Patent Document ID: 10061052
Application ID: 14399025
Patent Flag: 1

Claim One:
1. A method of training a subterranean heavy oil viscosity model based on nuclear magnetic resonance (NMR) data, the method comprising steps: (a) conducting multiple ex-situ NMR measurements consisting of individual Carr Purcell Meiboom Gill (CPMG) echo trains corresponding to different inter-echo spacing values (TE) from a sample collected from a subterranean region; (b) obtaining individual relaxation-time distributions corresponding to the individual TE values in step (a); (c) normalizing each relaxation-time distribution to a common normalizing value to obtain a normalized relaxation-time distribution whose integral equals the common normalizing value; (d) repeating steps (a)-(c) with multiple heavy oil samples from different subterranean regions having different viscosities; (e) obtaining oil viscosity values of all samples with a non-NMR means; (f) producing a subterranean fluid viscosity model for heavy oil by computing parameters for a plurality of weighted radial basis functions from the normalized relaxation-time distributions and the viscosity values from step (e); and (g) determining properties of hydrocarbon fluid in the subterranean region based only on the NMR data using the viscosity model in step (f) for use in reservoir quality assessment and, based on the determined properties, selection of which wells and/or which depth interval of a well to move into production.