Advanced Time-Lapse Ground-Penetrating Radar Data Processing for Quantitatively Monitoring of Small-Scale Fluid Infiltration

Monitoring underground fluid infiltration and estimating soil water content (SWC) is essential for hydrogeology and soil science research. Conventional hydrological survey methods, such as trenching, soil sampling, or time-domain reflectometry (TDR), provide in situ, static, and discrete measurements. However, these methods have limitations in capturing the spatiotemporal dynamics of fluid infiltration. Ground-penetrating radar (GPR) offers a noninvasive and high-spatiotemporal measurement approach for near-surface applications. Nevertheless, the complexity of GPR data and its weak response to small-scale fluid infiltration pose challenges in instantaneous attribute analysis and SWC estimation using the travel-time method. In this article, we propose a time-lapse GPR data full-waveform inversion (FWI) method to effectively monitor the spatial distribution of small-scale fluid transport and estimate SWC with improved accuracy. First, we combine velocity spectral analysis and the structural similarity index (SSIM) to construct a permittivity model that solves the dependence of FWI on the initial model. Subsequently, to simultaneously invert the permittivity and conductivity, we introduce gradient normalization to balance the convergence rate of the two parameters during the inversion process. The typical GPR time-lapse infiltration GPR field data example confirms that the proposed method can accurately characterize small-scale fluid infiltration distribution and estimate SWC parameters. The total estimated error in SWC is found to be less than 5%. The proposed time-lapse GPR data processing protocol provides a quantitative means for monitoring small-scale fluid infiltration.