Improving crosshole radar velocity tomograms: A new approach to incorporating high-angle traveltime data

Abstract

To obtain the highest-resolution ray-based tomographic images from crosshole ground-penetrating radar (GPR) data, wide angular ray coverage of the region between the two boreholes is required. Unfortunately, at borehole spacings on the order of a few meters, high-angle traveltime data (i.e., traveltime data corresponding to transmitter-receiver angles greater than approximately 50° from the horizontal) are notoriously difficult to incorporate into crosshole GPR inversions. This is because (1) low signal-to-noise ratios make the accurate picking of first-arrival times at high angles extremely difficult, and (2) significant tomographic artifacts commonly appear when high- and low-angle ray data are inverted together. We address and overcome thesetwo issues for a crosshole GPR data example collected at the Boise Hydrogeophysical Research Site (BHRS). To estimate first-arrival times on noisy, high-angle gathers, we develop a robust and automatic picking strategy based on crosscorrelations, where reference waveforms are determined from the data through the stacking of common-ray-angle gathers. To overcome incompatibility issues between high- and low-angle data, we modify the standard tomographic inversion strategy to estimate, in addition to subsurface velocities, parameters that describe a traveltime ‘correction curve’ as a function of angle. Application of our modified inversion strategy, to both synthetic data and the BHRS data set, shows that it allows the successful incorporation of all available traveltime data to obtain significantly improved subsurface velocity images.

The hydrogeologic information in cross-borehole complex conductivity data from an unconsolidated conglomeratic sedimentary aquifer

“…Tronicke et al (2004) gather a set of GPR measurements from the BHRS, with the transmitter and receiver deployed in C5 and C6, and note that values of ∅ derived from an inversion of the GPR data differed in detail from the layered stratigraphy identified by Barrash and Clemo (2002), but a cluster analysis of the inverted Cross-borehole complex conductivity E411 GPR data identified clusters with similar values of velocity and attenuation, broadly corresponding to areas with contrasting ∅ values. Furthermore, crosshole GPR analysis was conducted by Ernst et al (2007) and Irving et al (2007). Dafflon et al (2011b) invert multiple intersecting high-resolution crosshole GPR profiles at the BHRS and obtain a 3D distribution of ∅ values that are in broad agreement with the results of the geostatistical study by Barrash and Clemo (2002).…”

“…Note the closer correspondence in the lower portion of the stratigraphy in which K and porosity are more related in the Kozeny-Carman sense . sion of σ 0 measurements are broadly supportive of the multiscale heterogeneity affecting hydraulic, lithologic, and geophysical parameters, which has been demonstrated in the sedimentary structure of the site (Barrash and Clemo, 2002;Barrash and Reboulet, 2004), and recognition of two types of electrical-porosity (and dielectric-porosity) behavior evident in the subdivision of unit 2 into units 2A and 2B (Ernst et al, 2007;Irving et al, 2007;Mwenifumbo et al 2009;Dafflon et al, 2011b). Observation of ∅ and CR logs and analysis of correlation between ∅ and CR show strong correlation at the stratigraphic unit scale but highly variable weak to strong correlation at the subunit scale (Figure 14 here and Barrash and Cardiff, 2013).…”

Subglacial topography, ice thickness, and bathymetry of Kongsfjorden, northwestern Svalbard

“…On the 25 high gain channel, we applied a spherical and exponential (SEC) gain to reinforce bed returns. The surface and bed returns were digitized semi-automatically with a cross-correlation picker (Irving et al, 2007) at the first break of the bed reflection.…”

High-resolution ice thickness and bed topography of a land-terminating section of the Greenland Ice Sheet

“…Several corrections and filters were applied to the radar data: (1) a butterworth bandpass filter, with cut-off frequencies of 0.75 and 7 MHz, was used to remove the unwanted frequency components in the data; (2) normal move-out correction was applied to correct for antenna separation; (3) rubber-band correction was used to interpolate the data to uniform trace spacing; and (4) two-dimensional (2-D) frequency wave-number migration (Stolt, 1978) was used to collapse hyperbolic reflectors back to their original positions in the profile direction. The bed returns were digitized semi-automatically with a cross-correlation picker (Irving et al, 2007). We calculated the ice thickness from the picked travel times of the bed return using a constant wave speed of 168 m µs −1 (discussed further in Sect.…”