An optimized observation system and inversion method for fault detection based on surface-wave while tunneling

Understanding geological structures ahead of the tunnel face is important for safe and efficient construction of the urban tunnel. The surface-wave while tunneling (SWT) method, using drilling noise by shield machine as source, is expected to dynamically predict the adverse geologies in front of the tunnel face. Observation system and inversion method are keys for SWT. To improve the imaging accuracy of the geological conditions, it is urgent to optimize the observation system for data acquisition and inversion method for velocity inversion, especially for the utilization of multi-modes surface-waves. For observation system, several key parameters (minimum source-geophone distance, length and interval of survey line) are optimized to obtain sufficient information of dispersion curves. Then observation systems for source at different depth were optimized, supporting for geological detection using surface-waves generated by underground drilling noise. For velocity imaging, numerical simulations are studied to reveal the applicability of typical inversion methods for multi-modes of surface wave, and particle swarm optimization (PSO) algorithm is optimized for velocity inversion due to its advantages of stable calculation and good accuracy. On this basis, SWT was optimized both in data acquisition and velocity inversion for better understanding geological condition both in buried depth and detection distance. Then the improved method was applied in the Jinan tunnel and successfully detected a fault, providing geological information for construction safety and verifying the feasibility.