Quantitative Parameters for Rock Joint Surface Roughness

Belem, Tikou; Homand-Étienne, F.; Souley, Mountaka

doi:10.1007/s006030070001

Cited by 287 publications

(93 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Most morphological reconstructions of fracture surfaces are realized by the 3D wireframe (curved rectangle) model (Belem et al 2000;Zhang et al 2009) or TIN model (Belem et al 2000;Grasselli 2001;Cottrell 2009;Grasselli and Egger 2003;Lee et al 2011;Tang et al 2012). Elements of the 3D wireframe or TIN have their own physical properties including dip angle, dip direction, height, area, etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Estimating the three-dimensional joint roughness coefficient value of rock fractures

2017

Bull Eng Geol Environ

View full text Add to dashboard Cite

Measurement and estimation of the joint roughness coefficient (JRC) is a critical but also difficult challenge in the field of rock mechanics. Parameters for estimating JRC based on a profile derived from a fracture surface are generally twodimensional (2D), where a single or multiple straight profiles derived from a surface cannot reflect the roughness of the entire surface. It is therefore necessary to derive the threedimensional (3D) roughness parameters from the entire surface. In this article, a detailed review is made on 3D roughness parameters along with classification and discussion of their usability and limitations. Methods using Triangulated Irregular Network (TIN) and 3D wireframe to derive 3D roughness parameters are described. Thirty-eight sets of fresh rock blocks with fractures in the middle were prepared and tested in direct shear. Based on these, empirical equations for JRC estimation using 3D roughness parameters have been derived. Nine parameters (θ s , θ g , θ 2s , S sT , S sF , V an , Z sa , Z rms , and Z range ) are found to have close correlations with JRC and are capable of estimating JRC of rock fracture surfaces. Other parameters (Z ss , Z sk , V svi , V sci , S dr and S ts ) show no good correlations with JRC. The sampling interval has little influence when using volume and amplitude parameters (V an , Z sa , Z rms , and Z range ) for JRC estimation, while it influences to some extent when other parameters (θ s , θ g , θ 2s , S sT and S sF ) are used. For their easy calculation, the equations with amplitude parameters are recommended to facilitate rapid estimation of JRC in engineering practice.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Estimating the three-dimensional joint roughness coefficient value of rock fractures

2017

Bull Eng Geol Environ

View full text Add to dashboard Cite

show abstract

“…The iso-surfaces of the fractures were generated from the binary 3D image using an open-source 3D mesh generator iso2mesh with minimum smoothing to preserve the roughness [74], and the sum of the areas of the surface meshes provides an estimate of the fracture surface area. Surface roughness was quantified by the surface Z 2 parameter, which has been used and documented in details in previous studies [21,75]. The surface Z 2 parameter is the root mean square of the elemental surface slope, and has a larger value for a rougher surface for which the local surface slope varies substantially.…”

Section: Geometrical Characterizations and Permeability Simulationmentioning

confidence: 99%

Quantifying fracture geometry with X-ray tomography: Technique of Iterative Local Thresholding (TILT) for 3D image segmentation

2016

View full text Add to dashboard Cite

This paper presents a new method-the Technique of Iterative Local Thresholding (TILT)-for processing 3D X-ray computed tomography (xCT) images for visualization and quantification of rock fractures. The TILT method includes the following advancements. First, custom masks are generated by a fracture-dilation procedure, which significantly amplifies the fracture signal on the intensity histogram used for local thresholding. Second, TILT is particularly well suited for fracture characterization in granular rocks because the multi-scale Hessian fracture (MHF) filter has been incorporated to distinguish fractures from pores in the rock matrix. Third, TILT wraps the thresholding and fracture isolation steps in an optimized iterative routine for binary segmentation, minimizing human intervention and enabling automated processing of large 3D datasets. As an illustrative example, we applied TILT to 3D xCT images of reacted and unreacted fractured limestone cores. Other segmentation methods were also applied to provide insights regarding variability in image processing. The results show that TILT significantly enhanced separability of grayscale intensities, outperformed the other methods in automation, and was successful in isolating fractures from the porous rock matrix. Because the other methods are more likely to misclassify fracture edges as void and/or have limited capacity in distinguishing fractures from pores, those methods estimated larger fracture volumes (up to 80 %), surface areas (up to 60 %), and roughness (up to a factor of 2). These differences in fracture geometry would lead to significant disparities in hydraulic permeability predictions, as determined by 2D flow simulations.

show abstract

“…It is recognized that there have been several systems and approaches proposed to describe the rock fracture roughness (e.g., Lee et al, 1990;Odling, 1994;Belem et al, 2000;Tang et al, 2012). The JRC is used here primarily because it is relatively simple and quick to determine from the two-dimensional fracture profile along the shear direction.…”

Section: Rock Samplesmentioning

confidence: 99%

Effects of Displacement Velocity on Rock Fracture Shear Strengths under Large Confinements

Kleepmek¹,

Hamrat²,

Fuenkajorn³

2016

ESR

View full text Add to dashboard Cite

Triaxial shear tests are performed to assess the effects of displacement velocity and confining pressure on shear strengths and dilations of tension-induced fractures and smooth saw-cut surfaces prepared in granite, sandstone and marl specimens. A polyaxial load frame is used to apply confining pressures between 1 and 18 MPa with displacement velocities ranging from 1.15×10 -5 to 1.15×10 -2 mm/s. The results indicate that the shearing resistances of smooth saw-cut surfaces tend to be independent of the displacement velocity and confining pressure. Under each confinement the peak and residual shear strengths and dilation rates of rough fractures increase with displacement velocities. The sheared-off areas increase when the confining pressure increases, and the displacement rate decreases. The velocity-dependent shear strengths tend to act more under high confining pressures for the rough fractures in strong rock (granite) than for the smoother fractures in weaker rocks (sandstone and marl). An empirical criterion that explicitly incorporates the effects of shear velocity is proposed to describe the peak and residual shear strengths. The criterion fits well to the test results for the three tested rocks.

show abstract

Quantitative Parameters for Rock Joint Surface Roughness

Cited by 287 publications

References 11 publications

Estimating the three-dimensional joint roughness coefficient value of rock fractures

Estimating the three-dimensional joint roughness coefficient value of rock fractures

Quantifying fracture geometry with X-ray tomography: Technique of Iterative Local Thresholding (TILT) for 3D image segmentation

Effects of Displacement Velocity on Rock Fracture Shear Strengths under Large Confinements

Contact Info

Product

Resources

About