AMBIENT SEISMIC NOISE FOOTPRINTS AND SPECTRA IN THE MIDDLE BENUE TROUGH, NIGERIA
Journal: Earth Science Malaysia (ESMY)
Author: Clifford N. C. Mbachi, Etim D. Uko, Chibuogwu L. Eze, Iyeneomie Tamunobereton -Ari, Dorathy B. Umoetok And Allu A. Umbugdau
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
Ambient noise was analysed from a two-dimensional (2D) seismic data acquired in the Middle Benue Trough, Nigeria for the purpose of characterizing the ambient seismic noise. Sercel 428XL recording instrument was deployed on 3 traverse lines where dynamite explosive sources and geophone detectors were used. The acquired data was processed using frequency wavenumber (FK) and wild amplitude attenuation (WAA) algorithms. The dominant amplitude of the primary reflection ranges between -20dB and -10dB, while those of the ambient seismic noise varies between -42dB and -3dB. The primary reflections have dominant frequency varying from 6Hz to 75Hz while that of ambient seismic noise varies between 4Hz and 70Hz. Analysis of the noise shows two distinct ground roll modes with velocities between 400 ms-1 and 810 ms-1 both of which are dispersive with wavelength (λ) of 61.5m and peak frequency at 6.5Hz. Analysis of passive noise records acquired showed that ambient seismic (background) noise level excluding source-generated noise average of 91.56% are below 25µV, which is the tolerance noise level limit. The combination of frequency wavenumber FK and WAA filters effectively attenuated the surface waves especially ground rolls and other high amplitude noise making the primary reflection very visible and better enhanced. The filtered amplitude values estimated from signal-to-noise (SNR) analysis using cross correlation (XC) method are much higher than the values of the unfiltered amplitudes indicating that SNR are highest when noises are attenuated from the data than when noise algorithm is not applied to the data. The attributes of these seismic noises will provide further information and solution for their suppression during seismic data acquisition and processing.