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

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 si...

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Main Authors: Chunyu Liu, Hongfeng Yang, Baoshan Wang, Jun Yang
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/12/2421
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spelling doaj-4fe570afcb7640a293dc6692a4f2d99d2021-07-01T00:45:46ZengMDPI AGRemote Sensing2072-42922021-06-01132421242110.3390/rs13122421Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, ChinaChunyu Liu0Hongfeng Yang1Baoshan Wang2Jun Yang3Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518000, ChinaShenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen 518000, ChinaSchool of Earth and Space Sciences, University of Science and Technology of China, Hefei 230026, ChinaDali Center, China Seismic Experimental Site, China Earthquake Administration, Dali 671000, ChinaAn 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>δ</mi><mi>t</mi><mo>/</mo><mi>t</mi></mrow></semantics></math></inline-formula> 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.https://www.mdpi.com/2072-4292/13/12/2421airgunambient noiseseismic interferometry
collection DOAJ
language English
format Article
sources DOAJ
author Chunyu Liu
Hongfeng Yang
Baoshan Wang
Jun Yang
spellingShingle Chunyu Liu
Hongfeng Yang
Baoshan Wang
Jun Yang
Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China
Remote Sensing
airgun
ambient noise
seismic interferometry
author_facet Chunyu Liu
Hongfeng Yang
Baoshan Wang
Jun Yang
author_sort Chunyu Liu
title Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China
title_short Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China
title_full Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China
title_fullStr Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China
title_full_unstemmed Impacts of Reservoir Water Level Fluctuation on Measuring Seasonal Seismic Travel Time Changes in the Binchuan Basin, Yunnan, China
title_sort impacts of reservoir water level fluctuation on measuring seasonal seismic travel time changes in the binchuan basin, yunnan, china
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-06-01
description 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>δ</mi><mi>t</mi><mo>/</mo><mi>t</mi></mrow></semantics></math></inline-formula> 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.
topic airgun
ambient noise
seismic interferometry
url https://www.mdpi.com/2072-4292/13/12/2421
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AT baoshanwang impactsofreservoirwaterlevelfluctuationonmeasuringseasonalseismictraveltimechangesinthebinchuanbasinyunnanchina
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