Improved accuracy of cross-borehole radar velocity models for ice property analysis

Abstract

Cross-borehole radar (XBHR) is widely used for the quantification of pore-scale liquid water in geologic materials, inferred from bulk velocity variations caused by differences in electromagnetic properties between the water and the surrounding material. The XBHR can accurately and repeatedly measure variation at depth, with sampled material remaining under natural stresses, while maintaining good lateral sampling. However, even small errors in measured radar velocities result in large errors in water content estimates, emphasizing the need to quantify and minimize errors. We have rigorously assessed the sources of uncertainty in XBHR surveys undertaken in a glaciological setting. We have summarized and quantified the three main areas of uncertainty in data collection: (1) instrument time drift, (2) first-break picking, and (3) borehole geometry. Our analysis of field data indicated that contemporary acquisition procedures can produce velocity errors of AE3.0% (AE0.0050 m∕ns), equivalent to AE0.84 vol% water content. We have developed several revisions to produce improved data acquisition. Through enhancement of existing techniques, the velocity uncertainties were improved to AE1.5%. We also found the measurement of borehole diameter during hot-water drilling, which could hypothetically further reduce the velocity uncertainty to AE0.8%, equivalent to AE0.2 vol% water content. The need for such precise measurement is clear because an increase in englacial water content, from 0% to 0.8%, has been proven to triple the strain rate and soften the ice. Liquid water between ice crystals has also been linked to faster velocities in ice streams and surging events.

Coal top detection by conductively guided borehole radar wave imaging for open cut blast‐hole drilling

“…It is often based on a vertical electric dipole antenna, which radiates the maximum electromagnetic (EM) waves perpendicular to the antenna axis, and a null EM wave along the antenna axis. It has been used for imaging around the borehole with applications such as detecting cavities, voids and tunnels (Davis, Lytle and Lame 1979;Lytile et al 1979;Owen and Suhler 1982;Olhoeft 1993;Kim, Cho and Yi 2004), salt domes (Nickel et al 1983), fracture mapping (Olsson et al 1992;Lane, Haeni and Williams 1994;Stevens et al 1994;Miwa, Sato and Niitsuma 1999;Sato and Miwa 2000;Haeni et al 2002), coal mining (Cook 1977), hydrological property mapping (Hubbard et al 1997;Paprocki and Alumbaugh 1999;Deiana et al 2007), geotechnical evaluation (Mason, Cloete and Palmer 2012), orebody delineation (Turner et al 2000;Zhou and Fullagar 2001), the burningfront detection of coal gasification ) and ice property analysis (Axtell et al 2016).…”

Detection of Tracer Plumes Using Full‐Waveform Inversion of Time‐Lapse Ground Penetrating Radar Data: A Numerical Study in a High‐Resolution Aquifer Model

“…For a typical used frequency ( f ) spectra of 10–200 MHz (the range used in this study) of the EM signal and a ε r of 12–25 of the media, the wavelength scales between 0.3 and 8.5 m ( λ ( ε r ,f ) = c 0 /√ ε r /f; with c 0 = 3 × 10 8 m/s as the EM velocity in air (Annan, 2009)). Especially, GPR acquisition in a wave transmission configuration with transmitters in one borehole and receivers in another (crosshole) (Huisman et al., 2003; Klotzsche, Vereecken, & van der Kruk, 2019) allows a good subsurface illumination with dense ray‐coverage and relatively small acquisition errors (Axtell et al., 2016). Time‐lapse crosshole GPR monitoring of fluid transport using ray‐based tomography was successful in illuminating preferential pathways from either signal attenuation due to a saline tracer of about 2 m width in a fractured rock (Day‐Lewis et al., 2003), or wave velocity changes due to soil water content changes at a decimeter scale (Looms et al., 2008).…”

A borehole trajectory inversion scheme to adjust the measurement geometry for 3D travel time tomography on glaciers

“…Crosshole tomography has been used in mining exploration (Wong, 2000), aquifer delineation and hydrology-related topics (Hubbard and Rubin, 2000;Daley et al, 2004;Dietrich and Tronicke, 2009;Linder et al, 2010;von Ketelhodt et al, 2018), for characterising a host rock and its small-scale structures such as fault planes (Maurer and Green, 1997;Rumpf and Tronicke, 2014;Schmelzbach et al, 2016;Doetsch et al, 2020;Shakas et al, 2020), for investigating pore pressure variations in aquifers and caprocks (Daley et al, 2008;Marchesini et al, 2017;Grab et al, 2022) and voids in karst regions (Duan et al, 2017;Kulich and Bleibinhaus, 2020;Peng et al, 2021). Furthermore, Gusmeroli et al (2010) and Axtell et al (2016) used GPR-based travel time tomography to estimate the water content in a polythermal glacier.…”