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We use two local attributes and a fast solver for local crosscorrelation to denoise the ambient noise CCFs for short period/high frequency recording, like nodal array or DAS

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Denoise_CCFs

We use two local attributes and a fast solver for local crosscorrelation to denoise the ambient noise CCFs for short-period/high-frequency recording, like a nodal array or DAS

Please kindly cite our paper by Bin He, David Lumley and Hejun Zhu, Improving signal-to-noise ratios of ambient noise cross-correlation functions using local attributes, 2024, Geophysical Journal International, ggae228, https://doi.org/10.1093/gji/ggae228.

How to use

The current version is based on Madagascar (https://www.reproducibility.org/wiki/Main_Page) and Noisepy (https://github.com/chengxinjiang/NoisePy)

Find more details in README in branch trail_version.o

Other requirement

OpenMPI

If you have questions about parallel computing for all virtual sources, please contact me at (binhebj@gmail.com)

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We use two local attributes and a fast solver for local crosscorrelation to denoise the ambient noise CCFs for short period/high frequency recording, like nodal array or DAS

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