WEBJun 25, 2015 · Image processing based characterisation of coal cleat networks ... the context of underground coal mining. Cleat and cleat network geometry can be described as a function of frequency, aperture ...
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WEBMar 1, 2017 · To address this issue, an imageprocessing workflow is introduced that begins with unpaired domain transfer by cycleconsistent adversarial network, which is used to transfer synchrotronbased ...
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WEBJun 15, 2020 · This paper develops the framework of constructing imagebased Fracture Pipe Network Model (FPNM) for fractured coal samples to efficiently estimate the permeability. ... Cleatscale characterisation of coal: an overview. J. Nat. Gas Sci. Eng., 39 ... Image Processing Toolbox User's Guide (R2016b). 2015 [cited Revised for .
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WEBJun 1, 2018 · Based on the scanning at two scales, the detail structures of coal samples are reconstructed with the image processing technique, which realizes the multiscale qualitative and quantitative ...
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WEBMay 1, 2019 · Coal characteristics analysed in this paper include cleat geometry, topology of cleat network, degree of mineralisation, and roughness of cleat surfaces. MicroCT scanning procedures to obtain ...
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WEBOct 1, 2015 · The coal beds that cleat network is well conductive to the connected fracture can be an improved target area for CBM production. During CBM production, a variety of flow regimes are available ...
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WEBDOI: / Corpus ID: ; Image processing based characterisation of coal cleat networks article{Busse2017ImagePB, title={Image processing based characterisation of coal cleat networks}, author={Julia Busse and JeanRaynald de Dreuzy and Sergio A. G. Torres and Detlef Bringemeier and Alexander .
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WEBAug 27, 2021 · Abstract Accurate characterization of the initiation of hydraulic fractures is crucial for understanding the formation of multiple hydraulic fracture networks in coal seams in coalbed methane extraction and disaster prevention. To this end, hydraulic fracturing has been extensively employed in the reservoir stimulation of shale and .
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WEBOct 1, 2015 · A workflow for extracting coal cleats, including sample preparation, image acquisition, and image processing has been established (Ramandi et al., 2015;Mostaghimi et al., 2017). ...
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WEBAug 1, 2020 · Though no direct permeability calculation is involved in the preprocessing. ... Image processing based characterisation of coal cleat networks. Int. J. Coal Geol. (2017) ... Due to a limited number of research dedied to imagebased porescale modelling in coal, we develop a hybrid numerical model that combines the Hagen .
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WEBFigure 6 a. Initial feature and the principle of b. dilation and c. erosion of image features using a diskshaped element with radius r to reconnect features originally being separated due to the binary process "Image processing based characterisation of .
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WEBAug 27, 2017 · Coal characteristics analysed in this paper include cleat geometry, topology of cleat network, degree of mineralisation, and roughness of cleat surfaces. MicroCT scanning procedures to obtain ...
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WEBImage processingbased characterisation of coal cleat networks. International Journal of Coal Geology 169, 1–21. | Image processingbased characterisation of coal cleat networks. Crossref | GoogleScholar Google Scholar | Connell LD, Mazumder S, Marinello S, Sander R, Camilleri M, Pan Z, Heryanto D (2013). Characterisation of Bowen Basin .
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WEBJul 1, 2019 · The main purpose of image processing is to perform various processing operations on the image to improve its visual effect and lay the foundation for subsequent target recognition. ... It should be noted that the natural cleat of coal has an effect on the gas permeation system, and the corresponding calculation model should be changed ...
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WEBEstimates of these parameters can be made from imagebased threedimensional (3D) characterization of coal cleats using Xray microcomputed tomography (μCT). One key step in this process, after cleat extraction, is the separation of individual cleats, without which the cleats are a connected network and statistics for different cleat sets ...
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WEBJun 1, 2017 · Characterization of coalbed methane reservoirs is a challenging task because of complex petrophysical properties of coal. Coal cleat system has a key role in permeability of gas through coalbed.
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WEBNov 7, 2016 · Abstract. Coal seam gas is an unconventional resource for natural gas that is becoming popular due to its. environmental benefit and abundance. This paper reviews recent developments on the pore ...
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WEBDec 1, 2019 · Coal permeability is known to be affected by the sorptioninduced strain. Indeed, coal swells with gas sorption and shrinks with desorption, which is likely to modify the cleat aperture and thus the permeability. Coal permeability evolution is crucially important for either Coalbed Methane production (CBM) or Carbon dioxide Capture and .
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WEBDec 1, 2017 · A characterisation framework is developed to determine if the developedDFN models can preserve the topological properties of the coal cleat network found in microCT data and it is concluded that the topology of the DFN models are closer to that of the realistic cleat networks that do not have segmentationinduced pores. .
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WEBGalindo Sergio., Bringemeier D. and Scheuermann A., Image processing based characterisation of coal cleat networks, ... An approach on determination on coal quality using digital image processing, Int. Journal of Engineering Research and Appliions 5 (12) (2015), 38 ...
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WEBApr 2, 2024 · Imagebased automatic fracture extraction methods have many practical appliions in geological and engineering. Fracture identifiion and quantitative characterization require the means of interpreting and statistically analyzing image data. In comparison to traditional digital image processing methods, supervised semantic .
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WEBJun 4, 2021 · A 2D numerical model is constructed incorporating a real coal cleat network. A coupled hydromechanical model that incorporates fracture deformation, damage evolution and stressdependent permeability is used for the simulation. ... Image processing based characterisation of coal cleat networks. Int J Coal Geol 169:1–21. Google Scholar
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