Skip to main content

subsurface

DataHub for geoscientific data in Python. Two main purposes:

  • Unify geometric data into data objects (using numpy arrays as memory representation) that all the packages of the stack understand

  • Basic interactions with those data objects:

    • Write/Read
    • Categorized/Meta data
    • Visualization

Data Levels

The difference between data levels is not which data they store but which data they parse and understand. The rationale for this is to be able to pass along any object while keeping the I/O in subsurface::

            HUMAN

\‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾‾/
= = = = = = = = = = = = = = /. \ -> Additional context/meta information about the data = = = = geo_format= = = = /. .
= = = = = = = = = = = = /. . . \ -> Elements that represent some = = = geo_object= = = /. . . . \ geological concept. E.g: faults, seismic = = = = = = = = = = /. . . . ./ = = element = = = /. . . . / -> type of geometric object: PointSet, = = = = = = = = /. . . ./ TriSurf, LineSet, Tetramesh \primary_struct/. . . / -> Set of arrays that define a geometric object: = = = = = = /. . ./ e.g. StructuredData, UnstructuredData \DF/Xarray /. . / -> Label numpy.arrays = = = = /. ./ \array /. / -> Memory allocation = = /./ = // /

           COMPUTER

Documentation (WIP)

Note that subsurface is still in early days; do expect things to change. We welcome contributions very much, please get in touch if you would like to add support for subsurface in your package.

An early version of the documentation can be found here:

https://softwareunderground.github.io/subsurface/

Direct links:

  • Developers-guide <https://softwareunderground.github.io/subsurface/maintenance.html>_
  • Changelog <https://softwareunderground.github.io/subsurface/changelog.html>_

Installation

.. code-block:: console

pip install subsurface

or

.. code-block:: console

conda install -c conda-forge subsurface

Be aware that to read different formats you will need to manually install the specific dependency (e.g. welly to read well data).

Metadata

Release files for subsurface-terra 2026.2.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for subsurface-terra 2026.2.3
File Size Uploaded
subsurface_terra-2026.2.3.tar.gz 250.5 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for subsurface-terra 2026.2.3
File Interpreter ABI Platform
subsurface_terra-2026.2.3-py3-none-any.whl Python 3 none any Details

Total release size: 366.2 kB

Release files / subsurface_terra-2026.2.3.tar.gz

Download URL subsurface_terra-2026.2.3.tar.gz
Size 250.5 kB
Tags Source
SHA-256 checksum
How to use checksums
3bc53627b18bf7e94a99815ad6dc79dc93693179fb4038e867084917900deb16
BLAKE2b-256 checksum
How to use checksums
7340edae93c7f90c0ab37b51e1525e4f3a3e1e2e1ff2fbccb722ac177c592708
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.5

Release files / subsurface_terra-2026.2.3-py3-none-any.whl

Download URL subsurface_terra-2026.2.3-py3-none-any.whl
Size 115.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
4a0a8bd6d9f491c782842aa18beb2dd33e50af53fdfe78a5a77dab6fdd3c1034
BLAKE2b-256 checksum
How to use checksums
90dad66c9c0bbe17018bb95f07a79b3959f5262d7c7fe2bfe375830166e6122e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.5
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page