A novel NMR methodology for the quantitative characterization of solid organic matter in shale oil

Continental shale oil reservoirs in China, particularly those of low to medium maturity, contain a high proportion of untransformed solid organic matter (SOM). The SOM plays a critical role as a potential oil and gas resource. Nuclear magnetic resonance (NMR) is a powerful technique for the evaluation of shale oil reservoirs. However, it is challenging for conventional T 1 - T 2 measurement methods to fully capture signals from ultra-short relaxation components such as SOM, due to the measurement deficiency caused by NMR instruments. To this end, the free induction decay (FID) and inversion recovery FID (IR-FID) pulse sequences are introduced, and two novel methods are proposed for quantitative characterization of SOM. The first method, Method I, employs the signal amplitude difference between T 2 ∗ and T 1 - T 2 spectra to obtain the SOM content. The second, Method II, directly quantifies the SOM signal from the T 1 - T 2 ∗ spectrum. A novel parameter, the ratio of T 1 / T 2 * to T 1 / T 2 , is also proposed to refine the identification of SOM in the T 1 - T 2 spectrum. The effectiveness of the proposed methods is validated by strong correlations with four geochemical parameters indicative of SOM content. The results from Method I show significantly improved correlations with all four geochemical parameters compared to the conventional T 1 - T 2 method. The results from Method II show excellent correlations with parameters from step-by-step (SBS) Rock-Eval pyrolysis, reaching coefficients of determination ( R 2 ) as high as 0.8958 and 0.8828. This method also shows strong numerical consistency with the geochemical parameters, specifically with ( S 1-2b + S 2-1 + S 2-2 ). Method II is therefore highly suitable for quantitatively evaluating the total solid hydrogen content, including solid petroleum hydrocarbons, bitumen, and kerogen. This work achieves, for the first time, the precise quantification of SOM at the core scale, providing a high-precision, large-scale, and non-destructive approach for evaluating the resource potential of shale oil reservoirs.