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Create xarray.DataArrays from various subsurface data formats.

Project description


Tests PyPI version PyPI versions PyPI license

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

Basic usage

In general, there's a reader for each supported file format. The reader produces an xarray.DataArray, or xarray.Dataset if the format supports multiple surfaces in one file.

import gio

da = gio.read_surfer(fname)

There are currently no output functions; combing soon!


See the documentation for more examples.


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.

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