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Create xarray.DataArrays from various subsurface data formats.

Project description

gio

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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.

Installation

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/agilescientific/gio/archive/develop.zip

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)
da.plot()

Documentation

See the documentation for more examples, and for help developing gio or making contributions back to this project.

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