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Develops a mathematical model to enhance NMR interpretation of oil mobility in shale reservoirs, suggesting improved characterization techniques.
The advancement of shale oil field development is of significant importance for the global energy sector. Although well-established experimental systems exist for studying shale oil occurrence and mobility, nuclear magnetic resonance (NMR) interpretation methods still have significant limitations. Conventional NMR methodologies are mostly developed for water-saturated samples, directly correlating relaxation times with pore radius while neglecting the influence of bulk relaxation on the relaxation process of oil. This decoupling between the relaxation time and pore size undermines the reliability of pore size distributions interpreted from NMR data. To address this limitation, this study develops a quantitative mathematical model for quantifying the bulk relaxation influence in NMR responses. By incorporating a theoretical bulk relaxation influence factor, we propose a method to quantitatively partition the NMR relaxation of shale oil into its bulk and surface components. By doing so, the method extends its application to establish criteria for partitioning signals in T 1 - T 2 maps. This approach allows for a more precise characterization of shale oil distribution and mobility grounded in the fundamental differences between bulk and surface relaxation. Our experimental results validate the method’s utility in characterizing fluid occurrence and assessing mobility, providing a critical foundation for shale oil reservoir characterization and efficient development.
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Li et al. (2026) studied this question.
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