No abstract

No abstract

The ahead geological prospecting of severely weathered surrounding rock in a tunnel is challenging due to complex geological conditions. Hence, the best approach is to use a variety of geophysical exploration methods. In this study, we have applied seismic, electrical resistivity (ER), and transient electromagnetic (TEM) methodologies for ahead prospecting of the highly weathered and complex surrounding rock at the diversion tunnel of the Hongyan River to Stone River Water Transfer Project in Shaanxi Province, China. The seismic method was employed to detect structural information for an area of 100 m from the front of the tunnel, the TEM method was used to obtain the resistivity information within 60 m, and the ER method was conducted to obtain detailed resistivity information over a range of 30 m. The integrated results generated a comprehensive interpretation of the geological body located within 100 m of the front of the tunnel. We divided this geological area into intact, severely weathered, and slightly weathered sections. Information on the water content of each section was also produced. The results of subsequent excavations are consistent with our results, proving the effectiveness and feasibility of a comprehensive approach for analyzing highly weathered and complex surrounding rock.

No abstract

In view of the key problem that a large amount of noise in seismic data can easily induce false anomalies and interpretation errors in seismic exploration, the time-frequency spectrum subtraction (TF-SS) method is adopted into data processing to reduce random noise in seismic data. On this basis, the main frequency information of seismic data is calculated and used to optimize the filtering coefficients. According to the characteristics of effective signal duration between seismic data and voice data, the time-frequency spectrum selection method and filtering coefficient are modified. In addition, simulation tests were conducted by using different S/R, which indicates the effectiveness of the TF-SS in removing the random noise.