A Comparative Study of the Influence of Volumetric Joint Counts (Jv) and Resistivity on Rock Quality Designation (RQD) Using Multiple Linear Regression

• Published in: Pure and applied geophysics Vol. 180; no. 6; pp. 2351 - 2368
• Main Authors: Junaid, Muhammad, Abdullah, Rini Asnida, Sa’ari, Radzuan, Shah, Kausar Sultan, Ullah, Rafi
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01-06-2023; Springer Nature B.V
• Subjects: Boreholes; Comparative analysis; Comparative studies; Correlation; Drilling; Earth and Environmental Science; Earth Sciences; Electrical resistivity; Empirical analysis; Geophysics/Geodesy; Parameters; Quality assessment; Regression analysis; Rock; Rock mass rating; Rocks; Seismic velocities; Slope stability; Surveys; Tomography; Unmanned aerial vehicles; Velocity; 2D electrical resistivity; unmanned aerial vehicle; RQD; multiple linear regression
• ISSN: 0033-4553; 1420-9136
• DOI: 10.1007/s00024-023-03260-8

Rock quality designation (RQD) index is useful for assessing rock mass quality and slope instabilities. The traditional method of calculating RQD, such as drilling, suffers several limitations. Therefore, RQD has been correlated with several parameters, such as fracture frequency (
λ
), Volumetric Joint Count (Jv) and seismic velocity index. However, all the correlations in previous studies considered single parameters such as Jv and seismic velocity index. This study deployed an integrated unmanned aerial vehicle, 2D electrical resistivity tomography (2D ERT) and borehole survey to correlate and compare the influence of Jv and resistivity on RQD. A single linear regression analysis (SLR) in this research suggests that RQD and Jv are inversely proportional, while resistivity and RQD are directly proportional. In line with this, the negative coefficient (− 2.85) for Jv while positive (0.003) for resistivity obtained using multiple linear regression (MLR) modelling reflects that Jv and resistivity are negatively correlated while RQD and resistivity are positively correlated. Empirical correlation obtained via MLR revealed that the Jv influences the RQD more than resistivity. Based on the strong correlation between RQD and resistivity, it is concluded that resistivity is highly sensitive to the degree of rock mass fracturing. This allows us to conclude that the 2D ERT survey is a reliable and expeditious technique for subsurface rock mass characterization.