US 12,000,279 B2
Estimating pore and fluid characteristic properties in rock samples using nuclear magnetic resonance analyses
Olabode Ijasan, The Woodlands, TX (US); and Darren M. McLendon, Houston, TX (US)
Assigned to ExxonMobil Technology and Engineering Company, Spring, TX (US)
Filed by ExxonMobil Technology and Engineering Company, Spring, TX (US)
Filed on Aug. 14, 2020, as Appl. No. 16/947,764.
Claims priority of provisional application 62/930,275, filed on Nov. 4, 2019.
Claims priority of provisional application 62/930,270, filed on Nov. 4, 2019.
Prior Publication US 2021/0132250 A1, May 6, 2021
Int. Cl. G01N 24/08 (2006.01); E21B 7/04 (2006.01); E21B 49/02 (2006.01); E21B 49/08 (2006.01); G01N 15/08 (2006.01); G01N 33/24 (2006.01); G01R 33/50 (2006.01); G01V 3/32 (2006.01); G01V 3/38 (2006.01)
CPC E21B 49/088 (2013.01) [E21B 7/046 (2013.01); E21B 49/02 (2013.01); E21B 49/0875 (2020.05); G01N 15/088 (2013.01); G01N 24/081 (2013.01); G01N 24/082 (2013.01); G01N 33/241 (2013.01); G01R 33/50 (2013.01); G01V 3/32 (2013.01); G01V 3/38 (2013.01); G01N 2015/0846 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of improving production of hydrocarbons from a subsurface region, comprising:
identifying modes in nuclear magnetic resonance (NMR) longitudinal relaxation time (T1)-transverse relaxation time(T2) data from a plurality of samples;
assigning the modes to a poro-fluid class;
clustering the modes based on poro-fluid class to produce a plurality of clusters, wherein each cluster represents one or more poro-fluid classes;
estimating a bulk fluid relaxation time (estimated TB) based on an asymptote fit of the clusters, wherein the asymptote is based on T1 and T2 relaxation mechanisms in a bulk fluid relaxation-dominated limit;
estimating a ratio of a transverse T2 pore surface relaxivity constant (ρ2) to a longitudinal T1 pore surface relaxivity constant (ρ1), the ratio represented as ρ2/ρ1, based on an asymptote fit of the clusters, wherein the asymptote is based on T1 and T2 relaxation mechanisms in a surface relaxation-dominated limit;
fitting the T1 relaxation mechanisms and the T2 relaxation mechanisms to one or more of the clusters using the estimated TB;
deriving at least one pore or fluid relaxation parameter and endpoint for the poro-fluid classes from the fit, wherein the at least one pore or fluid relaxation parameter and endpoint is selected from the group consisting of ρ1, ρ2, a pore surface-to-volume ratio (A/V), an equivalent pore-throat radius (req), and a bulk fluid relaxation time (TB); and
identifying potential hydrocarbon-bearing formations in the subsurface region based on the derived at least one pore or fluid relaxation parameter and endpoint for the poro-fluid classes.