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:
[x] Rev 0 (1975)
[x] 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.