2016
DOI: 10.1016/j.fuel.2015.11.086
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Characterization of typical 3D pore networks of Jiulaodong formation shale using nano-transmission X-ray microscopy

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Cited by 88 publications
(43 citation statements)
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“…The 3D tomography of fiber reconstruction provides useful microstructure characterization not only on the geometrical arrangement of fiber-fiber, fiber-particle but also on the porosity distribution of the two filter media. More detail information of TXM can be found elsewhere [23].…”
Section: D Tomographymentioning
confidence: 99%
“…The 3D tomography of fiber reconstruction provides useful microstructure characterization not only on the geometrical arrangement of fiber-fiber, fiber-particle but also on the porosity distribution of the two filter media. More detail information of TXM can be found elsewhere [23].…”
Section: D Tomographymentioning
confidence: 99%
“…The resolution of FIB-SEM could be several nanometers and thus it provides a useful tool to study the three-dimensional pore structure Energies 2021, 14, 5282 2 of 12 at a nanoscale. However, a shale sample should be destroyed to perform an FIB-SEM test, and unfortunately, the sample could not be used for further study [15]. Currently, combined methods are also applied to characterize 2D and 3D pore geometry [16,17].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, the multi-scale pore structure (e.g., pore types, shapes, size and connectivity) of shales has been studied extensively using various methods [20]. For example, field emission-scanning electron microscopy (FE-SEM) [2,[13][14][15][16][17], small angle neutron scattering (SANS) [3,19,20], nuclear magnetic resonance (NMR) [25][26][27][28][29], nano-scale X-ray computed tomography (Nano-CT) [18,[30][31][32], low-pressure gas physisorption (LPGA) and mercury intrusion capillary pressure (MICP) [1,[21][22][23][24][33][34][35][36][37][38] were applied to characterize the pores in shales. Of these techniques, FE-SEM and Nano-CT were effectively applied to the quantitative characterization of OM pores, with the help of image processing, data extraction and electron tomography of subnanometric resolution to characterize the porous network in organic matter [13][14][15][16][17][18][30][31][32].…”
Section: Introductionmentioning
confidence: 99%