An Efficient Dual-Parameter Full Waveform Inversion for GPR Data Using Data Encoding
Deshan Feng, Bingchao Li, Xun Wang, Siyuan Ding, Xiaoyong Tai, Liqiong Cai, Xuan Su
Abstract
Ground penetrating radar (GPR) is an important shallow electromagnetic non-destructive detection technology. The full waveform inversion (FWI) of GPR data utilizes all information including dynamics and kinematics, theoretically has the highest imaging accuracy, and meets the increasingly sophisticated needs of engineering exploration imaging. However, the bottleneck restricting the FWI is the low calculation efficiency, which cannot meet the requirements of rapid reconstruction of underground medium in actual engineering. In order to improve the calculation efficiency, we introduce the data encoding into the GPR dual-parameter FWI. Data encoding often brings crosstalk noise, and the noise is closely related to the encoding methods and data types. For this reason, we select the encoding of the crosshole data, wide-angle reflection and refraction data, and common-offset data for inversion. Experiments show that data encoding can effectively reduce computing time, and three different GPR data require different encoding methods due to their different redundancies. Total variation (TV) regularization can suppress the noise caused by data encoding. Although it will slightly increase the calculation time, it can significantly improve the inversion quality.