Poldw: a Python code to denoise 3C seismic data with a new threshold-free polarization technique

What is it about?

The paper introduces a Python code named "poldw" that implements a novel method for denoising three-component (3C) seismic data using a threshold-free polarization technique. This technique enhances the signal-to-noise ratio by rotating the seismic data to concentrate the signal energy into a single component, while other components, which are assumed to contain noise, are minimized. The method is designed to work with linearly polarized signals and is particularly useful for processing microseismic data, which often have low signal-to-noise ratios. The authors provide both the code and a Jupyter notebook for users to apply and explore the method.

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Photo by NASA on Unsplash

Photo by NASA on Unsplash

Why is it important?

This work is significant because it offers a simple yet effective way to improve the quality of seismic data, which is crucial for various geophysical applications, including seismic event studies, reservoir characterization, and fracture monitoring. Traditional denoising methods often require complex parameter tuning or thresholding, which can be sensitive to the specific dataset. The poldw method reduces this complexity by eliminating the need for thresholding and offering robustness against non-Gaussian noise, making it a valuable tool for researchers and practitioners in the field of geophysics. The availability of the code and supporting materials further facilitates its adoption and application in real-world scenarios.

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