Complex pores and fissures are the main transportable channels of coal reservoir resources and key factors affecting the permeability of coal seams. Owing to different tectonic stresses, the development characteristics of pores and fissures in coal can differ significantly, which also results in differences in reservoir permeability. Therefore, analysing the influence of pore structure characteristics on coal-rock permeability is needed. In this study, four samples from the DaTong Coal Mine in the central and southern Qinshui Basin of Shanxi Province were selected for analysis. Combined computerised tomography (CT) scanning and digital image processing technology revealed the development characteristics, distribution rules, morphology, and structural differences of different coals. Based on the capillary seepage channel model and fractal geometry theory combined with the pore structure parameters obtained by CT scanning, the permeability was predicted. Furthermore, the control mechanism of the pore structure on coal permeability is discussed. The results showed that the coal porosity is positively correlated with pore diameter, pore volume, connectivity factor, and connectivity strength at the micrometer scale. Coal reservoir permeability is controlled by multiple factors, including pore size, pore volume, porosity, connectivity factor, connectivity strength, and fractal dimension, among which pore size has the most significant influence. After the complexity and connectivity of the micropore structure in coal rock were considered, the accuracy and applicability of the pore structure parameters obtained by CT scanning to predict the permeability were verified by comparing with the measured permeability.
Attenuation refers to any decrease in the power of a propagated signal through a medium. Attenuation measurement techniques include ultrasonic, resonance bar, and stressstrain methods. The stressstrain method measures elastic and viscoelastic properties in the seismic frequency range. The signals received via attenuation measurement systems using the stressstrain method can be considerably weak. Moreover, the noise in these signals causes errors when estimating the signal phase angle difference between the sample signal and probe signal, thereby reducing system precision and measurement accuracy. Accurate measurements of such phase differences are essential to the measurement of attenuation. In this paper, we measure the frequency-dependent seismic wave attenuation based on the stressstrain method and digital signal processing techniques. The system estimates the attenuation of a rock by measuring the phase shift in the stressstrain cycle. As a pre-processing method, the finite impulse response bandpass filters are designed to eliminate the influence of noise and direct current offset while ensuring that the phase difference of the measured signal remains unchanged. We compare three methods for phase difference estimation, i.e., cross-correlation, fast Fourier transform (FFT), and Hilbert transform, for different signal-to-noise ratios, sampling frequencies, data sample lengths, and true phase differences. The results show that the phase difference estimation based on FFT is the best among all three methods and can effectively improve the precision of the experimental results. Our simulation and measurement results further indicate that the attenuation measurement system achieves stable and reliable attenuation measurements in the range of 3 Hz 2,000 Hz.
Abstract-In actual construction ,there existing a big error in GPS, the geophones embedded non-vertical ,azimuth has some deviation.However ,the position information of shot point and receiver point ,and the azimuthal angle information of 3D3C geophones determine the accuracy of seismic exploration final interpretation . While through orientation and coordinate data collection ,loading the observation system information and geophone attitude information which stored in data receiving unit to the seismic data .After R-T rotation ,we obtain the common-geophone seismic gather ,obviously the continuity of the lineups are better.
Coal is a complex viscoelastic porous medium with fractal characteristics at different scales. To model the macroscale structure of coal, a fractal viscoelastic model is established, and the P-wave velocity dispersion and attenuation characteristics are discussed based on the complex modulus derived from this model. The numerical simulation results indicate that the fractional order α and relaxation time τ greatly affect the P-wave velocity dispersion and attenuation. The fractal viscoelastic model indicates a full-band velocity dispersion between 1 Hz and 104 Hz. Meanwhile, the P-wave velocity has a weaker dispersion with the fractal viscoelastic model than with the Kelvin-Voigt model and Zener model between 1 Hz and 104 Hz for the same relaxation time and elastic modulus, but the velocity at 1 Hz based on the fractal viscoelastic model is higher with the Kelvin-Voigt model and Zener model. Simultaneously, the velocities of five coal samples are tested, and the attenuation factor is calculated using a low-frequency system. The experimental results indicate a strong dispersion in coal in the range of 10–250 Hz. The classic Kelvin-Voigt model and Zener model cannot describe the dispersion characteristics of coal, but the fractal viscoelastic model can describe them well by using the appropriate fractional order and relaxation time.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.