pyGIMLi is an open-source multi-method library for modelling and inversion in
pyGIMLi-based research papers
Improved geophysical imaging through geostatistical regularization
Jordi et al. (2018), Geophysical Journal International
Petrophysical joint inversion for water, ice, and air
Wagner et al. (2019), Geophysical Journal International
Coupling underwater electrial resistivity and seismic refraction tomography
Ronczka et al. (2017), Solid Earth
Structural joint inversion with cross-gradients on irregular meshes
Jordi et al. (2020), Geophysical Journal International
Monitoring seawater intrusion dynamics with crosshole ERT
Palacios et al. (2020), Hydrol. Earth Syst. Sci.
Long-electrode ERT modelling study
Ronczka et al. (2015), Geophysics
Structural constraints on ERT derived from reflection seismics
Bergmann et al. (2014), Geophysics
Block joint electrical and resonance sounding inversion
Günther & Müller-Petke (2012), Hydrol. Earth Syst. Sci.
Cole-Cole and Debye fitting of SIP/DP spectroscopy
Loewer et al. (2017), Geophysical Journal International
Optimized survey design for storage reservoir monitoring
Wagner et al. (2015), Geophysics
Ice estimation in alpine permafrost via joint inversion
Mollaret et al. (2020), Front. Earth Sci.
Aquifer monitoring with long electrode ERT
Ronczka et al. (2015), Journal of Applied Geophysics
Complex EM modelling using the open-source code custEM
Rochlitz et al. (2018), Geophysics
Open-source 2D magnetic resonance tomography
Skibbe et al. (2020), Geophysics
Structurally coupled inversion of ERT and seismic refraction
Hellman et al. (2017), Journal of Applied Geophysics
Laterally-constrained inversion of airborne MRS
Costabel et al. (2016), Geophysics
Simulating the electrical response of seawater intrusion in Australia
Costall et al. (2020), Scientific Reports
Testing conceptual models in hydrogeology using remote sensing and geophysics
Enemark et al. (2020), Water Resources Research
Imaging electrified plant roots
Peruzzo et al. (2020), Plant and Soil
Improved imaging using parameter and structure constraints
Wunderlich et al. (2018), Geophysics
Coupling electrical and magnetic resonance soundings
Skibbe et al. (2018), Geophysics
Crosshole GPR with deep neural networks
Laloy et al. (2020)
Probabilistic inference of subsurface heterogeneity and interface geometry
de Pasquale et al. (2019), Geophysical Journal International
DC/IP imaging of trees
Martin & Günther (2013), European Journal of Forest Research
3D ERT monitoring of infiltration processes in a hillslope
Hübner et al. (2017), Hydrol. Earth Syst. Sci.
Spectrally constrained inversion of induced polarization data
Günther & Martin (2016), Journal of Applied Geophysics
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.
Check out the tutorials.
To get started, have a look at the
. Applications and user stories can be found in the
We want your help.
You found a bug or desperately miss a certain functionality? Fill out a
bug report or a feature
. If you have used pyGIMLi for an interesting application, consider
your example. Please cite the pyGIMLi paper
or derived ones when using it for scientific purposes.