Seismic Background Noise Analysis from the Seismic Station Located at the University of Abuja, Northcentral Nigeria

Abstract

In October 2018, the Federal Government of Nigeria established several seismic stations in different places in the country. Three of these stations are located in the Abuja region (the Federal Capital Territory, or FCT) and are managed by the Nigerian Geological Survey Agency. Over the past few years, several low to intermediate earthquakes have been recorded within and around the Abuja region. These occurrences have provided valuable opportunities to study seismic earth noise using the dataset collected from the VolksMeter II seismometer installed at the University of Abuja. The data was processed using the Win QUAKE software to analyze the seismic background noise by identifying its sources. This analysis aimed to examine the seasonal and/or daily noise levels and check the seismometer’s stability through spectral display. The physical examination and/or quantitative observation of the spectrum revealed that there was a distinct area with densely high ranges between 0.08 and 10 s, corresponding to a frequency range of 0.1Hz–12.53Hz. This assessment involved a full Fast Fourier Transform (FFT) calculation. The spectral analysis indicated the presence of noise burbles, primarily attributable to instrumental noise. These noise burbles were prominent in the east-west direction during the months of March, April, May, and June 2019, with frequencies of 0.03Hz, 0.04Hz, 0.03Hz, and 0.03Hz, respectively. A similar pattern was observed in the north-south direction, with noise peaks of 0.07Hz in the months of January, April, and July 2019. The findings from this study of seismic noise amplitude demonstrate a clear correlation with the global seismic noise models. The sources contributing to the station’s noise levels encompass factors such as wind, geological influences, instrumental noise, and human activities including machinery and airport operations as well as vehicular traffic. These observations highlight the potential of using background seismic noise to quantify tremors and monitor their spatial variations, a task that remains difficult with traditional approaches.