Attenuation of coherent noise, typically weather generated noise and more specifically swell noise, is a major concern in seismic. Such noise, usually characterized by its low-frequency content and high amplitudes, is a common problem in seismic acquisition and, in particular, for marine data. We propose a multiple-input adaptive noise canceller as a solution to attenuate nonstationary coherent noise. This filter uses multiple noise sequences to estimate the noise contained in each trace. This noise estimate is then subtracted to obtain an estimate of the trace whose coherent noise has been attenuated. For the implementation of the adaptive filter, we use a variable step-size normalized least mean squares algorithm, as it is known for its simplicity and robustness. In addition, we demonstrate that variable step-size is necessary for this filter to adapt to the changing statistics of the seismic data. This method is tested on real marine seismic data and compared to a time-frequency median filter and a second-order high-pass Butterworth filter. We demonstrate that the multiple-input adaptive noise canceller is a powerful and efficient filter to attenuate swell noise while preserving the seismic reflections. Depending on the noise configuration, it can be used either by itself or in combination with a time-frequency median filter to obtain the best results.
Adaptive Processing for EM Telemetry Signal Recovery: Field Data from Sichuan Province
