pyGIMLi - Geophysical Inversion
Quick Reference
import pygimli as pg
from pygimli.physics import ert, srt
# Load ERT data
data = ert.load("survey.ohm")
# Invert
mgr = ert.ERTManager(data)
model = mgr.invert(lam=20, verbose=True)
# View result
mgr.showResult()
Key Classes
| Class | Purpose |
|---|
pg.Mesh | Finite element meshes |
pg.DataContainer | Survey data and geometry |
pg.Inversion | Base inversion framework |
ert.ERTManager | ERT processing and inversion |
srt.SRTManager | Seismic refraction inversion |
Essential Operations
Load and View ERT Data
import pygimli as pg
from pygimli.physics import ert
data = ert.load("survey.ohm")
print(f"Measurements: {data.size()}")
ert.showData(data) # Pseudosection
ERT Inversion
from pygimli.physics import ert
mgr = ert.ERTManager(data)
model = mgr.invert(
lam=20, # Regularization
verbose=True
)
mgr.showResult()
resistivity = mgr.model
Seismic Refraction
from pygimli.physics import srt
data = srt.load("traveltimes.sgt")
mgr = srt.SRTManager(data)
model = mgr.invert(lam=30, zWeight=0.3)
mgr.showResult()
Create Custom Mesh
import pygimli as pg
from pygimli.physics import ert
data = ert.load("survey.ohm")
mesh = pg.meshtools.createParaMesh(
data.sensors(),
quality=34.0,
paraMaxCellSize=5,
boundary=2
)
pg.show(mesh)
Save and Export
# Save mesh and model
mgr.mesh.save("result_mesh.bms")
pg.save(model, "resistivity_model.vector")
# Export to VTK for ParaView
mgr.mesh.exportVTK("result", mgr.model)
Array Types
| Code | Array |
|---|
wa | Wenner-alpha |
wb | Wenner-beta |
dd | Dipole-dipole |
pd | Pole-dipole |
pp | Pole-pole |
slm | Schlumberger |
gr | Gradient |
Data Formats
| Format | Extension | Description |
|---|
| BERT/pyGIMLi | .ohm | Unified data format |
| Syscal | .txt | IRIS export |
| Res2DInv | .dat | 2D inversion format |
| ABEM | .ohm | ABEM Terrameter |
| SRT | .sgt | Seismic traveltimes |
When to Use vs Alternatives
| Scenario | Recommendation |
|---|
| Standard ERT inversion with common arrays | pyGIMLi - simplest API, built-in array types |
| Seismic refraction tomography (SRT) | pyGIMLi - integrated SRT manager |
| Multi-method inversion (DC, magnetics, gravity, EM) | SimPEG - broader method coverage |
| Commercial ERT processing with reporting | Res2DInv - industry standard, GUI-based |
| Custom forward operators or research flexibility | SimPEG - more modular design |
| FEM-based geophysical modelling | pyGIMLi - native FEM mesh support |
Choose pyGIMLi when: You need near-surface geophysical inversion (ERT, SRT, IP) with minimal code. Its manager classes (ERTManager, SRTManager) handle the full workflow from data loading to inversion to visualization in a few lines.
Avoid pyGIMLi when: You need methods beyond near-surface (use SimPEG), or you require a commercial-grade reporting pipeline.
Common Workflows
ERT data inversion and visualization
- Load ERT data file with
ert.load("survey.ohm") - Inspect data: check measurement count with
data.size(), plot pseudosection - Remove outliers or bad data points
- Create
ERTManager with data - Run inversion:
mgr.invert(lam=20) (start with higher lambda) - Check chi-squared value (target ~ 1)
- Visualize result with
mgr.showResult() - Export mesh and model to VTK for ParaView:
mgr.mesh.exportVTK() - Adjust lambda and zWeight if needed, re-invert
Inversion Tips
- Start with higher lambda (50-100) and decrease
- Check data quality - remove outliers before inversion
- Use zWeight < 1 for layered structures
- Check coverage - low coverage = poorly resolved
- Chi-squared ~ 1 indicates good fit without overfitting
References
Scripts
