Determination of roughness coefficient in 3D digital representations of rocks

Abstract

The roughness property of rocks is significant in engineering studies due to their mechanical and hydraulic performance and the possibility of quantifying flow velocity and predicting the performance of wells and rock mass structures. However, the study of roughness in rocks is usually carried out through 2D linear measurements (through mechanical profilometer equipment), obtaining a coefficient that may not represent the entire rock surface. Thus, based on the hypothesis that it is possible to quantify the roughness coefficient in rock plugs reconstructed three-dimensionally by the computer vision technique, this research aims to an alternative method to determine the roughness coefficient in rock plugs. The point cloud generated from the 3D model of the photogrammetry process was used to measure the distance between each point and a calculated fit plane over the entire rock surface. The roughness was quantified using roughness parameters ($$R_a$$ R a ) calculated in hierarchically organized regions. In this hierarchical division, the greater the quantity of division analyzed, the greater the detail of the roughness. The main results show that obtaining the roughness coefficient over the entire surface of the three-dimensional model has peculiarities that would not be observed in the two-dimensional reading. From the 2D measurements, mean roughness values ($$R_a$$ R a ) of $$0.35\,\upmu \hbox {m}$$ 0.35 μ m and $$0.235\,\upmu \hbox {m}$$ 0.235 μ m were obtained for samples 1 and 2, respectively. By the same method, the results of the $$R_a$$ R a coefficient applied three-dimensionally over the entire rocky surface were at most $$0.165\,\upmu \hbox {m}$$ 0.165 μ m and $$0.166\,\upmu \hbox {m}$$ 0.166 μ m , respectively, showing the difference in values along the surface and the importance of this approach.

Experimental study on the fracture surface morphological characteristics and permeability characteristics of sandstones with different particle sizes

“…Furthermore, as the values of pore pressure and gas pressure increase, the rate of permeability decrease also diminishes. (2) The relationship between permeability and pore pressure for different lithologies is fitted using exponential functions. The formula for the fitting function and the fitting coefficients are shown in the figure, with all fitting correlation coefficients exceeding 0.97, indicating an excellent fit.…”

“…1 The roughness coefficients proposed by the scholars concerned have been widely used in engineering practice and have been found to be more related to the roughness parameters of threedimensional structural surfaces. 2,3 The presence of joints affects the mechanical properties of the rock mass and the way the energy source propagates within it, and changes the damage mode of rock mass, affecting the strength and stability of rock mass, and the three-dimensional visualization and quantitative analysis of damage section morphology under different stressing methods and water-filled conditions. [4][5][6][7][8][9][10][11] Anisotropic characterization of structural faces formed under cleavage and shear was carried out and their influence on shear mechanical properties was studied.…”

“…At present, Barton has conducted many meaningful research on the morphological characteristics of rock sections and seepage characteristics 1 . The roughness coefficients proposed by the scholars concerned have been widely used in engineering practice and have been found to be more related to the roughness parameters of three‐dimensional structural surfaces 2,3 . The presence of joints affects the mechanical properties of the rock mass and the way the energy source propagates within it, and changes the damage mode of rock mass, affecting the strength and stability of rock mass, and the three‐dimensional visualization and quantitative analysis of damage section morphology under different stressing methods and water‐filled conditions 4–11 .…”