Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2018-61
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Development and technical paper
06 Mar 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
GemPy 1.0: open-source stochastic geological modeling and inversion
Miguel de la Varga, Alexander Schaaf, and Florian Wellmann Institute for Computational Geoscience and Reservoir Engineering
Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications: ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research studies and applications in geological surveys. A wide range of methods exists to generate geological models. However, especially the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geomodeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D geological models, including fault networks, fault-surface interactions, unconformities, and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (theano) that enables a direct execution on GPU's. The functionality can be separated into the core aspects required to generate 3-D geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to Machine Learning and Bayesian inference frameworks and thus a path to stochastic geological modeling and inversions. In addition, we provide methods to analyse model topology and to compute gravity fields on the basis of the geological models and assigned density values. In summary, we provide a basis for open scientific research using geological models, with the aim to foster reproducible research in the field of geomodeling.
Citation: de la Varga, M., Schaaf, A., and Wellmann, F.: GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-61, in review, 2018.
Miguel de la Varga et al.
Miguel de la Varga et al.

Model code and software

GemPy M. de la Varga, A. Schaaf, F. Wellmann, F. Stamm, C. Meeßen, and F. Wagner https://doi.org/10.5281/zenodo.1186117
Miguel de la Varga et al.

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Short summary
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. GemPy is implemented in the programming language Python, making use of a highly efficient underlying library – theano for efficient code generation that performs automatic differentiation. This enables the link to Machine Learning and Bayesian inference frameworks.
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows...
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