吉林大学学报(地球科学版) ›› 2026, Vol. 56 ›› Issue (4): 1449-1464.doi: 10.13278/j.cnki.jjuese.20250005

• 地球探测与信息技术 • 上一篇    下一篇

被动源面波成像在岩溶发育区探测中的应用

咸海龙1, 2,吴陈耿1, 2,闫英伟3,苏荣华4,李静5,孙睿哲5,刘聪1, 2,王好龙1, 2,皮伟1, 2   

  1. 1.河南省地球物理空间信息研究院有限公司,郑州 450000
    2.河南省地质物探工程技术研究中心,郑州 450000
    3.南方科技大学地球与空间科学系,广东 深圳 518055
    4.军事科学院国防工程研究院,北京 100036
    5.吉林大学地球探测科学与技术学院,长春 130026
  • 收稿日期:2025-01-06 出版日期:2026-07-26 发布日期:2026-08-11
  • 通讯作者: 苏荣华(1983—),男,高级工程师,主要从事工程伪装研究,E-mail: 382438200@qq.com
  • 作者简介:咸海龙(1986—),男,高级工程师,主要从事地震资料处理及解释研究,E-mail: xianhaizhilong@163.com
  • 基金资助:
    国家科技重大专项(2025ZD1008400);吉林省全国重点实验室重大专项(SKL202502020JC);教育部基础学科和交互学科突破计划项目(JYB2025XDXM803)

Application of Passive Surface-Wave Imaging to the Detection of Karst Development Areas

Xian Hailong1,2, Wu Chengeng1, 2, Yan Yingwei3, Su Ronghua4, Li Jing5, Sun Ruizhe5, Liu Cong1,2, Wang Haolong1, 2, Pi Wei1, 2   

  1. 1. Henan Institute of Geophysical Spatial Information Co., Ltd, Zhengzhou 450000, China
    2. Henan Geological and Geophysical Engineering Technology Research Center, Zhengzhou 450000, China
    3.  Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China
    4.  Defense Engineering Institute, AMS, PLA, Beijing 100036, China
    5.  College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China
  • Received:2025-01-06 Online:2026-07-26 Published:2026-08-11
  • Supported by:
    the National Science and Technology Major Project  (2025ZD1008400),the Major Special Project for National Key Laboratories of Jilin Province (SKL202502020JC) and the Basic Discipline and Interdisciplinary Breakthrough Program of the Ministry of Education (JYB2025XDXM803)

摘要: 岩溶是城市环境中的一种典型地质病害体,其发育会影响地表建筑的稳定性与安全性。相比于围岩,岩溶的横波速度较低,以低速异常体形式体现。环境噪声中的面波对横波速度敏感,其中的高阶面波对低速异常更加敏感。然而,由于使用了全局算法,目前的分阶段多阶面波频散曲线反演方法计算量较大。为此,本文对其做出改进:在第一阶段反演中使用局部优化算法中的预处理最速下降算法反演识别出的基阶面波频散曲线;在第二阶段反演中使用模式搜索算法反演所有的频散数据,并在迭代中使用Kuhn-Munkres算法动态确定未定阶次频散数据的阶次。以四层含软弱夹层地质模型反演测试为例,测试改进后方法识别浅层介质低速夹层结构的效果;并将其应用于深圳市龙岗区岩溶发育区的实际被动源数据,以评估改进后反演方法的实用性。结果表明:高阶面波频散数据是独立于基阶面波频散数据的观测约束,可提高反演结果的精度和垂向分辨率,增强对软弱夹层的识别能力;在深圳市龙岗区成功识别出了测线下方的岩溶发育区。高阶面波频散能量缺失与混叠是浅层面波数据中的一种常见现象,在多阶面波频散曲线反演中需要动态识别高阶面波频散数据的阶次。

关键词: 被动源面波, 岩溶发育区, 分阶段反演, 多阶反演, 横波速度

Abstract: Karst is a typical geological hazard in urban environments, and its development can affect the stability and safety of the infrastructures. Compared with the surrounding bedrock, the S-wave velocity of karst is relatively lower, and appear as low-velocity anomalies. Surface waves within ambient noise are highly sensitive to the S-wave velocity of underground media, with the higher-mode surface waves demonstrating even greater sensitivity to such low-velocity anomalies. However, the conventional staged inversion schemes for multimode dispersion curves rely on global optimization algorithms, resulting in substantial computational costs. To address this limitation, we propose an improved inversion workflow. In the first stage, the preconditioned steepest descent method, a local optimization algorithm, is employed to invert the identified fundamental-mode dispersion curve. In the second stage, the pattern search algorithm is utilized to invert all available dispersion data. During the iteration, the Kuhn-Munkres algorithm is implemented to dynamically assign the mode-orders to unlabeled dispersion points. The efficacy of the proposed method in characterizing shallow low-velocity interlayers is validated via synthetic tests based on a four-layer geological model containing a soft interlayer. Furthermore, the method is applied to the field passive-source data acquired in the karst development area of Longgang District, Shenzhen, to evaluate its practical utility. The results demonstrate that the higher-mode dispersion data serve as observational constraints independent of the fundamental-mode data, effectively enhancing the accuracy and vertical resolution of the inversion, and improving the delineation of soft interlayers. Additionally, the proposed approach successfully identified the underlying karst development area along the survey line. Notably, energy loss and modal aliasing of higher-mode surface waves dispersion are common phenomena in shallow surface wave data. Therefore, the dynamic mode-order identification is essential for robust multimode surface wave inversion.

Key words: passive surface-wave, karst development area, staged inversion, multi-order inversion, S-wave velocity

中图分类号: 

  • P631.4
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