Study on Fluid Mobility of Different Types of Deep Coal Rocks Based on Nuclear Magnetic Resonance

Deep coalbed methane (CBM) represents a strategic successor field for unconventional oil and gas exploration and development in China, and fluid mobility is a key parameter determining CBM recovery rates. Existing NMR-based studies on coal rock pore structure and fluid mobility suffer from three deficiencies: a lack of coal rock classification based on T2 spectral morphology, failure to incorporate fractal characteristics into pore classification, and insufficient understanding of fluid mobilization mechanisms in different pore types during gas-driven recovery. This study investigates deep coal rocks of the Taiyuan Formation in the Linxing Block, eastern Ordos Basin, using low-field nuclear magnetic resonance (LF-NMR), saturation gas displacement experiments, and fractal theory. Deep coal rocks were classified into three types based on T2 spectral peak morphology under saturated conditions: Type I (central main peak), Type II (left-shifted main peak), and Type III (balanced bimodal peak). A fractal-based method was established to subdivide fluid-filled pores into four types: P1-1, P1-2, P1-3, and P2. Through multiple nitrogen displacement experiments, the fluid mobilization characteristics of each pore type at different displacement stages were quantitatively characterized. A fluid mobility index was proposed to comprehensively evaluate the overall fluid mobility of coal rocks. The results indicate that Type I coal rocks exhibit the highest fluid mobility (54.83% after three displacement cycles), with P1-3 pores as the primary mobile fluid reservoir, whereas Type II and Type III coal rocks show lower mobility (27.70% and 32.89%, respectively), with P1-2 pores as the dominant contributors. Pore structure complexity exhibits a significant nonlinear evolutionary relationship with fluid mobility. The fluid mobility index demonstrates a strong positive correlation with the degree of mobile fluid, validating its effectiveness in characterizing fluid mobility in deep coal rock reservoirs. These findings provide a theoretical foundation for sweet spot identification and development optimization in deep coal gas reservoirs.