“MDIO” is a library to work with large multidimensional energy datasets. The primary motivation behind MDIO is to represent multidimensional time series data in a format that makes it easier to use in resource assessment, machine learning, and data processing workflows.
See the documentation for more information.
Abstractions for common energy data types (see below).
Distributed reads and writes using Dask.
Powerful command-line-interface (CLI) based on Click
Domain Specific Features
Oil & Gas Data
Import and export 2D - 5D seismic data types stored in SEG-Y.
Import seismic interpretation, horizon, data. FUTURE
Optimized chunking logic for various seismic types. FUTURE
Wind Resource Assessment
Numerical weather prediction models with arbitrary metadata. FUTURE
Optimized chunking logic for time-series analysis and mapping. FUTURE
Xarray interface. FUTURE
The features marked as FUTURE will be open-sourced at a later date.
Simplest way to install MDIO via pip from PyPI:
$ pip install multidimio
or install MDIO via conda from conda-forge:
$ conda install -c conda-forge multidimio
Extras must be installed separately on
For details, please see the [installation instructions][install] in the documentation.
Please see the [Command-line Reference][usage] for details.
For Python API please see the [API Reference][reference] for details.
Chunked storage and parallelization:
CLI and Progress Bars:
Cloud Object Store I/O
Contributing to MDIO#
Contributions are very welcome. To learn more, see the Contributor Guide.
Distributed under the terms of the Apache 2.0 license, MDIO is free and open source software.
If you encounter any problems, please file an issue along with a detailed description.
This project was established at TGS. Original authors and current maintainers are Altay Sansal and Sri Kainkaryam; with the support of many more great colleagues.
This project template is based on @cjolowicz’s Hypermodern Python Cookiecutter template.