The Block 9 field located in South Iraq has multiple reservoir units including the late Cretaceous Mishrif carbonates. Regionally, Mishrif consists of shallow-marine carbonates, known as the most important oil-bearing reservoir in southern Iraq and the whole Mesopotamian basin. One of the key subsurface challenges in carbonate reservoirs is how to understand and characterize reservoir complexity and heterogeneity and define the rock type for the static model. The complexity and heterogeneity of the reservoir have been reflected based on the core data and production data. This paper aims at finding a better method to accurately quantify the petrophysical rock types (PRT) for single wells and then depict the reservoir property variation laterally.
Based on the integrated study of rock typing, in a core domain, six rock types have been defined. Based on the CT scan, thin section analysis, and image log, it's observed that rock type 1 has more vugs and moldic pores than rock type 2 and rock type 3. The vugs and moldic pores in the form of large pores, if present, dominate the petrophysical properties, especially permeability. Advanced logs, e.g. nuclear magnetic resonance (NMR) logs, when available, were the primary tools to identify the large pores.
In the study of rock typing, one of the challenges is to define the PRT from cored wells to uncored wells using the method of cluster analysis based on conventional log data. Because of the ambiguous character of conventional log data between different rock types, there are high uncertainties to define the petrophysical rock type. The main reason is that the conventional log cannot depict the variations in the pore structure. However, advanced logs, e.g., NMR logs and image logs can be used to characterize the variations in pore structure, both qualitatively and quantitatively.
This paper presents a feasible method to quantify the large pores including moldic pores and vugs and define the PRT by integrating core data and NMR log data and extending the rock types to the other wells with available NMR log data. Firstly, by correlating between mercury injection capillary pressure (MICP) data and NMR data of different rock types, a cutoff of 256ms~300ms of T2 relaxation time was estimated to distinguish rock type1 and rock type 2 & rock type 3, and a variable named vug was defined to quantify the large pores. Then a cross plot was created to build the relationship between the variable vug and routine core analysis (RCA) data. Then two cutoffs were identified to separate rock types 1, 2, and 3. Finally, when the cutoff was determined, these cutoffs can be used to accurately define the PRT for uncored wells with available NMR log data.
Well test, production logging, and sonic noise logging have been carried out in this field. Based on the production logging and sonic noise logging data, the identified production contribution for each subunit is consistent with the rock typing defined by the NMR log. Rock type 1 is the highest permeable zone with more moldic pores and vugs which has the highest production contribution. The method can be widely applied in this area only if the NMR log is available. Therefore, NMR log is very helpful and effective for quantitative rock type classification and decreases the uncertainty of using the conventional log data solely.