Abstract
An airgun source in a water reservoir has been developed in the past decade as a green active source that had been proven effective to derive short-term subsurface structural changes. However, seasonal water level fluctuation in the reservoir affects the airgun signal, and thus whether the airgun signals can be used to derive robust seasonal variation in subsurface structure remains unclear. We use the airgun data observed in the Binchuan basin to estimate the seasonal variation of seismic travel time and compare the results with those derived from ambient noise data in the same frequency band. Our main observation is that seasonal change δt/t from airgun is negatively correlated to the variation of dominant frequency and water table fluctuation in the reservoir. One possible explanation is that water table fluctuation in the reservoir affects the dominant frequency of the airgun signal and causes significant phase shift. We also compute the travel time changes in P-wave from the empirical Green’s function after deconvolving the waveforms from a reference station that is 50 m from the airgun source. The dominant frequency after deconvolution still shows seasonal variation and correlates inversely to the travel time changes, suggesting that deconvolution cannot completely eliminate the source effect on travel time changes. We also use ambient noise cross-correlation to retrieve coda waves and then derive travel time changes in monthly stacked cross-correlations relative to a yearly average cross-correlation. We observe that seismic travel time increases to its local maximum in the end of August. The travel time changes lag behind the precipitation for about one month. We apply a poroelastic physical model to explain seismic travel time changes and find that a combined effect from precipitation and evaporation might induce the seasonal changes as shown in the ambient noise data. However, the pattern of travel time changes from the airgun differs from that from ambient noise, reflecting the strong effects of airgun source property changes. Therefore, we should be cautious to derive long-term subsurface structural variation from the airgun source and put more attention on stabilizing the dominant frequency of each excitation in the future experiments.
Highlights
Extensive field observations and lab experiments [1,2,3,4,5] have suggested that slowly evolving, low-amplitudes phases usually appear before the onset of natural hazards such as earthquakes, landslides, and volcanic eruptions
We follow the method of Moving-Window Cross-Spectral (MWCS) [30,57] to compute the phase shift between stacked reference and current airgun signals
A critical point in the MWCS analysis is the selection of the length of the moving
Summary
Extensive field observations and lab experiments [1,2,3,4,5] have suggested that slowly evolving, low-amplitudes phases usually appear before the onset of natural hazards such as earthquakes, landslides, and volcanic eruptions. Seismic velocity changes have been estimated through measuring travel time or phase difference from active sources including explosion [21,22,23,24,25], electronic hammer [26], airguns [18,27,28], repeating earthquakes [29,30,31,32,33,34], and dephasing of ambient noise crosscorrelations (CCs) [6,35]. Since 2011, a permanent seismic source [36,37,38] has been deployed in a water reservoir called Dayindian in Binchuan, Yunnan, China, to image velocity structure [39,40] and monitor seismic velocity changes [8,41,42,43,44] It has been in routine operation since September. We use ambient noise in the same frequency range to obtain seasonal changes in seismic velocity for coda waves and compare them with velocity changes for body waves
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