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GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.

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Open-source, implicit 3D structural geological modeling in Python.

PyPI PyPI license: LGPL v3 Documentation Status Travis Build Binder DOI DOCKER

Overview

GemPy is a Python-based, open-source geomodeling library. It is capable of constructing complex 3D geological models of folded structures, fault networks and unconformities, based on the underlying powerful implicit representation approach.

Installation

We provide the latest release version of GemPy via PyPi package services. We highly recommend using PyPi,

$ pip install gempy

as it will take care of automatically installing all the required dependencies - except in windows that requires one extra step.

Windows does not have a gcc compilers pre-installed. The easiest way to get a theano compatible compiler is by using the theano conda installation. Therefore the process would be the following:

$ conda install theano

$ pip install gempy

For more information, refer to the installation documentation

Resources

References

  • de la Varga, M., Schaaf, A., and Wellmann, F.: GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1-32, https://doi.org/10.5194/gmd-12-1-2019, 2019
  • Calcagno, P., Chilès, J. P., Courrioux, G., & Guillen, A. (2008). Geological modelling from field data and geological knowledge: Part I. Modelling method coupling 3D potential-field interpolation and geological rules. Physics of the Earth and Planetary Interiors, 171(1-4), 147-157.
  • Lajaunie, C., Courrioux, G., & Manuel, L. (1997). Foliation fields and 3D cartography in geology: principles of a method based on potential interpolation. Mathematical Geology, 29(4), 571-584.

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GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to address parameter and model uncertainties.

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  • Python 54.8%
  • Jupyter Notebook 44.9%
  • Other 0.3%