An optimum solution for coal permeability estimation from mesoscopic scale calibrated stochastic and deterministic discrete fracture network models

Bandyopadhyay, Krishanu; Mallik, Jyotirmoy

doi:10.1016/j.fuel.2022.125626

Cited by 6 publications

(2 citation statements)

References 56 publications

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“…The new fracture direction generated during the pyrolysis of the oil shale reservoir is mainly along the bedding direction. The discrete fracture network (DFN) model obtained by random simulation has been widely recognized by many scholars. − …”

Section: Random Fracture and Thm Coupling Modelmentioning

confidence: 99%

Analysis of Effective Pyrolysis Zone and Heat Loss in Oil Shale Reservoir with Random Fractures

Yu,

Tang,

Zhang

et al. 2023

ACS Omega

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Section: Random Fracture and Thm Coupling Modelmentioning

confidence: 99%

Analysis of Effective Pyrolysis Zone and Heat Loss in Oil Shale Reservoir with Random Fractures

Yu,

Tang,

Zhang

et al. 2023

ACS Omega

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“…The change in coal composition and rupture strength influence the rheological characteristics of coal system reservoirs [26]. Bandyopadhyay et al [27] proposed the deployment of a calibrated discrete fracture network (DFN) modeling technology based on mesoscale coal images. Furthermore, a sensitivity analysis of the key fracture properties was performed to quantify their impact on coal permeability.…”

Section: Introductionmentioning

confidence: 99%

Fractal Study of the Development Law of Mining Cracks

Wu,

Xie,

et al. 2023

Fractal Fract

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Studying mining fracture development is vital for geotechnical and mining engineering and geological disaster prevention. This research assesses crack effects on rock mass stress equilibrium during coal mining, potentially causing geological disasters such as land subsidence and landslides. Using fractal geometry theory, the present study investigates the development of horizontal and vertical mining cracks, revealing their propagation patterns. The fractal dimension generally increases as the propulsion distance increases; however, fluctuations vary from 250 to 287.5 m, forming a wavering line chart. The proportion of mining fracture area relative to mining space area increases with greater propulsion distance, indicating expanded upward mining space due to separation layers. The horizontal distribution of mining cracks persists, while the vertical distribution decreases, suggesting ground subsidence results from upward transmission. The fastest increase in fractal dimension occurs at 87.5–100 m. At 250 m, it peaks at 1.4136, indicating complex crack structures. During propulsion, the fractal dimension decreases due to upward mining space expansion through overlying rock layer collapse, forming new cracks. The proportion of mining crack area to mining space area increases gradually throughout the mining process. The present study presents a simulation model for crack identification, noting limitations in identifying tiny cracks.

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A combination of Light Detection and Ranging with Digital Panoramic Borehole Camera System in fracture mapping to characterize discrete fracture networks

Zhang

Shu

Shen

2023

Bull Eng Geol Environ

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An optimum solution for coal permeability estimation from mesoscopic scale calibrated stochastic and deterministic discrete fracture network models

Cited by 6 publications

References 56 publications

Analysis of Effective Pyrolysis Zone and Heat Loss in Oil Shale Reservoir with Random Fractures

Analysis of Effective Pyrolysis Zone and Heat Loss in Oil Shale Reservoir with Random Fractures

Fractal Study of the Development Law of Mining Cracks

A combination of Light Detection and Ranging with Digital Panoramic Borehole Camera System in fracture mapping to characterize discrete fracture networks

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