Lecture 4C - GPR applications and Interpretations

GPR is valuable for high-resolution near-surface measurements.
Applications include:
- Hydrological boundary detection like water tables, due to strong permittivity contrasts that make them strong radar reflectors.
- Archaeological investigations.
Limitation: Limited depth penetration, especially in high conductivity areas where attenuation is high.
- Most effective in dry or hard rock regions.
- Less effective in wet soils or clay-rich areas.

Identify strong parallel returns indicating the ground surface or ground wave (which can be ignored).
These parallel black and white lines represent a single interface due to oscillations in the transmitted pulse, not multiple interfaces.
Recognize main (primary) reflectors represented by parallel white and dark bands, indicating interfaces or boundaries between layers of contrasting permittivity.

Consider the potential for observing multiples, which are ghost reflections at depths that are multiples of the original reflector's depth.
Multiples occur due to the radar signal reflecting multiple times between the surface and the reflector.

Hyperbolic curves are common in GPR data.
They are artifacts of the common offset profiling method over small discrete reflectors.

Subsurface reflectors are not always long and continuous.
Smaller, localized features (sizes similar to the radar wavelength) reflect signals even when the instrument is not directly above them.
Radar signal radiates in a cone shape.
As the instrument approaches an anomaly, radar energy dispersed at the forward edge of the cone is reflected back to the receiver.
The inclined reflected path length shortens as the instrument moves towards the anomaly, becoming shortest when directly over the anomaly.
The reflector appears to shallow and then deepen as the instrument moves away.
This changing path length generates a hyperbolic reflection pattern.
The shape of the hyperbola can be used to estimate velocity.

Tests with a metal bar buried at different depths show clear hyperbolic reflectors.
Shallower buried pipes result in hyperbolas with shorter travel times and more peaked shapes.
Hyperbolas can represent features of interest, such as potential burial sites or utility pipes/cables.
Pipes crossing a profile at 90 degrees appear as hyperbolas in the cross-section.
The peak of the hyperbola indicates the location of the pipe.

Hyperbolas in the uppermost layer may represent discrete features like large boulders.
Modeling hyperbolas allows estimation of upper layer velocity.
The vertical axis can be converted from time to depth using estimated velocity.
Even clean GPR profiles can be difficult to interpret without training.

Line drawings can be constructed to represent subsurface reflectors more clearly.
The goal is to extract important information from radar profile data and represent it in a simple visualization.

Interesting features are represented by coherent, extended reflectors (repeated stripes of black and white).
Do not interpret adjacent parallel black and white stripes as multiple parallel interfaces.
Dipping interfaces may be shown as inclined reflectors, but avoid misinterpreting the edges of hyperbolas as dipping reflectors.
Individual hyperbolas represent individual discrete reflectors like pipes.
Many discrete reflectors may create a homogenous pattern where individual hyperbolic shapes are difficult to recognize.
Avoid over-interpreting data by considering each wiggle in a trace to represent a specific subsurface feature.
Look for consistency within layers or regions before ascribing characteristics.

GPR survey along transects to assess peat depth and determine characteristics like water content.
Combined with borehole data and resistivity survey.

Upper layer with multiple mixed reflections that peter out after $300$ nanoseconds.
Consistent reflector at about $400$ nanoseconds.
Hyperbolas identified within the circled region.

Hyperbolas are modeled to estimate velocity.
Velocity (e.g., $0.035$ meters per nanosecond) is used to convert the vertical axis from time to depth.

Travel time depth to the base of the peat can be estimated using: $distance = (travel \ time/2) * velocity$
Example: For a $280$ nanosecond two-way travel time and a velocity of $0.035$ meters/nanosecond, the depth is approximately $4.9$ meters.

Velocity can be interpreted in terms of water content using the equation:
$v = \frac{c}{\sqrt{\epsilon<em>r}}$ , where $v$ is the wave speed, $c$ is the speed of light, and $\epsilon</em>r$ is the relative permittivity.
Estimate relative permittivity: $\epsilon_r = (c/v)^2$
If $v = 0.035$ m/ns, then $\epsilon_r \approx 73$ .
Comparison with typical relative permittivity values (e.g., water is $80$ ) suggests high water content in the upper layer.

Borehole data allows direct verification of interpretations, such as the lower reflector corresponding to a change from peat to clay.
Resistivity data complements GPR data.
- Red indicates high resistivity (low conductivity).
- Blue indicates low resistivity (high conductivity).

GPR provides more detail in the near surface compared to resistivity.
Resistivity model shows resistivity decreasing with depth (conductivity increasing).
Radar attenuation increases with depth, limiting deeper GPR imaging.

GPR provides high-resolution results from shallow depths.
Localized radar reflectors are identified as hyperbolic curves in reflection profiles.
Hyperbolas are used to estimate radar wave velocities.
Velocities can be interpreted in terms of electrical permittivity and water content.