Automatic Approach for Fast Processing and Data Analysis of Seismic Ahead-Prospecting Method: A Case Study in Yunnan, China

Abstract

The seismic ahead-prospecting method is useful to detect anomalous zones in front of the tunnel face. However, most existing seismic detection method is designed for drilling and blasting tunnel. The detection method should be improved to satisfy the rapid tunneling of Tunnel Boring Machines (TBMs). This study focuses on reducing the time spent on seismic data processing and result analysis. Therefore, to reduce the data processing time, an automatic initial model establishment method based on surrounding rock grade is proposed. To reduce the time spent on result analysis and avoid subjective judgment, a modified k-means++ method is adopted to interpret the detecting results and extracting anomalous zones. The efficacy of the developed method is demonstrated by field tests. The fractured zones such as cavity collapse and fissure are successfully predicted and identified.