Probing Earth’s conductivity structure beneath oceans by scalar geomagnetic data: autonomous surface vehicle solution

Alexey Kuvshinov, Jürgen Matzka, Benny Poedjono, Friedemann Samrock, Nils Olsen, Sudhir Pai

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

The electric conductivity distribution of the Earth’s crust and upper mantle provides a key to unraveling its structure. Information can be obtained from vector data time series of the natural variations of the magnetic and electric field in a directional stable reference frame. Applying this method, known as magnetotellurics, to oceanic regions is challenging since only vector instruments placed at the sea bottom can provide such data. Here, we discuss a concept of marine induction surveying which is based on sea-surface scalar magnetic field measurements from a modern position-keeping platform. The concept exploits scalar magnetic responses that relate variations of the scalar magnetic field at the survey sites with variations of the horizontal magnetic field at a reference site. A 3-D model study offshore Oahu Island (Hawaii) demonstrates that these responses are sensitive to the conductivity structure beneath the ocean. We conclude that the sensitivity, depending on the bathymetry gradient, is typically largest near the coast offshore. We show that such sea-surface marine induction surveys can be performed with the Wave Glider, an easy-to-deploy, autonomous, energy-harvesting floating platform with position-keeping capability. Graphical abstract .
Original languageEnglish
Article number189
JournalEarth, Planets and Space
Volume68
Issue number1
Number of pages11
ISSN1343-8832
DOIs
Publication statusPublished - 2016

Bibliographical note

© The Author(s) 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Keywords

  • Marine EM
  • Wave Glider
  • Scalar magnetic field variations

Cite this

Kuvshinov, Alexey ; Matzka, Jürgen ; Poedjono, Benny ; Samrock, Friedemann ; Olsen, Nils ; Pai, Sudhir. / Probing Earth’s conductivity structure beneath oceans by scalar geomagnetic data: autonomous surface vehicle solution. In: Earth, Planets and Space. 2016 ; Vol. 68, No. 1.
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abstract = "The electric conductivity distribution of the Earth’s crust and upper mantle provides a key to unraveling its structure. Information can be obtained from vector data time series of the natural variations of the magnetic and electric field in a directional stable reference frame. Applying this method, known as magnetotellurics, to oceanic regions is challenging since only vector instruments placed at the sea bottom can provide such data. Here, we discuss a concept of marine induction surveying which is based on sea-surface scalar magnetic field measurements from a modern position-keeping platform. The concept exploits scalar magnetic responses that relate variations of the scalar magnetic field at the survey sites with variations of the horizontal magnetic field at a reference site. A 3-D model study offshore Oahu Island (Hawaii) demonstrates that these responses are sensitive to the conductivity structure beneath the ocean. We conclude that the sensitivity, depending on the bathymetry gradient, is typically largest near the coast offshore. We show that such sea-surface marine induction surveys can be performed with the Wave Glider, an easy-to-deploy, autonomous, energy-harvesting floating platform with position-keeping capability. Graphical abstract .",
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Probing Earth’s conductivity structure beneath oceans by scalar geomagnetic data: autonomous surface vehicle solution. / Kuvshinov, Alexey; Matzka, Jürgen; Poedjono, Benny; Samrock, Friedemann; Olsen, Nils; Pai, Sudhir.

In: Earth, Planets and Space, Vol. 68, No. 1, 189, 2016.

Research output: Contribution to journalJournal articleResearchpeer-review

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AU - Olsen, Nils

AU - Pai, Sudhir

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