Near-Surface Data-Driven Methods for Surface Wave and Multiple Removal, Onshore Kenya

Land surface seismic data are usually strongly affected by the presence of surface waves (ground-roll), which can completely obscure the underlying primary reflection signal. It is therefore crucial to isolate the reflection signal for both imaging and amplitude analysis needs. Complex near-surface conditions complicate ground-roll attenuation and may introduce other sources of noise such as multiples. We present an application of interferometric ground-roll removal and 3D convolutional de-multiple methods on a seismic dataset acquired onshore North Kenya, where the shallow subsurface is characterized by strong heterogeneity, caused by the presence of a fast volcanic layer and structurally complex geology. Effective removal of the unwanted surface-wave and multiple energy was achieved with minimal impact on the amplitude character of the primary reflection signal.