Research on the detection of underground pedestrian passage by high precision gravity exploration
YANG Min1,2,3,8(), XU Xin-Qiang1,8(), CHEN Ming4, Ji Xiao-Lin5, WANG Wan-Yin6,7, ZHAO Dong-Ming3, ZHOU Wei1, ZHANG Yi-Mi6,7
1. Xi’an Division of Surveying and Mapping, Xi’an 710054, China 2. Hubei Subsurface Multi-scale Imaging Key Laboratory, School of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China 3. Institute of Geospatial Information, Information Engineering University, Zhengzhou, 450001, China 4. Guangdong Geological and Geophysical Engineering Investigation Institute, Guangzhou 510000, China 5. Information and Navigation College, Air Force Engineering University 710007, China 6. School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710054, China 7. National Engineering Research Center of Offshore Oil and Gas Exploration, Beijing 100028, China 8. Key Laboratory of Smart Earth, Xi’an 710054, China
Underground cavities with shallow burial and small scale are difficult to detect. With the development of gravity sensing technology, the accurate and rapid acquisition of micro-gravity variations brings new opportunities for detecting underground cavities, and it has wide research and practical value for the detection of small-scale underground cavities. This paper systematically analyzes and studies underground cavities from three aspects: gravity basic theory, gravity detection technology, and gravity data processing and inversion. Under given body size and gravity data accuracy, the maximum burial depth of gravity detection is calculated using the bisection method. High-density acquisition and high-precision gravity detection methods are applied to the actual detection of an underground pedestrian tunnel in a certain area of a passenger station. A set of high-precision gravity grid data is obtained. The theoretical research and measurement results indicate that existing gravity instruments have the ability to detect underground cavities. By using the minimum curvature potential field separation method, 2.5D interactive inversion and the target area recognition three-dimensional physical property fast inversion method, the approximate SN distribution and burial depth of the underground pedestrian tunnel are obtained, which is approximately 2.5~5 m, consistent with the actual situation. This study has developed a complete gravity exploration process for detecting underground cavities, and it has certain reference value.
杨敏, 徐新强, 陈明, 纪晓琳, 王万银, 赵东明, 周巍, 张义蜜. 基于高精度重力勘探对地下空洞的探测研究[J]. 物探与化探, 2024, 48(3): 876-883.
YANG Min, XU Xin-Qiang, CHEN Ming, Ji Xiao-Lin, WANG Wan-Yin, ZHAO Dong-Ming, ZHOU Wei, ZHANG Yi-Mi. Research on the detection of underground pedestrian passage by high precision gravity exploration. Geophysical and Geochemical Exploration, 2024, 48(3): 876-883.
Wang Q B, Jiang D, Zhao D M, et al. Underground vacancy detection based on vertical gravity gradient measurements[J]. Journal of Geomatics Science and Technology, 2011, 28(3):161-168.
[2]
江东. 重力梯度测量探测地下人造空洞的研究[D]. 郑州: 解放军信息工程大学, 2012.
[2]
Jiang D. Underground man-made vacancy detection from Gravity gradiometry[D]. Zhengzhou: PLA Information Engineering University, 2012.
[3]
Fajklewicz Z J. Gravity vertical gradient measurements for the detection of small geologic and anthropogenic forms[J]. Geophysics, 1976, 41(5):1016-1030
[4]
Butler D K. Microgravimetric and gravity gradient techniques for detection of subsurface cavities[J]. Geophysics, 1984, 49(7):1084-1096
[5]
Romaides A J, Battis J C, Sands R W, et al. A comparison of gravimetric techniques for measuring subsurface void signals[J]. Journal of Physics, 2001, 34(3):433-443.
Hu Q, Wu J C, Zheng E L, et al. Detecting underground cavities in urban areas with micro-gravity measurements[J]. Geotechnical Investigation & Surveying, 2015, 43(11):74-78.
Liu P L, Qiao T R, Zhang H X. Detection methods and analysis of old air-raid shelters[J]. Surveying and Mapping and Spatial Geographic Information, 2021, 44(4):189-191.
Wang X Y, Liu J, Sun P Y, et al. Rapid detection of urban underground cavity based on vehicle gravity measurement platform[J]. Journal of Jilin University:Earth Science Edition, 2019, 49(3):838-845.
Xu Y J, Chen M, Wu Z H, et al. Application of high precision gravity in the research of urban underground space exploration[J]. Journal of Geology, 2021, 45(4):425-432.
[10]
Agocs W B. Least-squares residual anomaly determiration[J]. Geoghysics, 1951, 16(4):686-696.
Cheng F D, Liu D J, Yao R X. A study on the identification of regional and local gravity fields[J]. Computing Techiques for Geophysical and Geochemical Exploration, 1987, 9(1):1-9.
Ji X L, Wang W Y, Qiu Z Y. The research to the minimum curvature technique for potential field data separation[J]. Chinese Journal of Geophysics, 2015, 58(3):1042-1058.
Wang Q B, Zhang C, Huang J X, et al. Research on techniques and strategies in searching and detecting artificial underground cavity by gravity surveying[C]// The 13rd National Security Geophysical Workshop, 2017.
[18]
张超. 搜索地下空洞的重力反演技术与方法研究[D]. 郑州: 解放军信息工程大学, 2017.
[18]
Zhang C. Research on techniques and methods of gravity inverting in searching underground cavity[D]. Zhengzhou: PLA Information Engineering University, 2017.
[19]
Moazam S, Aghajani H, Kalate A N. The priority of microgravity focusing inversion in 3D modeling of subsurface voids[J]. Environmental Earth Sciences, 2021,80:343.
[20]
Yang M, Xu X, Wang W, et al. 3D gravity fast inversion based on Krylov subspace methods[J]. Journal of Geophysics and Engineering, 2024,21:29-46.
[21]
曾华霖. 重力场与重力勘探[M]. 北京: 地质出版社, 2005.
[21]
Zeng H L. Gravity field and gravity exploration[M]. Beijing: Geological Publishing House, 2005.
Zhang Y M, Wang W Y, Xiong S Q. Research on the vertical recognition ability of gravity and magnetic data of point (line) source model with given survey accuracy[J]. Chinese Journal of Geophysics, 2020, 63(11):4220-4231.
Lu H, Sun Y, Zhou M X, et al. Experiment and forward modeling analysis of microgravity detection of urbanunderground space[J]. CT Theory and Applications, 2022, 31(5):543-556.
[24]
Yang M, Wang W, Welford J K, et al. 3D gravity inversion with optimized mesh based on edge and center anomaly detection[J]. Geophysics, 2019, 84(3):G13-G23.