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Collaborating Authors
Kruse, Sarah
Mapping lava tubes with ground penetrating radar
Esmaeili, Sanaz (University of South Florida) | Jazayeri, Sajad (University of South Florida) | Kruse, Sarah (University of South Florida) | Bell, Ernest (University of Maryland) | Whelley, Patrick (University of Maryland) | Richardson, Jacob (University of Maryland) | Young, Kelsey (NASA Goddard Space Flight Center) | Brent Garry, William (NASA Goddard Space Flight Center)
Ground penetrating radar (GPR) is shown to be a successful tool in detecting tunnels and voids. Lava tubes are tunnel-like features in volcanic settings that can offer potential safe places for human crews and equipment on other planets. In this research we utilize GPR to detect and map lava tubes in Lava Beds National Monument, CA. Our results suggest that GPR surveys can generally be successful in resolving the ceilings of lava tubes, and in some cases, detecting the floor of the tubes. Presentation Date: Tuesday, October 13, 2020 Session Start Time: 9:20 AM Presentation Time: 10:10 AM Location: Poster Station 5 Presentation Type: Poster
Summary Ground Penetrating Radar (GPR) is a popular geophysical tool with many engineering applications. We investigate the applicability of sparse blind deconvolution (SBD) to define initial models for full-waveform inversion (FWI) of common-offset GPR data and evaluate its capabilities on a popular engineering problem, mapping of reinforcing steel bars (rebar) within concrete. SBD is used to estimate the wavelet and the initial reflectivity model of the subsurface which are required for the FWI process. Because rebar is commonly much smaller in radius than the wavelength of the GPR used for locating, traditional hyperbola fitting (ray-based) methods typically fail to provide reasonable estimates of the dimensions of the rebar. With FWI on data acquired with typical equipment and conditions, the rebar radius can be estimated with less than 30% error.
- Geophysics > Electromagnetic Surveying (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling > Seismic Inversion (0.62)
ABSTRACT Ground-penetrating radar (GPR) is a widely used tool for the detection and location of buried utilities. Buried pipes generate characteristic diffraction hyperbolas in raw GPR data. Current methods for analyzing the shapes and timing of the diffraction hyperbolas are very effective for locating pipes, but they are less effective for determining the diameter of the pipes, particularly when the pipes are smaller than the radar wavelengths, typically a few tens of centimeters. A full-waveform inversion (FWI) method is described for improving estimates of the diameter of a pipe and confirming the infilling material (air/water/etc.) for the simple case of an isolated diffraction hyperbola on a profile run perpendicular to a pipe with antennas in broadside mode (parallel to the pipe). The technique described here can improve a good initial guess of the pipe diameter (within 30%โ50% of the true value) to a better estimate (less than approximately 8% misfit). This method is developed by combining two freely available software packages with a deconvolution method for GPR effective source wavelet estimation. The FWI process is run with the PEST algorithm (model-independent parameter estimation and uncertainty analysis). PEST iteratively calls the gprMax software package for forward modeling of the GPR signal as the model for the pipe and surrounding soil is refined.
ABSTRACT Ground penetrating radar (GPR) is widely used for shallow (cms to tens of meters) subsurface imaging. Full-waveform inversion (FWI) of GPR data has enabled researchers to increase the subsurface image resolution. The FWI technique has been applied primarily to off-ground GPR and crosshole GPR data, due to complexity of surface-based on-ground data. A major difficulty with common-offset surface GPR data is the source wavelet estimation, particularly due to presence of the air wave, ground wave and noise. Existing deconvolution methods for estimation of the source wavelet require preliminary knowledge of the subsurface. Sparse blind deconvolution (SBD) methods permit estimation of the source wavelet without an initial synthetic model of soil structure. We investigate the performance of an SBD method to estimate the source wavelet of common-offset GPR data The effects of including/excluding the air/ground wave are studied on both synthetic and simple field test data involving a single buried pipe. For the 2D synthetic model, SBD extracts the wavelets. For the real field data, the estimated wavelets are compared to those derived from the deconvolution method. Ongoing research will examine the relative quality of FWI inversion results based on wavelets estimated with SBD.. Presentation Date: Monday, September 25, 2017 Start Time: 4:20 PM Location: 360C Presentation Type: ORAL
ABSTRACT Utility detection, UXO investigations and archeological studies can be heavily dependent on the results of ground penetrating radar data. Obtaining desired information about the depth, position and physical characteristics of the buried targets also requires an image of the soil properties. In cases of rebar or pipe detection, precise estimations of the location and depth can be critical. However, the highly nonlinearity of this problem makes the inversion for target position and target dimensions more complex and computationally expensive. We have recently established a new method for inverting GPR data using two freely available well-known software packages, gprMax for forward modeling of radar wave propagation and PEST for the inversion procedure. The combination of these packages enables retrieval of target location, dimensions, and constraints on the soil permittivity structure. Inversion results are presented in this paper for both synthetic and real cases of buried pipes. For the case of synthetic data, the structure of soil permittivity, the location, depth and the diameter of a pipe have been considered as unknowns. For the case of real data, parameters of the source wavelet are also considered as unkonwn. Pipe dimension radius and position are retrieved with errors of 10% in the synthetic case and 13% with the real field data. Presentation Date: Wednesday, October 19, 2016 Start Time: 9:15:00 AM Location: Lobby D/C Presentation Type: POSTER