利用微震技术的落石物理特征反演计算——基于野外人工滚石实验

Interpretation of Rockfall Characteristics from Seismic Signals:Insights from Field Artificial Rockfall Experiment

摘要:

崩塌落石灾害以其发生速度快、尺寸差异大、前兆信息不明显等特点,而难以利用传统方法进行监测预警。本文借助地震学中的微震监测技术,通过在广东省大宝山露天多金属矿山开展的野外人工滚石实验,分析落石物理岩崩过程与微震监测信号之间可能的联系,通过解译崩塌落石微震监测信号,获得落石的发生时间、体积、速度等物理层参数。本次人工投石实验采用27个落石样本,建立了由9个三轴速度型微震基站组成的微震监测网络。通过这9个微震监测设备监测到13个有效落石事件的微震信号,分析落石滚落的几种形式,获得相应的地球物理特征 (如微震的频率、波速),推导出落石的体积与能量,并从中估算出以地震波形式耗散的落石势能比。其次,分析了微震能量与势能之间存在的直接联系,发现此时滚石的势能E_p和撞击产生的微震相对能量E_s之间的关系为E_s=aE^b_p,其中a的范围在 (4.18×10^-4 ±3.79×10^-4) ～ (0.42±0.397) 之间,b的数值范围在 (0.973±0.088) ～ (1.64±0.008) 之间,拟合相关性系数R²=0.98、 R²=0.85。最后,将所得的落石体积反演计算模型在不同地质的环境下进行了模型可迁移性测实验证,即利用这9组a、b范围可反演出赣州市上犹县人工落石的体积。本研究可为崩塌落石微震远程监测和快速响应提供监测对象的物理参数信息,为崩塌落石、泥石流等快速冲击性地质灾害监测预警新技术、新方法提供新的思路。

Abstract:

Traditional methods struggle to effectively monitor and predict collapsing rockfall disasters due to their sudden onset,variable sizes,and lack of obvious precursors. This study applies microseismic monitoring technology,commonly used in seismology,to investigate the relationship between rockfall physical processes and microseismic signals. Artificial rockfall experiments were conducted at the Dabao Mountain open-pit polymetallic mine in Guangdong Province,using 27 rockfall samples and a microseismic monitoring network comprising nine triaxial velocity-type stations. Thirteen valid rockfall events were recorded,and the resulting microseismic signals were analyzed to extract key physical parameters such as occurrence time,volume,and velocity. The study classified various rolling behaviors and identified corresponding geophysical characteristics—such as frequency and wave velocity—that enabled the estimation of rockfall volume and energy. Furthermore,the proportion of potential energy dissipated as seismic energy was evaluated. A quantitative relationship between rockfall potential energy (E_p) and relative microseismic energy (E_s) was established,following the empirical formula E_s=aE^b_p,where a ranges from (4.18×10^-4 ±3.79×10^-4) to (0.42±0.397),and b from (0.973±0.088) to (1.64±0.008),with correlation coefficients R²=0.98 and R²=0.85. To assess the model's generalizability,the derived coefficients were applied to inversely estimate the volume of artificial rockfalls in Shangyou County,Ganzhou City under different geological conditions. This research provides a framework for using microseismic monitoring to remotely estimate physical parameters of rockfalls,offering a promising direction for early warning and rapid response to fast-onset geological hazards such as rockfalls and debris flows.