cgre-aachen/gempy

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.

What's New: GemPy 2024.1 (a.k.a GemPy v3) Release!

Welcome to the era of GemPy v3! We are thrilled to announce the release of the latest version, a product of meticulous planning, redesign, and rigorous testing. While the core essence remains intact, v3 brings significant enhancements and novelties that promise to revolutionize your geomodeling experience.

Delve into the exciting new features in the What's New in GemPy v3.

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[base]

Resources

After installation, you can either check the notebook tutorials or the video introduction to get started.

Go to the documentation site for further information and enjoy the tutorials and examples.

For questions and support, please use discussions.

If you find a bug or have a feature request, create an issue.

Follow these guidelines to contribute to GemPy.

Gallery

Geometries

Features

Case studies

Publications using GemPy

• Brisson, S., Wellmann, F., Chudalla, N., von Harten, J., & von Hagke, C. (2023). Estimating uncertainties in 3-D models of complex fold-and-thrust belts: A case study of the Eastern Alps triangle zone. Applied Computing and Geosciences, 18, 100115.

• Liang, Z., de la Varga, M., & Wellmann, F. (2023). Kernel method for gravity forward simulation in implicit probabilistic geologic modeling. Geophysics, 88(3), G43-G55.

• Kong, S., Oh, J., Yoon, D., Ryu, D. W., & Kwon, H. S. (2023). Integrating Deep Learning and Deterministic Inversion for Enhancing Fault Detection in Electrical Resistivity Surveys. Applied Sciences, 13(10), 6250.

• Thomas, A. T., Micallef, A., Duan, S., & Zou, Z. (2023). Characteristics and controls of an offshore freshened groundwater system in the Shengsi region, East China Sea. Frontiers in Earth Science, 11, 1198215.

• Haehnel, P., Freund, H., Greskowiak, J. & Massmann, G. (2023) Development of a three-dimensional hydrogeological model for the island of Norderney (Germany) using GemPy. Geoscience Data Journal, 00, 1–17.

• Jüstel, A., de la Varga, M., Chudalla, N., Wagner, J. D., Back, S., & Wellmann, F. (2023). From Maps to Models-Tutorials for structural geological modeling using GemPy and GemGIS. Journal of Open Source Education, 6(66), 185.

• Sehsah, H., Eldosouky, A. M., & Pham, L. T. (2022). Incremental Emplacement of the Sierra Nevada Batholith Constrained by U-Pb Ages and Potential Field Data. The Journal of Geology, 130(5), 381-391.

• Schaaf, A., de la Varga, M., Wellmann, F., & Bond, C. E. (2021). Constraining stochastic 3-D structural geological models with topology information using approximate Bayesian computation in GemPy 2.1. Geosci. Model Dev., 14(6), 3899-3913. doi:10.5194/gmd-14-3899-2021

• Güdük, N., de la Varga, M. Kaukolinna, J. and Wellmann, F. (2021). Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit, Geosciences, 11(4):150. https://doi.org/10.3390/geosciences11040150.

• Wu, J., & Sun, B. (2021). Discontinuous mechanical analysis of manifold element strain of rock slope based on open source Gempy. In E3S Web of Conferences (Vol. 248, p. 03084). EDP Sciences.

• Stamm, F. A., de la Varga, M., and Wellmann, F. (2019). Actors, actions, and uncertainties: optimizing decision-making based on 3-D structural geological models, Solid Earth, 10, 2015–2043.

• Wellmann, F., Schaaf, A., de la Varga, M., & von Hagke, C. (2019). From Google Earth to 3D Geology Problem 2: Seeing Below the Surface of the Digital Earth. In Developments in Structural Geology and Tectonics (Vol. 5, pp. 189-204). Elsevier.

Please let us know if your publication is missing!

A continuously growing list of gempy-applications (e.g. listing real-world models) can be found here.

References

• de la Varga, M., Schaaf, A., and Wellmann, F. (2019). GemPy 1.0: open-source stochastic geological modeling and inversion, Geosci. Model Dev., 12, 1-32.
• Wellmann, F., & Caumon, G. (2018). 3-D Structural geological models: Concepts, methods, and uncertainties. In Advances in Geophysics (Vol. 59, pp. 1-121). Elsevier.
• 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.

gempy's Issues

Data decimation

Integration with noddy

• Add redundancy checking for data points
• Implement reliable azimuth calculation

Enhanced progress indicator

Whenever anything in gempy is compiled / computed and it takes a while, a progress bar can be shown to the user. This feature needs to work in a command line, no fancy gifs. Example: https://stackoverflow.com/questions/3173320/text-progress-bar-in-the-console

Increase the number of formats to be read

So far we only accept csv but pandas is waaay more tolerant that this. It cannot be to difficult to implement pandas power directly in gempy

Get extent automatically from the input data

Test that the prototype works fine

improve the visualization of scalar fields when there are more than 1 dep series

Each series is separeted with each other by 50 "units" to avoid to have the same values of the scalar field in two distinct depositional series. Due to this jump in the values to contour plot makes most of the isosurfaces in this range giving as a result a very bad plot

Adding explanation of interactivity in some tutorial

Getting the spill point mathematically

Finish the coKriging part I started in Australia

add the logic of the finite faults into the the fault_block method

Dynamic font size for topology plot

curently either fits publication OR notebook

Push faults automatically to the top of the pile

At the moment the first series whatever they are will act as faults

Improve the readme.md

mplstereonet function for foliations dataframe

• colored by formations
• default all or give list of desired formations
• and pole density option

Deleting points in vtk

Check DEP code

Mismatch of gp.create_data loaded csv files formation number

Loading interfaces and foliation DataFrames with gp.create_data seems to not load correctly the "formation number" column values. reordering seems to happen although it shouldn't

Once you get Gx and Gy in the surfaces interpolate when 0 (maybe marching cubes)

Check the doc strings

Add densities in the geodata pandas dataframes

Visualization of random parameters in 2D or 3D

Compilation progress symbol

|/-|/-|

Intersect planes

Pole sampling using van Mises Fisher distribution for orientations

@flohorovicic we should invite Evran to our repository so I can assign it to him

Socket connection

add an assert that u_grade len is equal to number of series

Faults Enhancements

Topology: 3-D visualization

bubbles and lines

Add text to the sequential pile

Interpolate Gradient Z in the theano piece

Check a better way to compute the gravity

• So far we do it with absolutes values. In principle it has to be taken into account the background pull?
• Also because gempy's models are rescaled between 0 and 1 the absolute units are kind of crazy at the moment. See how is done in other projects

Check if or why it is necessary brackets on the faults keyword when we set series

can you two (@fastamo, @funveen) check this and if we can fix it?

Create error message if input data contains only one point per formation (2 necessary)

Conda installer

Try again to set up the conda installer enviroment

GPU optimization

• Reduce the unnecessary tiling
• Assign different operation to different devices

Give the option to choose between editing mode/or just view modei vtk when we call it and after

This issue (1k years old) was to add a flag to our old vtk renderer to make the model edition in real time or on off. In the old gempy vtk render I also added a key to change between modes on the fly.

Now, my question is @pytzcarraldo in pyvista if we have different objects for editing or viewing mode is there a easy way to change between them?

The solutions that come to my mind is:

1. We only allow to change between editing/viewing mode with a shortcut if since the beginning we are using the widgets for the data

2. We delete all the input data objects and recreate them either as widget or static symbols

Add assert to the gravity computation about the precomputations

At the moment when we create the theano graph to compute gravity (this is choose with a flag when we call the InterpData) we never check that the geophysics precomputations are ran before we call the theano function. This rise an error of theano complaining that some dimensions do not match.

It would be much better to have somewhere an assert with a error message written by us saying that before the gravity can be solved in theano we need to run the methods to select the voxels and decompose tx ty tz

Make assert of at least one dip per series

Adding points via vtk interactively

• series and formation options

Tut 2 path issue

---

TypeError Traceback (most recent call last)
in ()
----> 1 gp.export_to_vtk(geo_data, lith_block=lith_block[0], vertices=vertices, simplices=simplices)

~\gempy\gempy\gempy_front.py in export_to_vtk(geo_data, path, name, lith_block, vertices, simplices)
237 """
238 if lith_block is not None:
--> 239 vtkVisualization.export_vtk_lith_block(geo_data, lith_block, path=path+str('v'))
240 if vertices is not None and simplices is not None:
241 vtkVisualization.export_vtk_surfaces(vertices, simplices, path=path+str('s'), name=name)

TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'

Integration with geomodeller

Write and read the xml

update qgrid

In the last version of qgrid it seems that they have a method to retrieve the edited dataframe so we can recompute all the changes.

Adding Theano explanation to the documentation

@fastamo @Leguark
Taking the stuff from the paper an make a page for the documentation

fix topology edge classification (dependency changed)

Export gempy colormap to paraview

Merge compute gradient and compute orientation into a method

at the moment there are two distinct methods. It would be good to merge them and check that there is not contradictory data in the dataframe

Pseudo-3-D plot of data from r-geomod

Get topology module ready for 1.0 release

• refactoring if necessary
• documentation
• forwarding of needed functions to gempy_front
• fix adjacency storage
• integrate fabians function

Make standard likelihoods to avoid scalar fields artefacts due to stochasticity