Finding out the contributions of pores and fissures at different scales in coal to permeability can lay a foundation for studying the flow regularity of fluid in coal seam. In this paper, coal samples from Changping mine and Pingdingshan No.6 mine were taken as research objects, and mathematical models for calculating the permeability of micron-scale pores and micron-scale fractures were constructed by the method of Scanning Electron Microscope (SEM). A mathematical model for calculating the permeability of nano-scale seepage pores and nano-scale diffusion pores was constructed by the method of mercury injection and fractal dimension. According to the parameters of perimeter, area, length, average width, volume and specific surface area of pores and fractures at different scales measured by SEM and mercury injection, the permeability of pores and fractures at different scales was calculated by the established mathematical model, and the calculated results were compared with the measured values. The results show that, the measured permeability varied linearly with the calculated total permeability, by introducing the effective porosity, the model for calculating permeability of pores and fractures at different scales using SEM and mercury intrusion method compensates for a single calculation method. The nano-scale diffusion pores accounted for the highest proportion (between 71.21% and 90.66%) of the total effective porosity, while they had little influence on permeability and contributed less than 0.1% to the permeability. The micron-scale seepage pores and fractures accounted for the smallest proportion in terms of effective porosity, ranging from 3.24% to 14.78%, while contributing the most (more than 70%) to the overall permeability. With the increase of permeability, the contributions of micron-scale seepage pores and fractures in the coal samples to effective porosity and permeability increased; however, contributions of nano-scale diffusion pores to effective porosity and permeability both decreased.
Characterization of microscopic structure and macroscopic physical property are the basis for better understanding of coalbed methane reservoirs. X-ray computed tomography (CT), as an nondestructive measurement, has been widely and successfully applied to characterize the internal structure of coal. In this study, we introduce the principle of CT imaging and the microstructure recognition. A summary of CT imaging-based coal microstructure characterization follows, including three-dimensional (3D) microstructure reconstruction, pore and mineral quantification, and equivalent pore network model construction. We review the methods used to evaluate the macroscopic properties of coal, including porosity calculation, gas adsorption/diffusion rate test, permeability simulation, and mechanical behavior evaluation. This study discusses the application of CT to investigate the evolutionary mechanisms of microstructure and macroscopic properties during gas adsorption, temperature change, and damage deformation. We conclude this review with a summary of the challenges and application perspectives of CT. The small scanning range, limited observation accuracy, functional limitations, lengthy testing process, and high cost are some of the major hurdles in the broad application of CT for coal characterization. In the future, CT should be combined with other techniques to establish full-scale pore and fracture models, identify mineral types in microstructures, and effusively use the advantages of CT by selecting the key points in the evolutionary mechanisms of microstructure and macroscopic properties.
It is important to study the control mechanism of geological factors (coal bed structure and hydrodynamics) on the evolution of coalbed methane (CBM) gas components. In this paper, the tectonic, hydrochemical, and hydrodynamic field distributions in the Daning-Jixian block, the eastern edge of the Ordos Basin, were obtained by using well logging, seismic, and water sample testing data. The CBM origin was obtained by analyzing methane carbon isotope abundance (δ13C1) in gas sample tests. The results show that (1) the 5# coal seam in the study area is a monoclinic structure with deeper burial in the northwest and shallower burial in the southeast, and the direction of groundwater transportation is consistent with the slope direction of the terrain; (2) CBM in the study area is thermogenic gas and undergoes diffusion, dissolution, and transportation processes. As the hydrodynamics changed from high to low, the percentage of CH4 concentration increased, the percentage of CO2 and N2 composition decreased, pH became smaller, total dissolved solid increased, and δ13C1 became heavier; (3) at the early stage of drainage mining, δ13C1 increased significantly, the CH4 component showed a decreasing trend, and nonhydrocarbon gas components increased. As the discharge mining proceeds, the CH4 component tends to increase and the nonhydrocarbon gas components decreases.
Abstract Analysis of the adsorptive behaviour of kaolinite to sodium dodecyl benzene sulphonate (SDBS) at different concentrations can provides a basis for selecting the best concentration. The adsorptive capacity and adsorptive behaviour of kaolinite to SDBS at different concentrations were studied using ultraviolet spectrophotometer, pseudo-first-order adsorption kinetics model, and pseudo-second-order adsorption kinetics model. Scanning electron microscopy with energy dispersive spectrometry (SEM–EDS), X-ray diffraction (XRD), and infrared spectroscopy (FTIR) were used to study the variation characteristics of surface structure, crystallinity indices, and main functional groups on kaolinite before, and after, adsorption. The results show that as the SDBS concentration increase, the adsorptive capacity of kaolinite to SDBS increase. The adsorption process can be accurately fitted by the pseudo-secondary adsorption kinetic model, which means the adsorptive behaviour was mainly chemical in origin. The adsorption of SDBS by kaolinite mainly occurs on the surface. The solidification, lamellar aggregation, and crystallinity index of kaolinite are more obvious after the adsorption of SDBS, but the interlayer spacing of kaolinite did not change to any significant. After the adsorption of SDBS, the intensity ratio of 1000–1008 cm −1 bands changed significantly, indicating the change of the chemical environment, and the adsorptive behaviour was chemical.
The Interferometric Synthetic Aperture Radar (InSAR) has been widely used as a powerful technique for monitoring land surface deformations over the last three decades. InSAR observations can be plagued by atmospheric phase delays; some have a roughly linear relationship with the ground elevation, which can be approximated using a linear model. However, the estimation results of this linear relationship are sometimes affected by phase ramps such as orbital errors, tidal loading, etc. In this study, we present a new approach to estimate the transfer function of vertical stratification phase delays and the transfer function of phase ramps. Our method uses the idea of multi-scale spatial differences to decompose the atmospheric phase delay into the vertical stratification component, phase ramp component, and other features. This decomposition makes the correlation between the vertical stratification phase delays and topography more significant and stable. This can establish the correlation between the different scales and phase ramps. We demonstrate our approach using a synthetic test and two real interferograms. In the synthetic test, the transfer functions estimated by our method were closer to the design values than those estimated by the full interferogram–topography correlation approach and the band-pass filtering approach. In the first real interferogram, out of the 9 sub-regions corrected by the proposed method, 7 sub-regions were outperformed the full interferogram–topography correlation approach, and 8 sub-regions were superior to the band-pass filtering method. Our technique offers a greater correction effect and robustness for coseismic deformation signals in the second real interferogram.
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