Abstract

In the seismic industry, the ground roll has been inherently regarded as strong coherent noise to be filtered out as soon as possible. Ground roll is one of the prominent coherent noises recorded in land seismic surveys and is characterized by relatively low frequencies, high amplitudes and low apparent velocity as compared to the seismic reflection. Ground roll is mainly composed of Rayleigh waves which constitutes a large part of the recorded energy posing a challenge for its faithful removal during the seismic data processing without affecting the signal. In conventional seismic data acquisition techniques, recorded data are coarsely sampled due to large group intervals and surface waves are often aliased which further makes the ground role more challenging & difficult to remove during data processing. A key challenge with onshore seismic data is accurately compensating for the extreme horizontal and vertical velocity variations and the complex surface wave noise contamination that results from the highly heterogeneous near-surface geology. In this paper instead of treating surface waves as a noise to only be removed in signal processing, we extracted valuable information from them. In a geophysical advancement environment, we can now model and subtract ground roll from the recorded signal and also acquire a greater understanding of the near-surface velocities. Surfacewave analysis modelling and inversion is finding growing applications in the oil & gas exploration industry. We applied surface-wave analysis modelling and inversion method (SWAMI) technique to remove the aliased ground roll noise and obtained near-surface model by using the dispersion characteristics of Rayleigh wave. In this paper we discuss a workflow and methodology for the analysis, modelling, inversion, and attenuation of surface waves with 3D land data, showing examples from a land 3D seismic survey in Kumchai, thrust-belt area of Assam-Arakan