Articles | Volume 12, issue 1
Development and technical paper
02 Jan 2019
Development and technical paper |  | 02 Jan 2019

GemPy 1.0: open-source stochastic geological modeling and inversion

Miguel de la Varga, Alexander Schaaf, and Florian Wellmann

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Cited articles

Aug, C.: Modélisation géologique 3D et caractérisation des incertitudes par la méthode du champ de potentiel: PhD thesis, PhD thesis, ENSMP, Paris, 2004.
Ayachit, U.: The ParaView Guide: A Parallel Visualization Application, Kitware, Inc., USA, 2015.
Bardossy, G. and Fodor, J.: Evaluation of Uncertainties and Risks in Geology: New Mathematical Approaches for their Handling, Springer, Berlin, Germany, 2004.
Baydin, A. G., Pearlmutter, B. A., Radul, A. A., and Siskind, J. M.: Automatic differentiation in machine learning: a survey, arXiv preprint arXiv:1502.05767, 2015.
Bellman, R.: Dynamic Programming, Courier Corporation, Dover Books on Computer Science, 366 pp., ISBN:9780486317199, 2013.
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 probabilistic machine-learning and Bayesian inference frameworks.