为解决建筑交通阻隔、电磁机械干扰等复杂城市环境导致的城市地质勘探受限难题，快速查明隧道洞室的位置和埋深，排除施工安全隐患，以某城市轨道交通隧道探测项目为例，采用具有抗干扰能力和狭小空间适应性的多源频率域地震勘探法，通过多点分布式地震采集站获取三分量的多源频率域地震信号，提取主动源、被动源面波综合频散曲线和微动谱比曲线，在此基础上进行特征曲线的联合建模与反演，获得高精度的地层横波速度剖面。应用结果表明： 1）多源频率域地震勘探法探测速度快，其数据采集效率约为同类技术的3倍，且能通过采集站和移动端2种方式对硬件和数据进行监测，有效保证了数据质量； 2）通过多类型数据的联合建模与反演，提升了地层探测精度，能较好反映地层的横波速度分布情况进而圈定异常； 3）隧道顶板的探测结果与实际位置误差为3.3%，凸显了该方法在城市隧道洞室探测方面的有效性。

 Geological exploration in complex urban areas is often limited owing to building structures, traffic barriers, and electromagnetic and mechanical disturbance. Therefore, a case study is conducted on an urban rail transit tunnel to rapidly identify the location and burial depth of tunnel caverns and mitigate construction safety hazards. Herein, a multisource frequencydomain seismic exploration method with antiinterference capabilities and narrowspace adaptability is adopted. The method involves collecting multisource frequencydomain seismic signals of three components using a distributed seismic acquisition station with multiple points. Subsequently, comprehensive dispersion and micromotion spectrum ratio curves of surface waves with active and passive sources are obtained. On this basis, joint modeling and inversion of the characteristic curves are performed to obtain highprecision stratigraphic shear wavevelocity profiles. The results demonstrate the following: (1) The proposed method exhibits rapid detection capabilities; the data acquisition efficiency is approximately three times higher than that of similar technologies. Realtime monitoring of hardware and data at collection stations and mobile terminals have effectively ensured the data quality. (2) Through joint modeling and inversion techniques with multiple data sources, the accuracy of stratigraphic exploration is improved. This approach provides an accurate depiction of the shear wavevelocity distribution within the formation and enables us to identify anomalies. (3) The error between the detection results of the tunnel roof and its actual position is 3.3%, highlighting the effectiveness of the proposed method in detecting urban tunnel caverns.