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Abstract

Summary

This article examines the application of robust smoothing techniques to enhance the processing of Magnetotelluric (MT) data, a vital geophysical method for investigating subsurface electrical properties. The MT method captures natural electromagnetic fields generated by phenomena such as lightning and solar activity, which provide insights into the Earth’s interior. Effective data processing is essential for extracting meaningful information and involves several steps, including noise reduction, impedance estimation, and visualization. This study focuses on a dataset from the Rochechouart impact structure in France, comparing straightforward processing methods with those enhanced by robust smoothing techniques. The research addresses common challenges in MT data processing, particularly the presence of outliers when merging datasets from different sampling frequencies. By employing the Huber M-estimator and bisquare weight functions in an iterative process, the proposed robust smoothing method minimizes the influence of outliers and improves the reliability of resistivity and phase curve estimates. Results demonstrate that this approach not only enhances data quality but also provides more stable estimates of subsurface electrical properties. This work contributes valuable insights into improving MT data processing methodologies, ultimately advancing our understanding of geological structures beneath the Earth’s surface.

© EAGE Publications BV
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2025-06-02
2026-02-12

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/content/papers/10.3997/2214-4609.2025101275
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Enhancing Magnetotelluric Data Processing through Robust Smoothing Techniques
Conference Proceedings 2025, 1 (2025); https://doi.org/10.3997/2214-4609.2025101275
/content/papers/10.3997/2214-4609.2025101275
/content/papers/10.3997/2214-4609.2025101275
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