field and the creation of a data-driven petrophysical model based on only NMR and image log measurements for carbonate reservoirs.

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