>> 自然科学版期刊 >> 2019年01期 >> 正文
基于地震探测的围岩分类及其应用
供稿: 郑继东;陈水龙;李东艳;卓越;种凯琳;王华 时间: 2019-04-19 次数:

作者:郑继东;陈水龙;李东艳;卓越;种凯琳;王华

作者单位:河南理工大学资源环境学院中铁隧道集团有限公司

摘要:大瑞铁路高黎贡山隧道工程地质条件复杂,施工过程中掘进面大量涌水。为有效预防突水事故等突发性地质灾害的发生,基于TSP地震探测系统对掘进面前方围岩富水段和节理裂隙发育段等地质异常段进行探测。通过信息提取,研究地震信息与围岩稳定性的响应关系,建立地质异常评价指标体系,采用聚类分析法研究地震波空间分布特征、围岩物理力学参数、富水区与节理裂隙等地质异常体之间的相关性,将研究区围岩进行富水性和稳定性分级,并应用于PDZK225+999掘进面前方120 m范围内地质异常体预测。结果显示:掘进面前方50 m内围岩富水性较强,围岩类别为W2和S3,掘进面前方50~90 m内围岩节理裂隙异常发育但富水性不强,围岩类别为W3和S3,W4和S2,W4和S4。经超前水平钻探和实际隧道施工揭露验证,基于地震探测的围岩分级方法可行,分类结果与实际高度吻合,预测预报结果准确、可靠,有效提高了地震探测成果的可靠性。

基金:国家自然科学基金资助项目(41102219);

关键词:地震探测;围岩分级;地质异常;预测预报;

DOI:10.16186/j.cnki.1673-9787.2019.1.8

分类号:P631.4;U452.11

Abstract:Gaoligongshan tunnel of Da-Rui railway faces with complicated geological conditions and large water discharge during the construction. In order to prevent sudden geological accidents of water hazards, the waterenriched section and joint-fissure-developed section in surrounding rock in the front of the working-face were detected based on the TSP seismic detection system. The response of seismic information to the stability of surrounding rock was studied, and the geological anomaly evaluation index system was established based on information extraction. Meanwhile, cluster analysis method was used to analysis the seismic wave spatial distributions, the physical mechanics parameter of surrounding rock as well as the correlations between rich water area and joint fissure. The water rich and stability of surrounding rock was classified. The results of the classifications were used in prediction of geologic anomaly in 120 m range of PDZK225 + 999 face. The prediction results showed that the surrounding rock enriched in water in around 50 m of the front face in surrounding rock type as W2 and S3. The joint fissures of surrounding rock in the front 50 ~ 90 m of the face were abnormally developed but the water enrich was not strong, the surrounding rocks were W3 and S3, W4 and S2, W4 and S4. The advanced horizontal drilling and actual practice proved that the grading method was feasible and the results matched well with actual features, and the prediction results were accurate and reliable. By this method, the reliability of the seismic detection results was highly improved.

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