DASdenoising package is used to store the reproducible and open-access scripts for denoising the FORGE DAS dataset
The python-version and a much accelerated (with C implementation and is hundreds of times faster) python-version functions are included in the pyseistr package (https://github.com/aaspip/pyseistr). An example can be found at https://github.com/aaspip/pyseistr/blob/main/demos/test_pyseistr_das.py Please follow the python package for future developments.
If you find this package useful, please do not forget to cite the following paper. The PDF of the paper can be found at https://github.com/chenyk1990/dasdenoising-dataonly/blob/main/reference.
Chen, Y., Savvaidis, A., Fomel, S., Chen, Y., Saad, O.M., Wang, H., Oboue, Y.A.S.I., Yang, L., & Chen, W. (2023). Denoising of distributed acoustic sensing seismic data using an integrated framework, Seismological Research Letters, 94(1), 457–472, doi: 10.1785/0220220117.
BibTeX:
@article{dasdenoising2023,
title={Denoising of distributed acoustic sensing seismic data using an integrated framework},
author={Yangkang Chen and Alexandros Savvaidis and Sergey Fomel and Yunfeng Chen and Omar M. Saad and Hang Wang and Yapo Abol{\'e} Serge Innocent Obou{\'e} and Liuqing Yang and Wei Chen},
journal={Seismological Research Letters},
year=2023,
volume=94,
issue=1,
pages={457–472},
doi={10.1785/0220220117},
}
Authors of the dasdenoising paper, 2021-present
GNU General Public License, Version 3
(http://www.gnu.org/copyleft/gpl.html)
Using the latest version
git clone https://github.com/chenyk1990/dasdenoising
cd dasdenoising
addpath(genpath('./')); #in Matlab command line
The "main" directory contains all runable scripts test_figNO.m to reproduce all figures in the paper.
- Matlab 2015 and later versions
The development team welcomes voluntary contributions from any open-source enthusiast.
If you want to make contribution to this project, feel free to contact the development team.
Regarding any questions, bugs, developments, collaborations, please contact
Yangkang Chen
chenyk2016@gmail.com
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To run the reproducible scripts (test_xxxx.m), please first download the required package from: https://github.com/chenyk1990/seistr.
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Please put the seistr package in the main directory and add its sub-directories to the Matlab toolbox path.
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The scripts beginning with "test_" are runnable scripts.
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The directory subroutines stores all the required subroutines.
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The directory fig_bpsomffk stores all the results from the proposed denoising workflow.
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The directory mat_raw stores all the segmented multi-channel DAS seismic data at the FORGE site.
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The directory mat_bpsomffk stores all the denoised DAS data.
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The current version is based on Matlab. Future versions will also support Python and be optimized regarding computational efficiency.
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All datasets used in these DEMO scripts or produced from massive processing based on this package are in a separate repository https://github.com/chenyk1990/dasdenoising-dataonly (for easier downloading).
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test_oneevent.m is an example script to run through all processing steps (the three filters) for a specific event. It is used for denoising all the raw waveforms and produce the denoised waveforms. Both raw and denoised waveforms are stored in the repository of https://github.com/chenyk1990/dasdenoising-dataonly.
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The difference between the two "similar repositories" dasdenoising and dasdenoising-dataonly is that the latter is only used for storing the data (several GBs) and the former is only used for storing the scripts (less than 1 MB).
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All figures (except for fig1, which is a schematic plot) in the dasdenoising paper are in the following directory for a quick look (https://github.com/chenyk1990/dasdenoising-dataonly/tree/main/gallery/).
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The python-version and accelerated (C-implementation) python-version functions are included in the pyseistr package (https://github.com/aaspip/pyseistr). An example can be found at https://github.com/aaspip/pyseistr/blob/main/demos/test_pyseistr_das.py . The Matlab version remains as an educational tool but will not be further developed in the future. Please just follow the latest python package (pyseistr).
The gallery figures of the dasdenoising package can be found at https://github.com/chenyk1990/dasdenoising-dataonly/tree/main/gallery/ Each figure in the gallery directory corresponds to a test_figNO.m script in the "main" directory with the exactly the same file name (figNO.png).
These gallery figures are also presented below.
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
