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.

Date: March 19, 2023

Recorded video: https://youtu.be/qbLGbSEWOSw

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.