Experiment setup, data acquisition and processing. ... Image processing based characterisation of coal cleat networks. Int J Coal Geol (2017) A. Busch et al. ... The size of the CT scan specimen and the analytical scale of the CT image are mutually restricted, making it impossible to achieve highprecision imaging for the largersized specimens ...
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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 169:121. Google Scholar
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An image processing workflow to characterise coal cleat networks is introduced. •. Workflow is based on the distinction of perpendicular face and butt cleats. •. Geometric parameters for three different cleat networks are deduced. Characterisation of the cleat network serves as the basis for estimating the hydraulic and mechanical seam ...
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This paper considers the application of convolutional neural networks for coal petrographic images segmentation. The UNetbased model for segmentation was proposed. ... Bringemeier, D.; Scheuermann, A. Image processing based characterisation of coal cleat networks. Int. J. Coal Geol. 2016, 169, 121.
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1. Introduction. Coal reservoir is a multiscale complex system with the naturally fractured dualporosity medium consisting of cleats and matrices (Gan et al., 1972; Harpalani and Chen, 1997).The pore structure of coal matrix which is the main storage site of coalbed methane (CBM), and the fracture and cleat which are the permeable channel for CBM production, amalgamate to form the ...
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The characterization of fracture structures is key for evaluating the permeability of coalbed methane (CBM) reservoirs, and an interconnected fracture network is essential for the production of CBM. Taking the Upper Permian coal in the eastern Yunnan and western Guizhou region as an example, we systemically studied the characteristics of coal deformation and fracture development through direct ...
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The pore network model signifying that the studied coal seams are microstructurally different comprises a lateral difference in pore and cleat/fracture. ... Image processing based characterization of coal cleat networks. Int. J. Coal Geol. (2017) ... Cleatscale characterization of coal: an overview. J. Nat. Gas Sci. Eng.
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Coal seam gas (CSG) is a form of unconventional natural gas extracted from coal reservoirs. Coal is an extremely complex fractured porous medium, where gas flow is mainly controlled by its natural fracture, called "cleats." Xray microcomputed tomography (microCT) has been widely applied to obtain the 3D representation of cleat network.
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This paper reviews recent developments on the cleatscale characterisation of coal. Novel microCT imaging and image calibration methods are described. The application of microCT imaging for studying diffusion processes in ultralow permeability media is shown. The extraction of statistical information from microCT images to reconstruct cleats are demonstrated.
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Batubara yang terendapkan memberikan kenampakan geologi. Salah satu kenampakan tersebut adalah cleat pada batubara. Cleat pada batubara merupakan rengkahan yang ada pada batubara. Terdapat dua jenis cleat pada batubara, yaitu face cleat dan butt cleat, namun pada penelitian ini akan lebih memfokuskan penelitian pada face cleat.
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The butt cleats and face cleats interlace with each other and form complex fracture network in cross sections of coal block. It was assumed that all the fractures in the processed images were approximate rectangles. The lengths of rectangles represent measured values, while the widths represent averaged values.
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Carbon dioxide geological storage in deep underground oil and gas reservoirs or coal seam is considered a key technology to effectively mitigate carbon emissions. Deep coal seams are the potential host rock for CO2 storage, with chemical reactions occurring when coal is exposed to CO2saturated brine. However, limited studies have been conducted to reveal the effect of chemical reaction ...
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select article Image processing based characterisation of coal cleat networks. ... Research article Full text access Image processing based characterisation of coal cleat networks. J. Busse, de Dreuzy, S. Galindo Torres, D. Bringemeier, A. Scheuermann. Pages 121 View PDF.
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the second two sets of face cleats intersected by butt cleats and the third parallel face cleats only. Keywords cleat geometry, image processing, coal properties, CT scans 1. Introduction Coal cleat networks Coal is characterised by its unique microstructure of a low permeable porous matrix intersected by a network of face and butt cleats.
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Digital image processing is the use of computer algorithms to conduct image processing on digital images. A raw image of sample B is shown in Fig. 2 (a). The brightness contrasts shown in the images represent the Xray attenuation in each material, which depends on the atomic number and the density of the material (Van Geet et al., 2001).Voids in the tested coal sample are shown in black in ...
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DOI: / 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 Andres Galindo Torres and Detlef Bringemeier and Alexander Scheuermann}, journal={International Journal of Coal Geology ...
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Image processingbased characterisation of coal cleat networks. International Journal of Coal Geology 169, 121. | 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 Coal ...
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Image processing based characterisation of coal cleat networks. Int. J. Coal Geol. (2017) Bustin et al. Abrupt changes (jumps) in reflectance values and chemical compositions of artificial charcoals and inertinite in coals ... Coal cleat reconstruction using microcomputed tomography imaging. Fuel (2016) S. Karimpouli et al. Stochastic ...
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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 characterization. ... Image processing based characterisation of coal cleat networks. International Journal of Coal Geology, Volume 169, 2017, pp. 121.
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Mostaghimi et al. [26] has reviewed recent developments in microscale characterisation of coal. Methane production is mainly controlled by coal permeability [27], [28], which is governed by the geometrical properties of the cleat network, including orientation, length, spacing and aperture size [26], [29], [30]. To obtain the geometrical ...
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Observation on the Tanjung Enim coal outcrops has been conducted to evaluate coal and cleat characteristics, particularly those occurring at Suban and Air Laya Putih (ALP) sites. Tectonically, the region is located in the South Palembang Subbasin. In this region, there are four to five coal seams dipping to the SW direction.
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S. Mazumder, K.H. A. A. Wolf, K. Elewaut, and R. Ephraim, "Application of Xray computed tomography for analyzing cleat spacing and cleat aperture in coal samples," International Journal of Coal ... and A. Scheuermann, "Image processing based characterisation of coal cleat networks," International Journal of Coal Geology, vol. 169, pp ...
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DigiCoal toolbox is a powerful tool for characterising fractured coal sample on multiple length scales based on 3D microCT data. It is divided into four building blocks. The building block of segmented image preprocessing can prepare the data to be favourable for subsequent quantitatively analyses.
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The form definition of a cleat in a coal specimen is based on the widely accepted concept of an orthogonal network of butt and face cleats with both normal to the bedding plane (Fig. 1). For the study of cleat occurrence and geometry in 2D image processing, a cleat has been defined as a feature that is longer than wide and aligned straight.
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Image processing based characterisation of coal cleat networks ... Characterisation of the cleat network serves as the basis for estimating the hydraulic and mechanical seam properties which in ...
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Cleats/fractures play a vital role in gas extraction from coal bed methane reservoirs. As such, fractures are identified in microcomputed tomography images by segmentation in detailed fracture characterization studies. Conventional segmentation methods include thresholdingbased, region growing, and hybrid methods. In digital images, these methods are unable to differentiate fractures from ...
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Estimates 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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Image processing based characterisation of coal cleat networks J. Busse *a, de Dreuzy b, Sergio Galindo Torres a, D. Bringemeier a,c, A. Scheuermann a *Corresponding author:, +61 40 1906 327 a Geotechnical Engineering Centre, School of Civil Engineering, University of Queensland, St. Lucia, QLD, Australia b
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Image processing based characterisation of coal cleat networks. ... Characterisation of the cleat network serves as the basis for estimating the hydraulic and mechanical seam properties which in turn are fundamental for flow and geomechanical modelling in the context of underground coal mining. Cleat and cleat network geometry can be described ...
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Conclusions. DigiCoal toolbox is a powerful tool for characterising fractured coal sample on multiple length scales based on 3D microCT data. It is divided into four building blocks. The building block of segmented image preprocessing can prepare the data to be favourable for subsequent quantitatively analyses.
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Image processing based characterisation of coal cleat networks J. Busse *a, de Dreuzy b, Sergio Galindo Torres a, D. Bringemeier a,c, A. Scheuermann a *Corresponding author:, +61 40 1906 327 a Geotechnical Engineering Centre, School of Civil Engineering, University of Queensland, St. Lucia, QLD, Australia b
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