Multi-Region Full Waveform Inversion for Ground Penetrating Radar Common-offset Data#xD;

Ground-penetrating radar full waveform inversion (GPR-FWI) is a high-resolution inversion technique that quantitatively estimates the subsurface physical parameters (permittivity, conductivity) by matching both waveform amplitude and phase. However, the requirement to meet stability conditions forces the during wave propagation grid dimensions to be at the centimeter level, resulting in significant memory usage when discretizing the full radar wavefield. This makes it challenging to apply the FWI method on large-scale 2D or 3D GPR datasets. Furthermore, most commercial GPR systems record common-offset gathers (COG), so most GPR field data does not need to calculate the full model-space wavefield during the FWI iteration procedure. This work proposes a multi-region full waveform inversion approach (MR-FWI) for common-offset GPR data. The core strategy is to divide the model space into multiple grid regions and dynamically adjust these grids according to the requirements. By focusing on a given spatial range of the wavefield and model gradient, the computational steps are optimized, significantly reducing memory consumption and computational cost. A synthetic model and two raw GPR data examples validate that the multi-region strategy can reduce the computational burden without sacrificing inversion accuracy. The proposed MR-FWI is particularly suitable for limited computing resources and large-scale datasets, which provides a robust and high-resolution approach for most real common-offset GPR applications.