Removal of scattered guided waves from seismic data

Abstract

Abstract Near-surface scattered waves form a major source of coherent noise in seismic land data. Most current methods for removing these waves do not attenuate them adequately if they come from other than the inline direction. We present a wave-theory-based method for removing (scattered) guided waves by a prediction-and-removal algorithm. We assume that the near surface consists of a laterally varying medium, in which heterogeneities are embedded that act as scatterers. We first estimate the dispersive and laterally varying phase slowness field by applying a phase-based tomography algorithm on the direct groundroll wave. Subsequently, the near-surface heterogeneities are imaged using a least-squares criterium. Finally, the scattered guided waves are modeled and subtracted adaptively from the seismic data. We have applied this method to seismic land data and found that near-surface scattering effects are attenuated.