🎉 MDIO v1 is out. Ingestion and export for SEG-Y is fully functional with templates! However, there may still be minor issues. Please report any issues you encounter.
🚧👷🏻 We are actively working on updating the documentation and adding missing features to v1 release. Please check back later for more updates!
"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.
This is not an official TGS product.
Features
Shared Features
- Abstractions for common energy data types (see below).
- Cloud native chunked storage based on Zarr and fsspec.
- Standardized models for lossy and lossless data compression using Blosc and ZFP.
- 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.
- Optimized chunking logic for various seismic types using MDIO templates.
- Native Xarray data model and interface wrapper.
- Import seismic interpretation, horizon, data. FUTURE
Installing MDIO
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
Condaenvironments.
For details, please see the installation instructions in the documentation.
Using MDIO
Please see the Command-line Usage for details.
For Python API please see the API Reference for details.
Requirements
Minimal
Chunked storage and parallelization: zarr, dask, numba, and psutil.
SEG-Y Parsing: TGSAI/segy
CLI and Progress Bars: click, click-params, and tqdm.
Optional
Distributed computing [distributed]: distributed and bokeh.
Cloud Object Store I/O [cloud]: s3fs, gcsfs, and adlfs.
Lossy Compression [lossy]: zfpy
Contributing to MDIO
Contributions are very welcome. To learn more, see the Contributor Guide.
Licensing
Distributed under the terms of the Apache 2.0 license, MDIO is free and open source software.
Issues
If you encounter any problems, please file an issue along with a detailed description.
Credits
This project was established at TGS. The current maintainer is Brian Michell with the support of many more great colleagues.
Release files for multidimio 1.2.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| multidimio-1.2.2.tar.gz | 95.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| multidimio-1.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 233.4 kB
Release files / multidimio-1.2.2.tar.gz
| Download URL | multidimio-1.2.2.tar.gz |
|---|---|
| Size | 95.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
abaa0cce295255f594a83d12b27a93fcf07a7efc7be138271d8d84901521ad99
|
|
BLAKE2b-256 checksum How to use checksums |
0cc0e7b26fce7c1885346602b9ffe4524645fc00265b2eb4d0d445424def7c31
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Release files / multidimio-1.2.2-py3-none-any.whl
| Download URL | multidimio-1.2.2-py3-none-any.whl |
|---|---|
| Size | 138.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3ce5209400ee1a5964f09d07d3f16dd5834077bca5b178f4357e6dbebfe9953e
|
|
BLAKE2b-256 checksum How to use checksums |
792a6346834ce52e6276dd2e1cbfdb5d2265c24211762474603d9ca79c698091
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
