Create xarray.DataArrays from various subsurface data formats.
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.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 https://github.com/agile-geoscience/gio/archive/develop.zip
In general, there's a reader for each supported file format. The reader produces an
xarray.Dataset if the format supports multiple surfaces in one file.
import gio da = gio.read_surfer(fname) da.plot()
There are currently no output functions; combing soon!
See the documentation for more examples.
Please get involved! See CONTRIBUTING.md.
You can run the tests (requires
Building the project requires
build, so first:
pip install build
Then to build
python -m build
The builds both
.whl files, either of which you can install with
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.