pyGIMLi - Open-source Research & Teaching Software

A tutorial for the SEG Near Surface Webinar series

Instructors: Florian Wagner¹, Thomas Günther² and Carsten Rücker³

¹ Geophysical Imaging and Monitoring, RWTH Aachen University, Germany
² Leibniz Institute for Applied Geophysics, Hannover, Germany
³ Institut für Angewandte Geowissenschaften, Technische Universität Berlin, Germany

About

In this webinar, we introduce you to pyGIMLi, an open-source software for Geophysical Inversion and Modelling. After giving some general information on pyGIMLi, we will demonstrate its potential by inverting field ERT data through adding increasing complexity.

Installation

We recommend installing a Python distribution locally. In case of installation problems, one can alternatively use Google Colab.

Local Python installation using conda

We recommend installing a Python distribution like miniforge or Anaconda.

• Install miniforge: https://github.com/conda-forge/miniforge#install
• follow the installation instructions on https://www.pygimli.org/installation.html
• open a terminal (on Windows Powershell prompt)

conda create -n pg -c gimli -c conda-forge pygimli=1.5 jupyter

or download the file https://github.com/gimli-org/SEGwebinar/environment.yml

mamba env create --file environment.yml

Activate the environment and call Jupyter Notebook:

conda activate pg
jupyter notebook

Google colab

1. Login to colab using your Google account.
2. Open new Notebook and choose the GitHub option
3. Paste the webinar URL https://github.com/gimli-org/SEGwebinar
4. Select the template or full notebook
5. Create your own notebook, starting with !pip install pygimli

License

This work is licensed under the Apache 2.0 License

Further reading

• pyGIMLi website with API reference and lots of tutorials and examples
• pyGIMLi tutorial given on Transform 2021 (with 2h Youtube tutorial)
• pyGIMLi tutorial given on Transform 2022 (with 2h Youtube tutorial)
• Jupyter Notebook collection using pyGIMLi
• Collection of Example data used here and on website

References

• Rücker, C., Günther, T., Wagner, F.M. (2017): pyGIMLi: An open-source library for modelling and inversion in geophysics, Computers & Geosciences 109, 106-123, doi:10.1016/j.cageo.2017.07.011.
• Hübner, R., Günther, T., Heller, K., Noell, U. & Kleber, A. (2017): Impacts of a capillary barrier on infiltration and subsurface stormflow in layered slope deposits monitored with 3-D ERT and hydrometric measurements. Hydrol. Earth Syst. Sci. 21, 5181-5199, doi:10.5194/hess-21-5181-2017.
• Jordi, C., Doetsch, J., Günther, T., Schmelzbach, C. & Robertsson, J.O.A. (2018): Geostatistical regularisation operators for geophysical inverse problems on irregular meshes. Geophysical Journal International 213, 1374-1386, doi:10.1093/gji/ggy055.
• Grünenbaum, N., Günther, T., Greskowiak, J., Vienken, T., Müller-Petke, M. & Massmann, G. (2023): Salinity distribution in the subterranean estuary of a meso-tidal high-energy beach characterized by Electrical Resistivity Tomography and Direct Push technology. J. of Hydrol. 617, 129074, doi:10.1016/j.jhydrol.2023.129074.
• Wunderlich, T., Fischer, P., Wilken, D., Hadler, H., Erkul, E., Mecking, R., Günther, T., Heinzelmann, M., Vött, A. & Rabbel, W. (2018): Constraining Electric Resistivity Tomography by Direct Push Electric Conductivity logs and vibracores: An exemplary study of the Fiume Morto silted riverbed (Ostia Antica, Western Italy). Geophysics 83(3), B87-B103, doi:10.1190/geo2016-0660.1.
• Wagner, F.M., Mollaret, C., Günther, T., Kemna, A., Hauck, A. (2019): Quantitative imaging of water, ice, and air in permafrost systems through petrophysical joint inversion of seismic refraction and electrical resistivity data. Geophys. J. Int. 219, 1866-1875. doi:10.1093/gji/ggz402.
• Ronczka, M., Günther, T., Grinat, M. & Wiederhold, H. (2020): Monitoring freshwater-saltwater interfaces with SAMOS - installation effects on data and inversion. Near Surf. Geophys. 18(4), 369-383, doi:10.1002/nsg.12115.
• Hübner, R., Heller, K., Günther, T. & Kleber, A. (2015): Monitoring hillslope moisture dynamics with surface ERT for enhancing spatial significance of hydrometric point measurements. Hydrology and Earth System Sciences 19(1), 225-240, doi:10.5194/hess-19-225-2015.
• Jiang, C., Igel, J., Dlugosch, R., Müller-Petke, M., Günther, T., Helms, J., Lang, J. & Winsemann (2020): Magnetic resonance tomography constrained by ground-penetrating radar for improved hydrogeophysical characterisation, Geophysics 85(6), JM13-JM26, doi:10.1190/geo2020-0052.1.
• Skibbe, N., Günther, T. & Müller-Petke, M. (2021): Improved hydrogeophysical imaging by structural coupling of two-dimensional magnetic resonance and electrical resistivity tomography. Geophysics 86 (5), WB135-WB146, doi:10.1190/geo2020-0593.1.
• Rochlitz, R., Becken, M. & Günther, T. (2023): Three-dimensional inversion of semi-airborne electromagnetic data with a second-order finite-element forward solver. Geophys. J. Int. 234(1), 528-545, doi:10.1093/gji/ggad056.