Integration of Core and Log Data for Classification of Reservoir Rock Types in Minagish Reservoir of Greater Burgan Field, Kuwait

A detailed Geological and Petrophysical characterization was achieved in a stepwise approach as part of full field 3D Reservoir Modeling and Simulation study for Minagish reservoir in the Greater Burgan field in Kuwait. Foundation of Reservoir Rock Types (RRT) was developed in first step based on Mercury Injection Capillary Pressure (MICP) dataset. A combination of Discriminant Analysis and Indexed Self Organizing Map (SOM) was used for rock type classification using hyperbolic tangent method. To improve classification of bimodal Pc curves, additional pressure values at different non-wetting phase saturations were used in conjunction with above mentioned parameters. In second step, the available Routine Core Analysis (RCA) porosity, permeability data was grouped together based on common patterns to generate rock types in RCA domain. Blind tests in two of the cored wells revealed a conformance of 81% between MICP and RCA Petrophysical Groups (PG). In the final step of the process, petrophysical groups were propagated in log domain using available log measurements common in all the wells of the field. It was challenging to establish a high level of accuracy for PG’s in log domain mainly due to fine scale heterogeneity and inability of log data to capture rock fabric variation. This porosity estimate, coupled with rock type classification, helped to derive a continuous permeability log with a correlation coefficient of 0.89 validated in key cored wells. The porosity and permeability data in all the wells was incorporated in the 3D geocellular model after up-scaling honoring the unique, per rock type, Phi-K relationship. Modeled capillary pressure curves generated for each rock type in the core domain using MICP data set in 3 wells were used in saturation height modeling. The modeled equation was captured in the 3D geocellular model after populating rock types in the 3D grid to map water saturation for volumetric estimation.