De-noising distributed acoustic sensing data using an adaptive frequency–wavenumber filter

Summary Data recorded by distributed acoustic sensing (DAS) along an optical fibre sample the spatial and temporal properties of seismic wavefields at high density. Often leading to massive amount data when collected for monitoring many kilometre long cables. The spatially coherent signals from weak arrivals within are often obscured incoherent noise. We present a flexible computationally efficient filtering technique, which makes use dense sampling that can handle large data. presented adaptive frequency–wavenumber filter suppresses noise while amplifying wavefield. analyse response in time spectral domain, we demonstrate its performance on noisy set was vertical borehole observatory showing active passive phase arrivals. Lastly, performant open-source software implementation enabling real-time DAS sets.