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Volume 45 Issue 2
Apr.  2026
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Article Navigation >  CARSOLOGICA SINICA  > 2026  >  45(2): 292-301
GUO Jianmin, ZHENG Canzheng, DING Qingzhong, WANG Hongzhen, FU Yang, Gong Liang. Application of microtremor survey and three-dimensional geological modeling in urban karst geological survey[J]. CARSOLOGICA SINICA, 2026, 45(2): 292-301. doi: 10.11932/karst20260202
Citation: GUO Jianmin, ZHENG Canzheng, DING Qingzhong, WANG Hongzhen, FU Yang, Gong Liang. Application of microtremor survey and three-dimensional geological modeling in urban karst geological survey[J]. CARSOLOGICA SINICA, 2026, 45(2): 292-301. doi: 10.11932/karst20260202
shu

Application of microtremor survey and three-dimensional geological modeling in urban karst geological survey

doi: 10.11932/karst20260202
  • 1.

    Groundwater Research Center, Shandong Provincial Geo-mineral Engineering Exploration Institute, Jinan, Shandong 250014, China

  • 2.

    Jinan Rail Transit Group Co., Ltd., Jinan, Shandong 250014, China

  • 3.

    School of Geo-Science and Technology, Zhengzhou University, Zhengzhou, Henan 450001, China

  • Received Date: 2024-06-21
  • Accepted Date: 2025-08-26
  • Rev Recd Date: 2025-05-13
    Abstract
  • The exploration of underground karst geological structures in urban environments poses significant challenges for conventional geophysical methods. These methods often suffer from high levels of noise, constraints on survey line layouts due to dense infrastructure, and the inherent limitation of two-dimensional (2D) data in representing the three-dimensional (3D) spatial complexity of geological bodies. To address these issues, this study proposes and demonstrates an integrated methodological framework that combines microtremor survey technology with 3D geo-statistical modeling to enhance subsurface characterization in karst terrains.The research was conducted within the planned section between Quancheng Park Station and Qianfo Mountain Station on Line 4 of the Jinan Urban Rail Transit System, a typical urban area underlain by karst-prone strata. Initially, a two-dimensional microtremor survey was implemented. Employing a linear array configuration with two-meter receiver spacing using three-component geophones, data were collected along 18 survey lines totaling 2,242 meters in length, encompassing 1,139 physical points. This passive-source method effectively utilizes ambient seismic noise generated by urban activities (e.g., traffic) and natural phenomena as the signal source, thereby overcoming the noise sensitivity of active-source methods and simplifying field logistics. Data processing involved preprocessing the recorded signals, extracting Rayleigh wave dispersion curves using the Spatial Auto-Correlation (SPAC) method, and subsequently inverting these curves to derive 2D shear-wave velocity (Vs) profiles. These profiles visually delineate subsurface velocity structures, where low-velocity anomalies against higher-velocity bedrock backgrounds indicate potential karst features such as cavities, dissolution zones, or fractured rocks.The inversion results from representative lines (e.g., QQWT01 and QQWT09) reveal a vertically layered velocity structure: very low velocities (500 m·s−1) in the shallow Quaternary overburden; intermediate velocities (500–1 500 m·s−1) corresponding to moderately weathered and karstified dolomite; and higher velocities (1 500 m·s−1) representing more competent, less weathered bedrock. Laterally, several distinct low-velocity zones were identified and interpreted as areas of karst development. Importantly, the interpretations from these 2D profiles showed a high degree of consistency with borehole data (e.g., boreholes W2, W3, W4), which encountered cavities and filled materials at depths predicted by the velocity anomalies, thereby validating the reliability of the microtremor method for karst detection in this setting.However, 2D profiles provide information only along specific lines, leaving gaps in understanding the full 3D spatial distribution of karst features. To address this limitation, the study employed 3D geostatistical modeling techniques. The densely sampled Vs data points from all 2D profiles were treated as a regionalized variable. Variogram analysis was conducted to quantify the spatial correlation structure of shear-wave velocity in three principal directions: along the dominant survey direction (approximate E–W), perpendicular to it (N–S), and vertically. An exponential variogram model was fitted, revealing spatial correlation ranges (e.g., 120 m maximum, 15 m minimum) that characterize the continuity and variability of the geological units. Using ordinary kriging as the estimation method, a continuous 3D Vs model of the entire study volume was constructed based on the 2D profile data and the derived variogram parameters.This 3D model was then visualized using volume rendering techniques. By setting transparency thresholds for different velocity ranges, the model enables intuitive 3D visualization of karst-prone zones. For instance, rendering zones with Vs < 1,500 m·s−1 as opaque highlights volumes with potential karst development. Further refinement, such as extracting volumes with Vs < 1,200 m·s−1, helps identify areas with a high incidence of cavities. Comparative analysis between the 3D model extracts and detailed 2D profile interpretations indicates that the geo-statistically derived model does not precisely delineate individual, isolated cavities. This limitation is attributed to the smoothing effect inherent in kriging interpolation, which tends to amalgamate closely spaced anomalies. Instead, the model effectively outlines the broader "karst high-incidence zones" or "karst development regions", where the probability of encountering karst features is significantly elevated.Despite this smoothing limitation, the primary value of the integrated approach lies in its comprehensive 3D perspective. It synthesizes scattered 2D line data into a coherent volumetric model, providing a more holistic view of subsurface karst hazard distribution than is possible with 2D sections alone. The clearly visualized 3D zones of elevated karst risk offer invaluable, spatially explicit guidance for engineering planning, risk assessment, and targeted mitigation strategies in urban rail transit and other underground projects. This methodology enhances exploration efficiency by maximizing information extraction from passive seismic data, reduces costs associated with excessively dense drilling, and provides a novel, more comprehensive pathway for precise imaging of urban underground karst systems-ultimately contributing to safer construction and long-term infrastructure maintenance.

     

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