Imaging the Crustal structure of Oman and the United Arab Emirates using  Seismic Noise Autocorrelation functions

The United Arab Emirates (UAE) and Oman are primarily characterized by an orogenic belt housing the well-known obduted Semail ophiolite and a number of foreland basins. The thickness of the sedimentary basins in the region remains elusive and challenging to determine, given the substantial sedimentary cover that potentially exceeds 10 km. This thickness limits traditional techniques, hindering their ability to reach greater depths. Constraining the depth of the Semail ophiolite is an additional challenge because the high velocities of oceanic lithospheric units prevent geophysical techniques from imagining the base of the ophiolite with clarity. Seismic noise autocorrelation proves to be an effective method for imaging subsurface structures owing to its independence from active seismic sources and its potential to reach greater depths. We used continuous seismic noise records from regional networks. Data were collected from 110 stations deployed across the mountain belt and adjacent sedimentary basins. Each station consisted of an average of one year of continuous records of passive seismic data. Data processing to obtain autocorrelation functions includes bandpass filtering and noise reduction to isolate the appropriate frequency range that is essential for imaging subsurface structures. Autocorrelation was performed on hourly files, and the phase-weighted stacking technique was applied to extract coherent signals from background seismic noise. We subsequently removed the common source function, which provides a final autocorrelation function over the two-way travel time. A 3-D velocity model of the region based on ambient noise tomography was used to convert the autocorrelations to a depth reflectivity profile beneath each station. The results were integrated with existing geophysical, geological, and well data and interpreted in terms of sedimentary basin and ophiolite thickness.