Attenuation of Non-Compressional Energy in Ocean Bottom Node Data

Attenuation of non-compressional energy, such as shear body waves and scattered surface waves, is a critical step in the processing of ocean bottom node seismic data, because this unwanted energy interferes with the desired compressional signals. In this paper, we first review conventional methods for attenuating non-compressional energy in vertical geophone recordings, including cooperative denoising procedures and adaptive subtraction techniques. We then introduce the use of rotational measurements from a new type of ocean bottom node for the attenuation of non-compressional energy. Our results demonstrate that rotational data improve the attenuation of the non-compressional energy, particularly for flat events at small offsets where conventional methods struggle. Finally, we explore the potential of machine learning to reduce the computational cost and human effort involved in the denoising workflow. Overall, the combination of conventional denoise techniques and rotational data delivers robust results. The introduction of machine learning provides a way forward that leverages the strengths of existing methods and reduces the cost of seismic data processing.