1. A method of training a subterranean fluid viscosity model based on NMR data, the method comprising: accessing multiple relaxation-time distributions generated from NMR measurements of a fluid associated with a subterranean region; normalizing each relaxation-time distribution to a common normalizing value to obtain normalized relaxation-time distributions; computing parameters for a plurality of weighted radial basis functions from the normalized relaxation-time distributions; and producing a subterranean fluid viscosity model that includes the weighted radial basis functions and the computed parameters.