name: gprpy
description: |
Process and visualize ground-penetrating radar (GPR) data with signal processing,
velocity analysis, and depth conversion. Use when Claude needs to: (1) Load GPR
files (.DZT, .DT1, .GPR, .rd3), (2) Apply dewow, gain, and filters to radargrams,
(3) Convert two-way travel time to depth, (4) Perform CMP/WARR velocity analysis,
(5) Apply topographic corrections, (6) Export processed profiles as images or SEG-Y,
(7) Batch process multiple GPR survey lines.
version: 1.0.0
author: Geoscience Skills
license: MIT
tags: [GPR, Ground-Penetrating Radar, Near-Surface, Signal Processing, GPRPy, Geophysics, Depth Conversion, Radargram]
dependencies: [gprpy>=1.0.0, numpy, matplotlib, scipy]
complements: [pyvista]
workflow_role: data-loading
GPRPy - Ground Penetrating Radar Processing
Quick Reference
import gprpy.gprpy as gp
import matplotlib.pyplot as plt
# Load and display
data = gp.gprpyProfile()
data.importdata('profile.DZT')
data.showProfile()
plt.show()
# Access data
print(f"Traces: {data.data.shape[1]}")
print(f"Samples: {data.data.shape[0]}")
print(f"Time range: {data.twtt.max():.1f} ns")
Supported Formats
| Format |
Manufacturer |
| .DZT |
GSSI |
| .DT1 |
Sensors & Software |
| .GPR |
MALA |
| .rd3/.rad |
MALA |
| .sgy |
SEG-Y |
Essential Operations
Basic Processing
data = gp.gprpyProfile()
data.importdata('profile.DZT')
data.dewow(window=10) # Remove low-frequency drift
data.remMeanTrace(ntraces=50) # Remove background ringing
data.tpowGain(power=1.5) # Time-power gain
data.agcGain(window=25) # Automatic gain control
data.showProfile()
Apply Filters
data.bandpassFilter(minfreq=100, maxfreq=800) # MHz
data.lowpassFilter(maxfreq=500)
data.highpassFilter(minfreq=50)
Time-to-Depth Conversion
velocity = 0.1 # m/ns (typical for dry sand)
data.setVelocity(velocity)
data.showProfile(yrng=[0, 5]) # Top 5 meters
Topographic Correction
data.topoCorrect(topofile='topography.txt', velocity=0.1)
# File format: x_position, elevation
Export Results
data.exportFig('processed.png', dpi=300)
data.exportSEGY('processed.sgy')
data.exportASCII('processed.txt')
Velocity Analysis (CMP)
cmp = gp.gprpyCMP()
cmp.importdata('cmp_survey.DZT')
cmp.showCMP()
cmp.semblance(vmin=0.05, vmax=0.15, vstep=0.01)
cmp.showSemblance()
Processing Parameters
| Parameter |
Typical Value |
Description |
| Dewow window |
5-20 ns |
Low-frequency removal window |
| Gain power |
1.0-2.0 |
Time-power gain exponent |
| AGC window |
10-50 ns |
Automatic gain window |
| Bandpass |
100-800 MHz |
Frequency filter range |
Material Velocities
| Material |
Velocity (m/ns) |
| Air |
0.30 |
| Dry sand |
0.10-0.15 |
| Wet sand |
0.06-0.08 |
| Dry soil |
0.08-0.12 |
| Wet soil |
0.05-0.08 |
| Limestone |
0.10-0.12 |
| Granite |
0.10-0.13 |
| Water |
0.033 |
| Ice |
0.16-0.17 |
When to Use vs Alternatives
| Tool |
Best For |
Limitations |
| gprpy |
Python-based GPR processing, scripted workflows, open-source |
Limited advanced migration algorithms |
| GPRMax |
Forward modelling and simulation of GPR responses |
Simulation only, not for data processing |
| REFLEXW |
Full commercial processing suite, advanced migration |
Commercial license required |
| Custom scipy |
Custom signal processing, research algorithms |
Must build everything from scratch |
Use gprpy when you need open-source GPR processing in Python, batch processing
of survey lines, or integration with other Python geoscience tools.
Consider alternatives when you need forward modelling of GPR responses (use GPRMax),
advanced migration or commercial-grade processing (use REFLEXW), or highly custom
signal processing algorithms (use scipy directly).
Common Workflows
Process raw GPR profile for interpretation
References
Scripts
By