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There are two types of seismic noise: random noise and coherent noise. In a multichannel seismic dataset, random noise does not correlate either with the neighboring channels (i.e., no spatial correlation) or along the same channel (i.e., no temporal correlation).
Power spectral density (PSD) is a signals distribution of power at different frequencies. While a time-domain analysis watches how a signal changes over time, a frequency-domain analysis like PSD examines how much of the signals power is present at different frequencies.
RMS is the Root Mean Square, it represent the mean value of the input signal. PSD is the measurement of the responses that shows me at which frequencies most of the energy is concentrated. The area below a curve is the integration of that function.
Therefore, while the power spectrum calculates the area under the signal plot using the discrete Fourier Transform, the power spectrum density assigns units of power to each unit of frequency and thus, enhances periodicities.
A Power Spectral Density (PSD) is the measure of signals power content versus frequency. A PSD is typically used to characterize broadband random signals.
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Power spectral density (PSD) estimates are widely used in seismological studies to characterize background noise conditions, assess instrument performance, and study quasi‐stationary signals that are difficult to observe in the time domain.
The amplitude of seismic noise vibrations is typically in the order of 0.1 to 10 m/s. High and low background noise models as a function of frequency have been evaluated globally.
It is now established that the primary microseism, the secondary microseisms, and the hum are the three main components of seismic noise in the frequency band from about 0.003 Hz to 1.0 Hz.

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