title: Comparison of NMR simulations of porous media derived from analytical and voxelized representations.
abstract: We develop and compare two formulations of the random-walk method, grain-based and voxel-based, to simulate the nuclear-magnetic-resonance (NMR) response of fluids contained in various models of porous media. The grain-based approach uses a spherical grain pack as input, where the solid surface is analytically defined without an approximation. In the voxel-based approach, the input is a computer-tomography or computer-generated image of reconstructed porous media. Implementation of the two approaches is largely the same, except for the representation of porous media. For comparison, both approaches are applied to various analytical and digitized models of porous media: isolated spherical pore, simple cubic packing of spheres, and random packings of monodisperse and polydisperse spheres. We find that spin magnetization decays much faster in the digitized models than in their analytical counterparts. The difference in decay rate relates to the overestimation of surface area due to the discretization of the sample; it cannot be eliminated even if the voxel size decreases. However, once considering the effect of surface-area increase in the simulation of surface relaxation, good quantitative agreement is found between the two approaches. Different grain or pore shapes entail different rates of increase of surface area, whereupon we emphasize that the value of the "surface-area-corrected" coefficient may not be universal. Using an example of X-ray-CT image of Fontainebleau rock sample, we show that voxel size has a significant effect on the calculated surface area and, therefore, on the numerically simulated magnetization response.
authors: Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
authors: Guodong
authors: G
authors: Jin
authors: Carlos
authors: C
authors: Torres-Verdín
authors: Emmanuel
authors: E
authors: Toumelin
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008956:Models, Chemical; D016062:Porosity; D012680:Sensitivity and Specificity