An enhanced GPR-based data processing approach for detecting subsurface utilities in urban distribution networks

Abstract

Ground-penetrating radar (GPR) is a non-destructive technique that helps find subsurface utilities. In geophysical investigations, the availability of noise sources, and the complexity of utility networks mean that performing a routine field operation and processing may not reveal the wanted anomalies. Thus, we use data acquisition and processing strategy to detect every single hyperbolic event (which means a probable anomaly) more accurately. In this approach, we first acquire data in parallel lines that cross the predetermined utility line path, use pre-processing techniques (zero-time correction, dewowing, etc.), and then use compensated time reversal (CTR) processing technique. Moreover, we group detected events depending on how frequently they occur through all traverses, where repeated events are probably caused by a utility line. For a better understanding, we compared CTR outputs with conventional processing (using filtering and Kirchhoff migration). This approach was used in a field that comprises buried utilities, such as pipelines and cables. Data were acquired along 4 parallel traverses with a GPR MALA tool and an antenna frequency of 250 MHz. Results indicate that the CTR generates better resolution/higher signal-to-noise ratio, and precise utility location as confirmed by drillings.