Using data from an ENI-operated field in Italy, a workflow was developed to estimate absolute permeability from NMR-derived grain size distribution (GSD). The principal driver for the work is a lack of consistency and associated lack of confidence in log-based permeability estimation using conventional methods. While production / well test-derived permeabilities are still considered accurate for understanding macro-scale flow characteristics, knowledge of heterogeneity at smaller scales is critical to effective reservoir management in complex fields.
The field reservoir rock comprises several minerals. Considerable variation of their volumes is observed within 3 wells and recognized as one of the limitations of conventional NMR permeability models. The log-scale permeability estimation was studied/examined by incorporating multimineralogical influence on NMR relaxation within a GSD prediction model. In addition to the rock properties analysis, a 2D NMR evaluation of pore fluid characteristics and substitution to equivalent 100' water condition enables the grain size model to be executed. The model output of sorting together with an NMR-effective porosity is then used in a Kozeny-Carman permeability framework, updating the tortuosity correlation with the predicted grain size distribution. The results compare favourably with formation testerderived mobilities, which is positive because the mobility estimation of the Kozeny-Carman model is derived from a hydraulic concept. The results suggest that a practical and valuable method has been developed.
