Seismic Surface Wave Inversion

F. Ahmed¹ and A.M. Almarzoug¹

¹Saudi Aramco

Abstract

In conventional seismic processing workflows, surface waves (ground roll) are usually treated as unwanted coherent noise and steps are then taken to remove them from the seismic data during the acquisition phase using receiver arrays. Also, during the early data processing stage, ground roll is further filtered out. Recently, there has been a growing interest in using surface waves for characterizing the near surface velocity model. Surface waves propagate in the shallow subsurface and can be used to derive shear wave velocities of the near surface. This is important for the Arabian Peninsula since the near surface geology is very complex. Surface wave analysis requires three steps: 1) acquisition of data that is un-aliased and with sufficient low frequency content 2) processing to generate dispersion curves and 3) inversion of the dispersion curves. In our study, we have successfully used surface waves extracted from a seismic dataset acquired using single sensor geophones. The use of single sensor geophones, along with dense surface coverage, allowed us to acquire data which is un-aliased as well as having good low frequency content. The dataset was used to generate multimodal dispersion curves with sufficient coherence for picking. The dispersion curves were subsequently inverted to derive shear wave velocities characterizing our complex near surface. Using synthetic data, various inversion techniques such as genetic algorithm and model-based were tested. We conclude that the model-based algorithm is more suited for cases where there is velocity inversion in the geology, which is prevalent in our study area.