Correlation of porosity types derived from NMR data and thin section image analysis in a carbonate reservoir

Nuclear Magnetic Resonance (NMR) longitudinal relaxation (T-1) experiments on water saturated plugs can be used to derive pore size frequency distributions in naturally porous media. These distributions can be cross validated with related distributions derived from petrographic image analysis (PIA). The decomposition of both NMR and PIA polymodal distributions yields pore types. Each pore type represents a sub distribution of pores possessing a characteristic size and shape. NMR pore types and PIA pore types are linearly related with respect to size. The constant of proportionality of this relationship can be used to estimate a value for the enhancement of relaxation caused by the nuclei interacting with the pore wall, called surface relaxivity (rho). The nature of the NMR pore type spectra indicate that a low T-1 component is associated with all the NMR pore types. The calculation of an estimated value of rho can be either from the linear relationship or from individual NMR/PIA pore type relationships. The various calculated values are very similar, and thus, a mean value for a given sample suite can be calculated. The estimation of rho is critical in the interpretation of NMR T-1 data, and external calibration is essential. This study demonstrates that calibration to PIA is one method, and that it is advantageous because PIA is the best method of deriving mean pore size from thin section. Moreover, PIA is advantageous because geometry effects are directly evident from thin section and SAWVEC B (an unmixing algorithm that decomposes polymodal data), as well as the ability of inferring mineralogy. In addition, PIA is advantageous because of its direct correlation to petrophysical properties. Therefore, NMR and PIA derived pore sizes can be used to cross validate each other. Thus, the relationship that commonly exists between pore size and throat size ensures that NMR and PIA derived pore sizes will have relevance in the understanding of petrophysical properties associated with fluid flow in natural porous media.