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Robust data processing of noisy marine controlled-source electromagnetic data using independent component analysis

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Pages 21-29 | Received 23 Oct 2017, Accepted 25 Oct 2017, Published online: 06 Dec 2018
 

Abstract

Data processing techniques are often used to estimate the noise-free response of marine controlled-source electromagnetic (CSEM) data and magnetotelluric transfer functions. We have implemented a new CSEM data processing scheme that uses a robust method based on independent component analysis (ICA) to extract interpretable datasets from noisy marine CSEM data. We applied the data processing scheme to signals from a new CSEM observation system comprising a remotely operated vehicle (ROV) and an ocean bottom electromagnetometer (OBEM). These datasets were obtained around the Iheya North hydrothermal field, Okinawa Trough, Japan. The observation system allows a small-scale CSEM survey to be conducted in areas of steep topography, such as hydrothermal fields, because the ROV can deploy the OBEM at the exact observation site. The results show that the coherent and environment noise that exists in the raw time series is reduced sufficiently by ICA processing. It makes interpretation of the resulting electric field data possible. The results also show that the processed data has a higher signal-to-noise ratio in the middle-to-high-frequency band than the data without ICA. The normalised spectrum, obtained by normalising the observed data from the hydrothermal area, indicates that a conductive anomaly exists in the near-offset area around the OBEM. We apply 2D inversion to the electric field data and find that a low resistivity body exists beneath the OBEM and 50 m offset from the OBEM. This resistivity structure is consistent with images taken by the ROV that show characteristic organisms in hydrothermal seepage around the OBEM site.

We have developed a new controlled-source electromagnetic (CSEM) data processing scheme that uses a robust method based on independent component analysis to extract interpretable datasets from noisy marine CSEM data. The results show that the coherent and environment noise is reduced sufficiently. It makes interpretation of the resulting data possible.

Acknowledgements

The authors thank the two anonymous reviewers for their fruitful suggestions and comments. They are grateful for the many efforts and kindness of Hiroyuki Yamamoto, JAMSTEC, Chief Scientist on the NT13–22 cruise. The authors also thank the Captain, crew and technicians of R/V Natsushima, the operating team of ROV Hyper-Dolphin and supporting members for their cooperation. This project is supported by MEXT (Ministry of Education, Culture, Sports, Science and Technology of Japan), in a development program of fundamental tools for exploration of deep seabed resources, and partly by JSPS KAKENHI Grant Numbers 26289347, 26249060, 26282101, 15H03715 and 15H05815.

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