Detection of karst caves during tunnel construction using ground‐penetrating radar and advanced drilling: A case study in Guangxi Province, China. Issue 3 (5th May 2022)

• Record Type: Journal Article
• Authors: Lan, Riyan; Liu, Zonghui; Liu, Maomao; Guan, Qiyu; Yan, Yuanfang; Sun, Huaifeng; Zhou, Dong
• Is Part Of: Near surface geophysics. Volume 20:Issue 3(2022)
• Page Start: 265
• Page End: 278
• Publication Date: 2022-05-05
• Subjects: 3D -- GPR imaging -- Karst area; Earth (Planet) -- Surface -- Periodicals; Geophysics -- Technique -- Periodicals; Engineering geology -- Periodicals; Geophysics -- Periodicals; Planets -- Surfaces; Engineering geology; Geophysics -- Technique; Geophysics; Earth (Planet); Periodicals; 550
• DOI: 10.1002/nsg.12207
• Languages: English
• ISSNs: 1569-4445

Abstract

ABSTRACT: In karst topography, hidden caves or underground rivers may imperil the safety of tunnels. It is critical to accurately detect the location and geometric shape of hidden karst caves for assessing the safety of tunnels. This paper reports a case where a large karst cave was exposed during the construction of the Nongmo tunnel in Duan County, Guangxi, China. A 2D ground‐penetrating radar survey was employed to preliminarily detect the distribution of hidden karst caves along the tunnel axis. Advanced drilling was used to obtain the velocity of electromagnetic waves and verify the 2D ground‐penetrating radar detection. Ground‐penetrating radar 3D grid detection was carried out for further detecting the geometric shape of the hidden karst caves. Rotary thrust power ratio, which is a function of drilling speed, rotating speed, propulsion pressure and torque, was proposed to reflect the integrity of the surrounding rocks. It was found that the depth of the peak value in the rotary thrust power ratio curve is consistent with that of the amplitude jump in ground‐penetrating radar A‐scans and in time–frequency distributions. The results of 3D attributes analysis indicate that due to the variation of highlights in different ground‐penetrating radar signal attributes, the obtained karst cave shapes using different attributes would be various. A multi‐attributes fusion method was proposed to generate a data volume considering various attributes. The 2D geometric shapes at different depths were obtained using the anomalous body lineament in the generated date volume slices. The 3D geometric shapes were reproduced by combining the obtained 2D geometric shapes at various depths. Based on different detection and analysis methods, the outline shape of karst caves at YK364 + 199 ∼ YK364 + 184 of the Nongmo tunnel was revealed in detail.