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Adverse Geology Identification Through Mineral Anomaly Analysis During Tunneling:Methodology and Case Study

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摘要 Accurate and effective identification of adverse geology is crucial for safe and efficient tunnel construction.Current methods of identifying adverse geology depend on the experience of geologists and are prone to misjudgment and omissions.Here,we propose a method for adverse geology identification in tunnels based on mineral anomaly analysis.The method is based on the theory of geoanomaly,and the mineral anomalies are geological markers of the presence of adverse geology.The method uses exploration data analysis(EDA)to calculate mineral anomaly thresholds,then evaluates the mineral anomalies based on the thresholds and identifies adverse geology based on the characteristics of the mineral anomalies.We have established a dynamic expansion process for background samples to achieve the dynamic evaluation of mineral anomalies by adjusting anomaly thresholds.This method has been validated and applied in a tunnel excavated in granite.As shown herein,in the tunnel range of 142+800–142+860,the fault F37 was successfully identified based on an anomalous decrease in the diagenetic minerals plagioclase and hornblende,as well as an anomalous increase in the content of the alteration minerals chlorite,laumonite,and epidote.The proposed method provides a timely warning when a tunnel enters areas affected by adverse geology and identifies whether the tunnel is gradually approaching or moving away from the fault.In addition,the applicability,accuracy,and further improvement of the method are discussed.This method improves our ability to identify adverse geology,from qualitative to quantitative,and can provide reference and guidance for the identification of adverse geology in mining and underground engineering.
出处 《Engineering》 SCIE EI CAS CSCD 2023年第8期150-160,共11页 工程(英文)
基金 financial support from the National Natural Science Foundation of China(52022053 and 52009073) the Natural Science Foundation of Shandong Province(ZR201910270116)。
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