Electromagnetic Propagation Logging: Advances in Technique and Interpretation

Wharton, R.P.; Rau, Rama N.; Best, David

doi:10.2118/9267-ms

Cited by 108 publications

(26 citation statements)

References 3 publications

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“…The interaction of the radar signal with this mixture is affected both by the volumetric ratio of ice to air as well as by the shape and orientation of the ice crystals and air voids. However, Harper and Bradford [2003] show that, for cold snow, the complex refractive index model (CRIM) equation [Wharton et al, 1980;Knight et al, 2004] can be adapted to closely…”

Section: Density From Velocitymentioning

confidence: 99%

Georadar‐derived estimates of firn density in the percolation zone, western Greenland ice sheet

et al. 2012

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[1] Greater understanding of variations in firn densification is needed to distinguish between dynamic and melt-driven elevation changes on the Greenland ice sheet. This is especially true in Greenland's percolation zone, where firn density profiles are poorly documented because few ice cores are extracted in regions with surface melt. We used georadar to investigate firn density variations with depth along a $70 km transect through a portion of the accumulation area in western Greenland that partially melts. We estimated electromagnetic wave velocity by inverting reflection traveltimes picked from common midpoint gathers. We followed a procedure designed to find the simplest velocity versus depth model that describes the data within estimated uncertainty. On the basis of the velocities, we estimated 13 depth-density profiles of the upper 80 m using a petrophysical model based on the complex refractive index method equation. At the highest elevation site, our density profile is consistent with nearby core data acquired in the same year. Our profiles at the six highest elevation sites match an empirically based densification model for dry firn, indicating relatively minor amounts of water infiltration and densification by melt and refreeze in this higher region of the percolation zone. At the four lowest elevation sites our profiles reach ice densities at substantially shallower depths, implying considerable meltwater infiltration and ice layer development in this lower region of the percolation zone. The separation between these two regions is 8 km and spans 60 m of elevation, which suggests that the balance between dry-firn and melt-induced densification processes is sensitive to minor changes in melt.

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Section: Density From Velocitymentioning

confidence: 99%

Georadar‐derived estimates of firn density in the percolation zone, western Greenland ice sheet

et al. 2012

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“…In the study that follows, we evaluate the reliability of porosity estimates derived from surface GPR velocity measurements by comparing the results to borehole GPR velocity measurements and neutron log porosity estimates. We include a comparison of two petrophysical transforms commonly used in hydrogeophysical applications, the Topp [ Topp et al , 1980] and Complex Refractive Index Method (CRIM) [ Wharton et al , 1980] equations.…”

Section: Introductionmentioning

confidence: 99%

Estimating porosity with ground‐penetrating radar reflection tomography: A controlled 3‐D experiment at the Boise Hydrogeophysical Research Site

Bradford

Clement

Barrash

2009

Water Resources Research

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[1] To evaluate the uncertainty of water-saturated sediment velocity and porosity estimates derived from surface-based, ground-penetrating radar reflection tomography, we conducted a controlled field experiment at the Boise Hydrogeophysical Research Site (BHRS). The BHRS is an experimental well field located near Boise, Idaho. The experimental data set consisted of 3-D multioffset radar acquired on an orthogonal 20 Â 30 m surface grid that encompassed a set of 13 boreholes. Experimental control included (1) 1-D vertical velocity functions determined from traveltime inversion of vertical radar profiles (VRP) and (2) neutron porosity logs. We estimated the porosity distribution in the saturated zone using both the Topp and Complex Refractive Index Method (CRIM) equations and found the CRIM estimates in better agreement with the neutron logs. We found that when averaged over the length of the borehole, surface-derived velocity measurements were within 5% of the VRP velocities and that the porosity differed from the neutron log by less than 0.05. The uncertainty, however, is scale dependent. We found that the standard deviation of differences between ground-penetrating-radar-derived and neutron-log-derived porosity values was as high as 0.06 at an averaging length of 0.25 m but decreased to less than 0.02 at length scale of 11 m. Additionally, we used the 3-D porosity distribution to identify a relatively high-porosity anomaly (i.e., local sedimentary body) within a lower-porosity unit and verified the presence of the anomaly using the neutron porosity logs. Since the reflection tomography approach requires only surface data, it can provide rapid assessment of bulk hydrologic properties, identify meterscale anomalies of hydrologic significance, and may provide input for other higherresolution measurement methods.

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“…Although water content can be directly calculated from GPR velocity analysis using petrophysical and empirical relationships, such as the Complex Refractive Index Model (CRIM; Wharton et al . []) and Topp's equation [ Topp et al ., ], the estimation of soil hydraulic properties is not feasible if the movement of water over time and depth is unknown. Here we use time‐lapse common midpoint (CMP) GPR data measured on an agricultural test site to obtain in situ travel times and interval velocities that reflect water content changes in the upper few meters of the vadose zone, enabling the estimation of unsaturated soil hydraulic properties over discrete depth intervals.…”

Section: Methodsmentioning

confidence: 99%

Coupled hydrogeophysical inversion of time-lapse surface GPR data to estimate hydraulic properties of a layered subsurface

et al. 2013

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A major challenge in vadose zone hydrology is to obtain accurate information on the temporal changes of the vertical soil water distribution and its feedback with the atmosphere and groundwater. A state of the art coupled hydrogeophysical inversion scheme is applied to evaluate soil hydraulic properties of a synthetic model and a field soil in southern Ontario based on time‐lapse monitoring of soil dynamics with surface ground‐penetrating radar (GPR). Film flow was included in the hydrological model to account for noncapillary water flow in a sandy medium during dry conditions. The synthetic study illustrated that GPR data contain sufficient information to accurately constrain soil hydraulic parameters within a coupled inversion framework and led to an accurate estimation of the soil hydraulic properties. When film flow was not accounted for within the inversion, an equally good fit could still be achieved. In this case, errors introduced by neglecting film flow were compensated by different hydraulic parameters. For the field data, the coupled inversion reduced the overall misfit compared to an uncalibrated model using hydraulic parameters obtained from laboratory data. Although the data fit improved significantly for water content in the deeper soil layers, accounting for film flow in the uppermost subsurface layer did not lead to a better fit of the GPR data. Further research is needed to describe the processes controlling water content in the dry range, in particular coupled heat and vapor transport. This study illustrates the suitability of surface GPR measurements combined with coupled inversion for near‐surface characterization of soil hydraulic parameters.

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Electromagnetic Propagation Logging: Advances in Technique and Interpretation

Cited by 108 publications

References 3 publications

Georadar‐derived estimates of firn density in the percolation zone, western Greenland ice sheet

Georadar‐derived estimates of firn density in the percolation zone, western Greenland ice sheet

Estimating porosity with ground‐penetrating radar reflection tomography: A controlled 3‐D experiment at the Boise Hydrogeophysical Research Site

Coupled hydrogeophysical inversion of time-lapse surface GPR data to estimate hydraulic properties of a layered subsurface

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