GemPy 1.0: open-source stochastic geological modeling and inversion

Miguel de la Varga (Corresponding Author), Alexander Schaaf, Florian Wellmann

Research output: Contribution to journalArticle

3 Citations (Scopus)
6 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)1-32
Number of pages32
JournalGeoscientific Model Development
Volume12
Early online date6 Mar 2018
DOIs
Publication statusPublished - 2 Jan 2019

Fingerprint

Stochastic Modeling
Open Source
Inversion
3D Model
modeling
Fault
Interpolate
Python
Dome
interpolation
Code Generation
Potential Field
Interpolation
Bayesian inference
Model
Programming Languages
Gravity
Machine Learning
Geological surveys
Branch

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)
  • Modelling and Simulation

Cite this

GemPy 1.0 : open-source stochastic geological modeling and inversion. / de la Varga, Miguel (Corresponding Author); Schaaf, Alexander; Wellmann, Florian.

In: Geoscientific Model Development, Vol. 12, 02.01.2019, p. 1-32.

Research output: Contribution to journalArticle

de la Varga, Miguel ; Schaaf, Alexander ; Wellmann, Florian. / GemPy 1.0 : open-source stochastic geological modeling and inversion. In: Geoscientific Model Development. 2019 ; Vol. 12. pp. 1-32.
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