异常区域超前辨识对于预防地下岩土工程灾害具有重要作用。为了满足地下工程高精度探测的需求，本文提出一种层析成像方法以辨识复杂岩体结构中的异常区域，结合了走时层析、阻尼最小二乘法和高斯滤波等技术。该方法克服了空洞区域辨识中速度差限制，减轻了迭代中孤立速度突变所带来的影响。开展了数值和室内实验，量化评估最短路径法（shortest-path method, SPM）、动态最短路径法（dynamic shortest-path method, DSPM）和快速扫描法（fast sweeping method, FSM）等正演模拟的识别精度和计算效率。结果表明，在数值和室内实验中DSPM和FSM均能清晰地辨识出异常区域。陕西震奥矿山现场应用结果证明了该方法可利用矿山开采中爆破、微震等多类声源对矿山内部未知结构进行波速场成像。本研究不仅实现了走时层析成像方法在异常区域识别中的应用，而且为地下岩土工程中潜在风险源的探测提供了新的思路。

Early identification of abnormal regions is crucial in preventing the occurrence of underground geotechnical disasters. To meet the high-accuracy detection requirements of underground engineering, this paper proposes a tomography method for abnormal region identification in complex rock-mass structures that utilizes traveltime tomography combined with the damped least-squares method and Gaussian filtering. The proposed method overcomes the limitation of velocity difference in empty region detection and mitigates the impact from isolated velocity mutation in the iteration. Numerical and laboratory experiments were conducted to evaluate the identification accuracy and computational efficiency of forward modeling, including the shortest-path method (SPM), dynamic SPM (DSPM), and fast sweeping method (FSM). The results show that DSPM and FSM can clearly detect abnormal regions in numerical and laboratory experiments. Field experiments were conducted in the Shaanxi Zhènào mine and achieve the reconstruction of the underground roadway distribution. This paper not only realizes the application of abnormal region identification using traveltime tomography but also provides new insight into potential hazards detection in underground geotechnical engineering.