What is it about?

Gravity gradiometry measurements are contaminated by high‐frequency noise. We propose an automatic, wavelet filtering technique specially designed to process gravity gradiometry data. We compare the proposed method with frequency‐domain filters by applying them to synthetic data sets contaminated with noise. The results demonstrate that the proposed filter is efficient and produces results that are comparable to the best results achievable through traditional filters.

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Why is it important?

Separation of the high‐frequency signal from noise is a crucial component of data processing. The separation can be performed in the frequency domain, which usually requires tuning filter parameters to obtain optimal results. Because gradiometry survey generates more data than traditional gravity, such time‐consuming operations are not very practical and may introduce subjectivity into the process. To address this difficulty, we propose an automatic wavelet filtering technique based on the thresholding of the wavelet coefficients to filter out high‐frequency noise while preserving localized sharp signal features. Read More: https://library.seg.org/doi/10.1190/1.1759463

Perspectives

This article was written having in mind the difficulties found along the work with gravity gradient data, which besides all other difficulties commonly found in dealing with any potential field data, has the additional complications caused by larger amounts of data. I hope it helps people that needs robust results in limited amount of time. Additionally, finding a solution through wavelet denoising was very gratifying because it allowed me, and I hope others as well, the discovery of these interesting elements of the Mathematics called wavelets.

Dr. Julio Lyrio
Petrobras

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This page is a summary of: Efficient automatic denoising of gravity gradiometry data, Geophysics, May 2004, Society of Exploration Geophysicists,
DOI: 10.1190/1.1759463.
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