Abstract

A noise that recorded at magnetotelluric acquisition data makes the data quality not good enough, so the information obtained after data processing might not be correct or not suitable for the subsurface condition. Several characters of noisy magnetotelluric data are the spiky shaped and non-stationarity time-series curves. This non-stationarity character can't be handled by the Fourier Transformation process. This research used Empirical Mode Decomposition (EMD) in the original of Huang as a filtering method in order to overcome the non-stationarity. This method decomposed the signal into a group of oscillation mode called Intrinsic Mode Decomposition (IMF). It is one of the best IMF chosen as the filtering result by spectrum analysis in the frequency domain. This work used magnetotelluric data from a station that had three components with different frequency sampling, which was 15 Hz, 150 Hz, and 2400 Hz. IMF filtering method then applied to the data resulting in a smoother times-series curve with the suppressed non-stationarity character. This research showed that EMD filtering can be implemented at magnetotelluric data processing and emphasized the effect caused by noise.

Original languageEnglish
Title of host publicationInternational Conference on Electromagnetism, Rock Magnetism and Magnetic Material, ICE-R3M 2019
EditorsSunaryono Sunaryono, Ann Marie Hirt, Jason Scott Herrin, Nordiana Mohd Muztaza, Markus Diantoro, Satria Bijaksana
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735420106
DOIs
Publication statusPublished - 18 Aug 2020
Event2019 International Conference on Electromagnetism, Rock Magnetism and Magnetic Material, ICE-R3M 2019 - Malang, Indonesia
Duration: 18 Sept 201919 Sept 2019

Publication series

NameAIP Conference Proceedings
Volume2251
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference2019 International Conference on Electromagnetism, Rock Magnetism and Magnetic Material, ICE-R3M 2019
Country/TerritoryIndonesia
CityMalang
Period18/09/1919/09/19

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