4.7 Article

Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China

期刊

REMOTE SENSING
卷 13, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/rs13122421

关键词

airgun; ambient noise; seismic interferometry

资金

  1. National Key R&D Program of China [2018YFC1503400]
  2. China Earthquake Science Experiment Project, CEA [2018CSES0102, 2019CSES0107]
  3. HKSAR Research Grant Council GRF Grant [14305617]
  4. National Natural Scientific Foundation of China [41790462]
  5. Chen Yong Academician Workstation of Yunnan Province in China [2014IC007]
  6. CUHK Direct Grant from Faculty of Science

向作者/读者索取更多资源

The study compares seasonal subsurface structural variations derived from airgun signals and ambient noise data, finding that airgun signals are influenced by reservoir water level fluctuations and are correlated with dominant frequency and travel time changes; ambient noise cross-correlation data shows seismic travel time changes corresponding to seasonal precipitation and evaporation effects.
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 delta t/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.

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