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Werthmüller, D., R. Rochlitz, O. Castillo-Reyes, and L. Heagy, 2021, Towards an open-source landscape for 3-D CSEM modelling: Geophysical Journal International, 227(1), 644--659

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Towards an open-source landscape for 3-D CSEM modelling

Werthmüller, D., R. Rochlitz, O. Castillo-Reyes, and L. Heagy, 2021, Towards an open-source landscape for 3-D CSEM modelling: Geophysical Journal International, 227(1), 644--659; DOI: 10.1093/gji/ggab238.

This repository contains the LaTeX source of the manuscript as well as the necessary codes to reproduce all the results and figures.

Repository structure

├── environment.yml  # Python environment file
├── LICENSE          # CC-BY-SA-4.0 License
├── README.md        # this file
├── manuscript/      # LaTeX-files
│   └── figures/     # figures used in manuscript
├── model-{MODEL}/   # for MODEL in {block, marlim}
│   ├── README.md    # info about MODEL
│   ├── {CODE}/      # for CODE in {custEM, emg3d, PETGEM, SimPEG}
│   └── results/     # results of the different codes
└── presentation/    # talk given at the AGU 2020

Each model-{MODEL}/-directory contains a README.md with more information about the particular model.

History

  1. 2020-10-23: Submitted to Geophysical Journal International.
  2. 2021-02-15: Revision I submitted.
  3. 2021-04-15: Revision II submitted.
  4. 2021-06-08: Revision III submitted.
  5. 2021-06-16: Accepted.

Data

The information in this repo is enough to reproduce all results and figures shown in the manuscript. Our results are available at 10.5281/zenodo.4535602.

Environment

The environment.yml file generates a conda-environment (see Anaconda Python Distribution) with all the required dependencies. To create the environment simply run

conda env create -f environment.yml

This will create a new conda environment called csem.

To activate the environment run

conda activate csem

and to deactivate it run

conda deactivate

To use this environment in the Jupyter notebook, you have to register it first:

python -m ipykernel install --user --name csem

Then, in the Jupyter notebook (or Jupyter lab), you can select it by going to Kernel->Change kernel and select csem.

To completely remove the environment run

conda remove --name csem --all

You need at least Python 3.7 to run (at least some of) the codes.

Dependencies

Dependencies are a difficult topic, and no-one can guarantee that the scripts will still work a few years down to road with many new releases of all dependencies. We list here therefore the most important dependencies that were used when creating the results.

Note that all notebooks (data creation, results, and computation of emg3d and SimPEG) have a scooby-report at the end, listing the most important dependencies and their version.

emg3d

The following is the emg3d-scooby report. You can get your own either in Python via emg3d.Report() or in the terminal via emg3d --report.

--------------------------------------------------------------------------------
  Date: Thu Jun 17 14:50:50 2021 CEST

                OS : Linux
            CPU(s) : 4
           Machine : x86_64
      Architecture : 64bit
               RAM : 15.5 GB
       Environment : Python

  Python 3.8.0 | packaged by conda-forge | (default, Nov 22 2019, 19:11:38)
  [GCC 7.3.0]

             numpy : 1.19.5
             scipy : 1.6.0
             numba : 0.52.0
             emg3d : 0.16.0
           empymod : 2.0.4
            xarray : 0.16.2
        discretize : 0.6.2
              h5py : 3.1.0
        matplotlib : 3.3.3
           IPython : 7.19.0

  Intel(R) Math Kernel Library Version 2020.0.4 Product Build 20200917 for
  Intel(R) 64 architecture applications
--------------------------------------------------------------------------------

custEM

custEM     1.0.0
fenics     2019.1
pygimli    1.1.0
tetgen     1.51

PETGEM

petgem     0.8
petsc      3.7
petsc4py   3.7
python     3.6.1
numpy      1.18.3
scipy      1.5.2
gmsh       4.5.4

SimPEG

The following an excerpt from the SimPEG-scooby report. You can get your own either in Python via SimPEG.Report() or in the terminal via python -c 'import SimPEG; print(SimPEG.Report())'.

                OS : Linux
            CPU(s) : 8
           Machine : x86_64
      Architecture : 64bit
               RAM : 413.4 GB
       Environment : Python
  Python 3.7.9 | packaged by conda-forge | (default, Dec  9 2020, 21:08:20)
  [GCC 9.3.0]
            SimPEG : 0.14.3
        discretize : 0.6.2
       pymatsolver : 0.1.2
        vectormath : 0.2.2
        properties : 0.6.1
             numpy : 1.19.2
             scipy : 1.2.1
        matplotlib : 3.3.4

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Werthmüller, D., R. Rochlitz, O. Castillo-Reyes, and L. Heagy, 2021, Towards an open-source landscape for 3-D CSEM modelling: Geophysical Journal International, 227(1), 644--659

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