Innovative Seismic Data Processing Approach to Improve Signal to Noise Ratio

Abstract

Abstract It is a common experience that undesired noise is invariably recorded during seismic data acquisition. The real signal is masked by the noise that may be coherent or random in nature. Coherent noise is generally identifiable by their apparent velocities. The aim of seismic data processing is to identify the noise, attenuate it and improve signal to noise ratio. In this paper, our aim is to remove coherent noise in shot domain before any subsequent data processing is taken up. Although f-k fan filters are commonly used to remove coherent noise by defining fan-like region in f-k spectrum but these are not applied on NMO corrected shot gathers. In our method, NMO correction is applied on shot gathers using reasonable velocities in such a way that primaries are either perfectly corrected or over-corrected and coherent noise remains under-corrected. Since events having different dips in t-x domain occupy separate zones in f-k spectrum, NMO corrected shot gathers are f-k filtered to remove under-corrected events that represent the coherent noise. Data thus f-k filtered is passed through inverse NMO process to remove any changes made to the input shot records during application of NMO correction. Subsequent processing of data is carried out as usual. Significant improvements are seen in data processed with this technique. The salient features of this technique are two folds. The first is that the NMO correction before f-k filtering widens the separation between real signal and the noise and the second is that the foldage in shot domain remains double of that in CDP domain thus no spatial aliasing takes place.