pyGIMLi is an open-source multi-method library for modeling and inversion in geophysics.

Showcase pyGIMLi-based research papers

Improved geophysical images through geostatistical regularization
Jordi et al. (2018), Geophysical Journal International

DC/IP imaging of trees
Martin & Günther (2013), European Journal of Forest Research

Improved imaging using parameter and structure constraints
Wunderlich et al. (2018), Geophysics

Structurally coupled inversion of electrical resistivity and seismic refraction data
Hellman et al. (2017), Journal of Applied Geophysics

3D ERT monitoring of infiltration processes
Hübner et al. (2017), Hydrol. Earth Syst. Sci.

Long-electrode ERT modelling study
Ronczka et al. (2015), Geophysics

Coupling electrical and magnetic resonance soundings
Skibbe et al. (2018), Geophysics

Complex EM modelling using Open-Source custEM
Rochlitz et al. (2018), Geophysics

Cole-Cole and Debye fitting of SIP/DP spectroscopy
Loewer et al. (2017), Geophysical Journal International

Block Joint VES and MRS inversion
Günther & Müller-Petke (2012), Hydrol. Earth Syst. Sci.

Optimized survey design for storage reservoir monitoring
Wagner et al. (2015), Geophysics

Structurally constrained RST for improved permafrost characterization
Steiner et al. (2019), The Cryosphere Discuss.

Laterally-constrained inversion of airborne MRS
Costabel et al. (2016), Geophysics

Coupling underwater electrial resistivity and seismic refraction tomography
Ronczka et al. (2017), Solid Earth

Structural contraints on ERT derived from reflection seismics
Bergmann et al. (2014), Geophysics

Probabilistic inference of subsurface heterogeneity and interface geometry
de Pasquale et al. (2019), Geophysical Journal International

Spectral induced polarization constraints
Günther & Martin (2016), Journal of Applied Geophysics

Aquifer monitoring with long electrodes
Ronczka et al. (2015), Journal of Applied Geophysics

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Get pyGIMLi. Available for different platforms.

pyGIMLi has been successfully compiled on Windows, various Linux distributions and Mac OS X. See the installation section for more details on how to install or build pyGIMLi.

Get started. Check out the tutorials.

To get started, have a look at the pyGIMLi tutorials. Applications and user stories can be found in the Example section. You can test all tutorials and examples as Jupyter Notebooks without installation at try.pygimli.org!

Get involved.

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If you have used pyGIMLi for an interesting application, consider sending us your example. Please cite the pyGIMLi paper or derived ones when using it for scientific purposes.