Skip to main content

SimPEG: Simulation and Parameter Estimation in Geophysics

Project description

SimPEG Logo

SimPEG

Latest PyPI version MIT license Travis CI build status Coverage status codacy

Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.

The vision is to create a package for finite volume simulation with applications to geophysical imaging and subsurface flow. To enable the understanding of the many different components, this package has the following features:

  • modular with respect to the spacial discretization, optimization routine, and geophysical problem

  • built with the inverse problem in mind

  • provides a framework for geophysical and hydrogeologic problems

  • supports 1D, 2D and 3D problems

  • designed for large-scale inversions

You are welcome to join forum and engage with people who use and develop SimPEG at: https://groups.google.com/forum/#!forum/simpeg.

Overview Video

All of the Geophysics But Backwards

Working towards all the Geophysics, but Backwards - SciPy 2016

Citing SimPEG

There is a paper about SimPEG!

Cockett, R., Kang, S., Heagy, L. J., Pidlisecky, A., & Oldenburg, D. W. (2015). SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications. Computers & Geosciences.

BibTex:

@article{cockett2015simpeg,
  title={SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications},
  author={Cockett, Rowan and Kang, Seogi and Heagy, Lindsey J and Pidlisecky, Adam and Oldenburg, Douglas W},
  journal={Computers \& Geosciences},
  year={2015},
  publisher={Elsevier}
}

Electromagnetics

If you are using the electromagnetics module of SimPEG, please cite:

Lindsey J. Heagy, Rowan Cockett, Seogi Kang, Gudni K. Rosenkjaer, Douglas W. Oldenburg, A framework for simulation and inversion in electromagnetics, Computers & Geosciences, Volume 107, 2017, Pages 1-19, ISSN 0098-3004, http://dx.doi.org/10.1016/j.cageo.2017.06.018.

BibTex:

@article{heagy2017,
    title= "A framework for simulation and inversion in electromagnetics",
    author= "Lindsey J. Heagy and Rowan Cockett and Seogi Kang and Gudni K. Rosenkjaer and Douglas W. Oldenburg",
    journal= "Computers & Geosciences",
    volume = "107",
    pages = "1 - 19",
    year = "2017",
    note = "",
    issn = "0098-3004",
    doi = "http://dx.doi.org/10.1016/j.cageo.2017.06.018"
}

Project details


Release history Release notifications | RSS feed

This version

0.6.3

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

SimPEG-0.6.3.tar.gz (214.6 kB view details)

Uploaded Source

Built Distribution

SimPEG-0.6.3-py2.py3-none-any.whl (275.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file SimPEG-0.6.3.tar.gz.

File metadata

  • Download URL: SimPEG-0.6.3.tar.gz
  • Upload date:
  • Size: 214.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for SimPEG-0.6.3.tar.gz
Algorithm Hash digest
SHA256 2247531e15c2ed60fe708253981fe57b7d32cb2fbc1efd82eeaa2a1268d76c97
MD5 e3a50ecddd006f98b91735bf08053655
BLAKE2b-256 678104182c10f1615f8ca67da4adf045ed7fbbc8be9bbabd56c80e5559b0a3e7

See more details on using hashes here.

File details

Details for the file SimPEG-0.6.3-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for SimPEG-0.6.3-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 9196dc3b42af1912368f6f0e65982a6916af5e988b8b2b0c1dc3d2441279dc59
MD5 5db6d325a8c6e41c1cc4b7c940bd8237
BLAKE2b-256 4497ca246d78a6626a745806a15a71e5d290942e31be61176702684eab3a1cf3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page