How Processing Methodologies Can Distort and Bias Power Spectral Density Estimates of Seismic Background Noise

Abstract

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. However, these studies often utilize different processing techniques, each of which can inherently bias the resulting PSD estimates. The level of smoothing, the size of the data window, and the method used for actually estimating the spectral content can all have strong influences on PSD estimates and background noise statistics. We show that although smoothing reduces the variance of the PSD estimate, the corresponding decrease in frequency resolution can eliminate or distort features of interest. For instance, popular software packages such as Incorporated Research Institutions for Seismology Modular Utility for STAatistical kNowledge Gathering (MUSTANG) and earlier versions of Portable Array Seismic Studies of the Continental Lithosphere Quick Look eXtended (PQLX), which were designed for data quality control and are effective in that regard, are less suitable for scientific studies that require accurate resolution of spectral peaks, even for peaks as broad as the primary (∼14 s period) and secondary (∼7 s period) microseisms. We also demonstrate how the 1 and 3 hr data windows used in MUSTANG and PQLX can be strongly influenced by energy generated from moderate-size (M>∼4.8) teleseismic earthquakes. The ubiquity of these events is likely skewing median ambient-noise estimates by as much as 5 dB upward, for periods of 10–50 s at high-quality broadband stations. Finally, we illustrate that many of the discrepancies between global low-noise models are attributable to processing methodologies rather than fundamental differences in the underlying seismic data.

Unprecedented quiescence in resource development area allows detection of long-lived latent seismicity

“…The Montney Play, which is Lower-Middle Triassic in age, is formed of extensive fine-grained siliciclastic units (inter-bedded sand, silt and mudstones) and stretches from west-central Alberta to north-east British Columbia (Eaton and Schultz, 2018;Dixon, 2000;Armitage, 1962). Over 5600 multistage horizontal hydraulically fractured wells had been completed within the Montney by December 2018 (Nieto et al, 2018).…”

Unprecedented quiescence in resource development area allows detection of long-lived latent seismicity

“…PPSD is one of the most common methods used to characterize ambient seismic noise. However, the level of smoothing, the size of the data window used in analysis and the methodology itself may all influence the PPSD calculation and distort features of interest (Anthony et al, 2020). Smoothing is primarily undertaken in order to reduce the uncertainty associated with the PPSD estimates, and means that short spikes in noise (e.g.…”

“…1 and 4, green vs. grey lines). Although we use a period smoothing of 0.025 octaves, this is likely to provide adequate spectral resolution of spectral peaks, as shown by Anthony et al (2020) and therefore impacts our results minimally.…”

“…However, the removal of seismicity from datasets is generally accepted as not necessary since they are low-probability occurrences within generally high-probability ambient seismic noise (McNamara and Buland, 2004). Only teleseismic earthquakes appear to have any real affect upon PPSD calculations (Anthony et al, 2020). A number of teleseismic events have been detected in the KSMMA during the period of quiescence analysis (e.g.…”

Performance Assessment of Geophysical Instrumentation Through the Automated Analysis of Power Spectral Density Estimates

“…Because variations in the PSD can possibly be attributed to local underlying geophysical processes (Burtin et al., 2008; García et al., 2006) global models are often insufficient, and every instrument and site needs to be verified independently. Furthermore, the global models themselves are sensitive to uncertainties introduced by the PSD processing and smoothing that may exceed the uncertainty of the data (Anthony et al., 2020). Therefore, it is recommended that a combination of multiple strategies is used to automatically monitor the performance of geophysical instrumentation when using PSD estimates.…”