首页|Empirical prediction of hydraulic aperture of 2D rough fractures:a systematic numerical study

Empirical prediction of hydraulic aperture of 2D rough fractures:a systematic numerical study

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This study aims to propose an empirical prediction model of hydraulic aperture of 2D rough fractures through numerical simulations by considering the influences of fracture length,average mechanical aperture,minimum mechanical aperture,joint roughness coefficient(JRC)and hydraulic gradient.We generate 600 numerical models using successive random additions(SRA)algorithm and for each model,seven hydraulic gradients spanning from 2.5 × 10-7 to 1 are considered to fully cover both linear and nonlinear flow regimes.As a result,a total of 4200 fluid flow cases are simulated,which can provide sufficient data for the prediction of hydraulic aperture.The results show that as the ratio of average mechanical aperture to fracture length increases from 0.01 to 0.2,the hydraulic aperture increases following logarithm functions.As the hydraulic gradient increases from 2.5 × 10-7 to 1,the hydraulic aperture decreases following logarithm functions.When a relatively low hydraulic gradient(i.e.,5 × 10-7)is applied between the inlet and the outlet boundaries,the streamlines are of parallel distribution within the fractures.However,when a relatively large hydraulic gradient(i.e.,0.5)is applied between the inlet and the outlet boundaries,the streamlines are disturbed and a number of eddies are formed.The hydraulic aperture predicted using the proposed empirical functions agree well with the calculated results and is more reliable than those available in the preceding literature.In practice,the hydraulic aperture can be calculated as a first-order estimation using the proposed prediction model when the associated parameters are given.

fluid flowrough fracture surfacemechanical aperturehydraulic aperturepredictive model

Xiaolin WANG、Shuchen LI、Richeng LIU、Xinjie ZHU、Minghui HU

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State Key Laboratory for Geomechanics and Deep Underground Engineering,China University of Mining and Technology,Xuzhou,221116,China

National Key R&D Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNatural Science Foundation of Jiangsu Province,ChinaAssistance Program for Future Outstanding Talents of the China University of Mining and TechnologyPostgraduate Research & Practice Innovation Program of Jiangsu Province

2022YFE01283005237911452379113BK202115842023WLKXJ187KYCX23 2746

2024

10.1007/s11707-023-1089-3

地球科学前沿
高等教育出版社

地球科学前沿

CSTPCD
影响因子：0.585
ISSN：2095-0195
年,卷(期)：2024.18(3)
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