LAUSR

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.