Velocity analysis of time-lapse sparse array antenna GPR CMP data to estimate infiltration front depth: A numerical study
Abstract
As an array antenna ground penetrating radar (GPR) system electrically switches any antenna combinations sequentially in milliseconds, multi-offset gather data, such as common mid-point (CMP) data, can be acquired almost seamlessly at the expense of spatial resolution as there is no flexibility in changing antenna offsets. The array antenna GPR system has been used to track the infiltration front during the field infiltration experiment (Iwasaki et al., 2016) by fixing the antenna position to collect time-lapse GPR data, including common offset gather (COG) and CMP data. Although only a limited number of scans could be acquired for CMP data as the number of transmitter and receiver is limited, electromagnetic (EM) wave velocities could be manually estimated for a given time-lapsed CMP data. We had to manually perform a velocity analysis of a large amount of time-lapse data, because the CMP data obtained by the array antenna GPR are too sparse to perform a common semblance analysis. The manually estimated velocities were then used to calculate the infiltration front depth at a given time. Our previous study showed that the GPR estimated infiltration front depths agreed well with the infiltration front depth calculated by HYDRUS (2D/3D).
The main objective of this study is to investigate the possibility of developing an automated velocity analysis for time lapsed CMP data collected during the infiltration test with array antenna GPR. In this study, we used simulated data so that true values were known. HYDRUS (2D/3D) (Simunek et al., 2018) was used for simulating water flow in variably-saturated soils, whereas gprMax (Warren, 2016) was used to simulate propagation of pulse EM wave in such soils by assigning dielectric constant and electrical conductivity correspond to simulated soil water content within the simulation domain. EM wave propagation was simulated at a given elapsed time to obtain CMP data with an antenna setup corresponds to the actual array antenna GPR. In this study, an interpolation technique based on projection onto convex sets (POCS) algorithm (Yi et al., 2016) was evaluated to interpolate sparse CMP data for the semblance analysis. Then, a semblance analysis was used to estimate EM wave velocities from the interpolated CMP data. Possibility of developing the automated approach was carefully evaluated.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMH003...13O
- Keywords:
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- 1835 Hydrogeophysics;
- HYDROLOGY;
- 1859 Rocks: physical properties;
- HYDROLOGY;
- 1865 Soils;
- HYDROLOGY;
- 5139 Transport properties;
- PHYSICAL PROPERTIES OF ROCKS