Hexiang Xu

Spontaneous imbibition in coal governs the migration and redistribution of injected water within coal seams. It is therefore a critical determinant of both water-injection wetting performance and gas-hazard mitigation. However, the role of bedding orientation in regulating dynamic water migration during spontaneous imbibition remains poorly understood. In this study, we used bituminous coal from the Hongyan Coal Mine in Shaanxi Province, China, to prepare specimens. Spontaneous imbibition experiments were conducted in conjunction with gravimetric measurements, low-field nuclear magnetic resonance (LF-NMR), and three-dimensional X-ray microscopy (3D-XRM) to systematically investigate the effects of bedding orientation on water migration during imbibition. A quantitative relationship between wetting-front position and imbibition time was further established. The results show that bedding orientation exerts a pronounced influence on the spontaneous imbibition capacity of coal. All specimens exhibit a common two-stage evolution characterized by rapid water uptake at the initial stage followed by a gradual approach to equilibrium. With continued imbibition, the water content of pores across all size scales increases. Adsorption pores remained the dominant water-storage spaces, whereas increasing bedding angles promoted the involvement of seepage pores, which served as critical pathways linking localized storage with long-distance water transport, thereby altering the spatial migration pattern of water. These results indicate that bedding orientation primarily controls spontaneous imbibition by altering water-migration pathways and hydraulic connectivity along the imbibition direction. This, in turn, governs the extent to which transport-related pore spaces, particularly seepage pores, participate in water migration, ultimately determining both the propagation distance of the wetting front and the macroscopic water-uptake capacity of coal. The findings provide a theoretical basis for optimizing the orientation and spacing of coal-seam water-injection boreholes, as well as the associated injection parameters.

To investigate the influence of the interaction between geological and engineering factors on the effectiveness of hot flue gas displacement for enhancing coalbed methane recovery, a thermo-hydro-mechanical coupled model for binary gas mixture displacement was constructed. First, the spatiotemporal evolution of key physical fields was analyzed. An enhanced harvesting index (EHI) was proposed to evaluate recovery efficiency. Subsequently, the response surface method was used to explore the response patterns of pre-EHI and post-EHI to single factors and multi-factor interactions. Finally, optimization maps of key process parameters for typical regions were drawn. The main results indicate that high-permeability and high-gas regions exhibit higher pre-EHI, but EHI drops rapidly in the later stage. Increasing the N2 ratio and injection pressure effectively improves pre-EHI. As injection pressure increases in the later stage, EHI gradually shifts from N2-dominated to CO2-dominated. When the initial gas pressure is high, pre-EHI first decreases and then increases with increasing CO2 ratio. Low gas pressure and high CO2 ratio correspond to a significant increase in post-EHI. For low-permeability regions, as injection pressure increases, the CO2 ratio should follow the principle of “first increase and then decrease.” For high-permeability regions, gradually reducing injection pressure and increasing the CO2 ratio can achieve multi-objective optimization of post-gas flow rate and recovery efficiency. The research results are expected to provide theoretical guidance for precise time- and zone-specific injection of hot flue gas.

Diffusion is a crucial factor governing gas migration within coal seams. The particle method is mainly used to test the gas diffusion coefficient. However, selecting the appropriate particle size for diffusion coefficient determination remains challenging. Although various diffusion models have been proposed to fit experimental data accurately, their impact on gas extraction simulations is still unclear. In this study, gas diffusion experiments were conducted on nine samples with varying particle sizes, and parameters for four diffusion models were calculated by solving the inverse problem using numerical methods. Four numerical simulations of gas extraction were subsequently performed using these parameters. Finally, a calculation method for determining the time nodes to enhance gas extraction was proposed. Results showed that the gas desorption ratio initially decreased and then stabilized as particle size increased. The representative elementary volume size of coal particles for gas diffusion was 0.83–1.7 mm. Except for classical unipore diffusion model, other diffusion models could effectively fit the experimental data. Among these, time-dependent diffusion model is more suitable for predicting the gas pressure within coal seams and gas production. However, this requires establishing a quantitative relationship between laboratory test results and field-scale simulation parameters. The concept of equivalent extraction resistance was introduced to determine the time nodes for enhanced gas extraction, which were found to be necessary when daily production decreased to 14.47%–21.73% of the initial value. The research findings are of great significance for bridging laboratory results with practical field applications.

Mining disturbances can rupture the closed pores, releasing the gas and potentially triggering gas accidents. The pre-drainage of gas via boreholes is the primary measure for preventing coal and gas outbursts. Nevertheless, the influence of closed pores on gas migration remains unclear, leading to suboptimal borehole spacing and radius. Therefore, a gas–solid coupled model incorporating closed pores was developed to investigate the influence of closed pores on gas migration during gas drainage (GD). Subsequently, response surface methodology was employed to investigate the input parameters and their interactions on residual gas content (RGC) and pre-drainage time (PDT). Finally, an optimization methodology for borehole spacing/radius was presented. The results show that both RGC and PDT exhibit a positive correlation with the ratio of closed porosity to total porosity (λ) and the ratio of closed pore diffusion coefficient to that of the open pore (Do/Dc). Initially, the total gas production is primarily extracted from fractures and open pores, followed by closed pores in the later stages. Single-factor analysis demonstrates that λ, permeability, and Do/Dc have a more significant impact on RGC and PDT compared to borehole spacing and borehole radius. Borehole spacing interacts more strongly with λ, permeability and Do/Dc than borehole radius. An optimization method for borehole spacing and borehole radius, constrained by PDT, RGC, and the number of boreholes, is proposed using response surface optimization maps. This method provides guidance for borehole construction to optimize GD efficiency and minimize RGC.

A photothermally generated microbubble on a single-mode fiber tip with tunable frequency bandwidth was demonstrated for sensitive detection of acoustic waves. The microbubble with spherical gas-water interface formed a flexible Fabry-Pérot cavity at the fiber tip and detected the acoustic waves by interferometric readout of the bubble deformation. To work in different liquids besides water, the sensor was encapsulated into a water-filled tube and the effects of the encapsulation process on the optical and acoustic characteristics of the sensor were investigated. A 40 μm-diameter microbubble based sensor exhibited a noise-equivalent pressure level of ∼1.0 mPa/Hz ^1/2 at the frequency of ∼100 kHz. The bubble diameter was photothermally changed from 20 μm to 60 μm, which enabled online tuning of the sensor resonant frequency from 100 kHz to 300 kHz. This tunable feature is attractive to applications that requires the detection of acoustic waves covering different frequency bands. The encapsulated microbubble sensor with advantages of high sensitivity, tunable bandwidth and low-cost would be interesting for applications in biomedical and industrial areas involving various liquid environments.