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Create xarray.DataArrays from various subsurface data formats.

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Geoscience I/O for grids and horizons.

The goal of this project is to load and save various geoscience surface data formats (2D and 3D seismic horizons, grids, etc). The interchange formats are the xarray.DataArray (and xarray.Dataset where we need a collection of arrays). This format is convenient because it allows us to store a NumPy array with Pandas-like indexing (as opposed to ordinary NumPy positional indexing).

We've started with:

  • OpendTect horizons
  • ZMAP grids
  • Surfer grids
  • Petrel horizons

What formats would you like to see? Make an issue.


This library is on PyPI, so you can install it with:

pip install gio

To get the latest unstable release, you can install it from GitHub:

python -m pip install --upgrade


import gio

da = gio.read_surfer(fname)

See more examples in the notebooks folder.


Please get involved! See


You can run the tests (requires pytest and pytest-cov) with



This repo uses PEP 517-style packaging. Read more about this and about Python packaging in general.

Building the project requires build, so first:

pip install build

Then to build gio locally:

python -m build

The builds both .tar.gz and .whl files, either of which you can install with pip.

© 2022 Agile Scientific, openly licenced under Apache 2.0

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