Characteristics of a Multi-scale Fracture Network and Its Contributions to Flow Properties in Anthracite

Abstract

Fractures are the main flow channels in the coal and play a significant role in coalbed methane (CBM) production. For a comprehensive understanding of the importance of multi-scale fractures in coal, an integrated approach of laboratory experiments and numerical simulation was used to analyze the characteristics of coal fracture networks in the samples collected from the southern Qinshui Basin, China. X-ray micro-computed tomography (micro-CT) was conducted to study the geometrical and topological parameters of multi-scale fractures in samples of different sizes. The fracture parameters, including fracture equivalent diameter, angle, orientation, spacing, fracture porosity, fractal dimension, and intersection point density, were quantitatively measured from micro-CT images of the coal samples. These micro-CT data were used to generate the multi-scale discrete fracture networks (DFNs), followed by the simulation of the gas flow behavior in coal fractures using COMSOL modeling software. The results show that the fracture equivalent diameter, fracture porosity, fractal dimension, and intersection point density are higher in the bright coal lithotype, indicating the heterogeneity distribution of the fractures in different coal lithotypes. The results depict a decline in the fracture equivalent diameter, fracture angle, fracture spacing, fracture porosity, and fractal dimension with the decrease in the sample size. However, the intersection point density of fractures shows the opposite trend. According to the fracture parameters, the fracture network development degree decreases, while the relation between different fractures (connectively) increases with the decrease of the fracture scale. The DFN simulation illustrates that the permeability increases from semi-dull coal (0.02 mD) to bright coal (0.025 mD). The long fractures contribute to the fracture connectivity network by connecting to smaller fractures and might show high-flow velocity in coal seams. Overall, the results indicate that the semi-bright coal and bright coal are beneficial to the production of CBM for the development of fractures. The findings of this study can help for a better understanding of the distribution of fractures in different coal lithotypes and will be favorable for enhancing CBM production.

Review on Applications of X-ray Computed Tomography for Coal Characterization: Recent Progress and Perspectives

“…In the 3D reconstruction of the coal microstructure, the specific grayscale ranges of pore fractures, minerals, and matrix normally determined by threshold segmentation. , As an important basis for 3D reconstruction, the accuracy of threshold determines the accuracy of the final 3D reconstruction model, and the existence of noise in the image makes deviation from the real image inevitable . Therefore, the CT images usually require further processing, including adjusting the image contrast and filtering the scatter dots noise prior to segmentation. − Using the preprocessed three-dimensional (3D) image, the threshold segmentation is calibrated along with measured porosity (MIP or other methods), and then used to obtain the 3D coal microstructure (see Figure ). ,, …”

Development Characteristics and Finite Element Simulation of Fractures in Tight Oil Sandstone Reservoirs of Yanchang Formation in Western Ordos Basin

“…The sweet spot prediction of fractured reservoirs is a hot spot in the current petroleum industry research (Borgia et al, 1996;Du and Yang., 2004;Barton et al, 2009;Cai., 2020;Cheng et al, 2020). Fractured reservoirs have strong heterogeneity, so traditional fracture evaluation methods face many challenges, such as the fine identifications of fractured segments and fracture sweet spots of tight reservoirs based on geophysical methods (Baecher., 1983;Bhatti et al, 2020;Chen., 2020;Fan et al, 2020a;Han et al, 2021;Liu et al, 2021a). At present, the conventional methods for identifying and evaluating reservoir fractures include core observations, conventional and imaging logging (Dowd et al, 2007;Casini et al, 2016;Li et al, 2019;Cao et al, 2020;Fan et al, 2020b;Liu et al, 2020a;Bukar et al, 2021).…”

Fine Logging Evaluation of Fractures in Continental Tight Oil Sandstone Reservoirs of Yanchang Formation in the Ordos Basin

“…Natural fractures are commonly developed in tight oil sandstone reservoirs, and the degree of fracture development is a key factor for whether low permeability reservoirs can obtain high and stable productivity (Casini et al, 2016;Bhatti et al, 2020;Bukar et al, 2021). Fractures have well geophysical responses in well logs, so well logs are often used to identify natural fractures (Hu et al, 2020;Guo et al, 2021;Han et al, 2021;He et al, 2021). At present, the research methods of tight reservoir fractures around the world include core observation, experimental testing, conventional, imaging logging and seismic prediction (Nakaya and Nakamura., 2007;Lai et al, 2018;Li., 2021).…”

“…The comprehensive evaluation of fractures involves the genesis mechanism, prediction and distribution law of fractures (Santosh and Feng., 2020;Wang and Wang., 2021;Xu and Dowd., 2010;Li, et al, 2020). Logging identifications of fracture are generally based on a single conventional log series or based on multiple log series (Dong et al, 2018;Chen et al, 2021;Han et al, 2021). Among them, fracture identification via multi-logging parameters has high fracture identification accuracy.…”

“…Among them, fracture identification via multi-logging parameters has high fracture identification accuracy. Fracture identification models with multiple logging parameters are usually constructed on the basis of multiple regression method, differential equivalent model, principal component analysis, and variable-scale fractal theory (Yin and Wu., 2020;Han et al, 2021).…”