Sandstone surface relaxivity determined by NMR T2 distribution and digital rock simulation for permeability evaluation

Abstract Many of the world's oil reservoirs are sandstones and some equations have been widely explored to estimate their permeability from NMR measurements, especially those based on the Schlumberger Doll Research (SDR) and Timur–Coates models. In both cases, the permeability is assumed to be related to pore sizes. Brownstein and Tarr showed that, under fast diffusion regime, the NMR transverse relaxation time is proportional to the pore size and the proportionality constant is defined by the interaction fluid/surface and represented by the surface relaxivity ρ. However, although there are several methods in the literature to estimate ρ, no standard methods have been established so far, to our knowledge. In this work, we estimated surface relaxivity by combining experimental and simulated NMR data using a recently developed computational method to emulate the NMR signal of fluids within Digital Rocks. In addition, we analyzed the correlation between the pore radii and the experimentally measured gas permeability. Comparing Schlumberger and Timur-Coates models for permeability prediction, we propose that the macro and microporosity intensities identified in the T2 distribution are correlated with characteristics of the sandstone surface. Thus, sandstone surface relaxivity can be estimated using the ratio of macro and microporosity intensities from NMR and, consequently, the pore size distribution can be obtained using only T2 distribution data.