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The Ultimate Python SEG-Y I/O with Cloud Support and Schemas

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SEG-Y

🚧👷🏻 This project is under active development, expect breaking changes the to API 👷🏻🚧 - March, 2024

This is an efficient and comprehensive SEG-Y parsing library.

See the documentation for more information.

This is not an official TGS product.

Features

The library utilizes numpy and fsspec, includes the reading from various local and remote resources at a high speed. It also allows the users to build their own SEG-Y specifications.

Installing segy

Clone the repo and install it using pip:

Simplest way to install segy is via pip from PyPI:

$ pip install segy

or install segy via conda from conda-forge:

$ conda install -c conda-forge segy

Extras must be installed separately on Conda environments.

For details, please see the installation instructions in the documentation.

Using segy

Please see the Command-line Usage for details.

For Python API please see the API Reference for details.

Reading Capabilities

It supports reading from local and cloud files (object store). It can read:

  • Sequential traces (fastest)
  • Disjoint sequential regions (fast)
  • Random traces (slow)

High Performance

The performance is high and to be proven with upcoming benchmarks. The initial subjective benchmarks is very acceptable.

Flexibility

The library provides a fully flexible, schematized SEG-Y structure, including data models and JSON schema parsing and validation.

Predefined SEG-Y Standards

It supports predefined SEG-Y "standards" for various versions. However, some versions are still in progress:

  • Rev 0 (1975)
  • Rev 1 (2002)
  • Rev 2 (2017)
  • Rev 2.1 (2023)

Custom SEG-Y Standards

You can build your own SEG-Y "standard" with composition of specs for:

  • Text header (file + extended)
  • Binary header
  • Traces (header + extended header + samples)

Contributing to segy

Contributions are very welcome. To learn more, see the Contributor Guide.

Licensing

Distributed under the terms of the Apache 2.0 license. segy 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. Current maintainer is Altay Sansal with the support of many more great colleagues.

The CI/CD tooling is loosely based on Hypermodern Python Cookiecutter with more modern tooling applied elsewhere.

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