Imaging of the West Indian Ocean Subsurface using Compliance from Ocean-Bottom Stations

This research focuses on deriving the compliance function from data collected by broadband ocean-bottom stations (OBS) during the RHUM- RUM experiment in the Indian Ocean. The primary objective is to determine the shear velocity structure beneath the ocean floor, a task essential for understanding the geological features of regions where data is sparse. The methodology revolves around analyzing the compliance function, a measure of the seafloor’s deformation in response to infra-gravity pressure signals at low frequencies (0.003 to 0.04 Hz). The compliance function, which represents the transfer function between vertical displacement and pressure, is greatly influenced by the shear velocity of the oceanic sub-structure beneath the station.

Our approach included several processing steps applied to the OBS data. These steps encompassed the removal of glitches, filtering out global and local seismic events, minimizing tilt effects, calibrating pressure gauges, and performing a linear search in the frequency and coherence domains to identify the optimal data window. The compliance function was computed using data recorded over 13 months in 2012 by the RHUM-RUM experiment’s broadband OBS near La Reunion Island, strategically placed at depths ranging from 3 to 5 km, predominantly over the central and southwest Indian Ridge.

Subsequently, we performed depth-velocity inversion of the compliance function using the Metropolis-Hastings algorithm and determined the oceanic crustal shear velocity structure up to a depth of 8 km.

This inversion process verified the compliance function’s stability and reliability throughout the observation period. Additionally, we developed specialized software, ’Compy’ designed to automate the processing steps required for this study, thereby enhancing efficiency and accuracy in seafloor compliance analysis. This research contributes significantly to our understanding of subsurface structures in marine environments, particularly in regions with limited data availability.