Hydrostratigraphy characterization of the Floridan aquifer system using ambient seismic noise

James, S. R.; Screaton, E.; Russo, R. M.; Panning, M. P.; Bremner, P. M.; Stanciu, A. C.; Torpey, M. E.; Hongsresawat, S.; Farrell, Matthew E.

doi:10.1093/gji/ggx064

Cited by 7 publications

(16 citation statements)

References 26 publications

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“…In other words, the highest frequencies will be most sensitive to the shallow active layer. High frequencies (>1 Hz) have been used successfully in previous near-surface applications by using waves generated from natural and anthropogenic sources [Halliday et al, 2008;Picozzi et al, 2009;James et al, 2017]. Frequencies >30 Hz were poorly recovered in this study, with signal-to-noise ratios (SNRs) close to one ( Figure S2).…”

Section: Methodsmentioning

confidence: 80%

Improved moving window cross‐spectral analysis for resolving large temporal seismic velocity changes in permafrost

James

Knox

Abbott

et al. 2017

Geophysical Research Letters

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Cross correlations of seismic noise can potentially record large changes in subsurface velocity due to permafrost dynamics and be valuable for long‐term Arctic monitoring. We applied seismic interferometry, using moving window cross‐spectral analysis (MWCS), to 2 years of ambient noise data recorded in central Alaska to investigate whether seismic noise could be used to quantify relative velocity changes due to seasonal active‐layer dynamics. The large velocity changes (>75%) between frozen and thawed soil caused prevalent cycle‐skipping which made the method unusable in this setting. We developed an improved MWCS procedure which uses a moving reference to measure daily velocity variations that are then accumulated to recover the full seasonal change. This approach reduced cycle‐skipping and recovered a seasonal trend that corresponded well with the timing of active‐layer freeze and thaw. This improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise.

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Section: Methodsmentioning

confidence: 80%

Improved moving window cross‐spectral analysis for resolving large temporal seismic velocity changes in permafrost

James

Knox

Abbott

et al. 2017

Geophysical Research Letters

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“…While the focus of our study was the specific utilization of installed telecom fiber probed by DAS for seismic sensing, our static imaging and monitoring results are consistent with and rely on broad advances in the field of ambient noise seismology applied to the near-surface. Beyond the foundational studies cited previously 38 , a variety of recent projects have utilized ambient noise approaches to probe hydrologic cycles 7,59–61 and aquifer structure 62 although typically using a sparse network of stations. Such studies have typically relied on the microseisms band as a noise source (0.1–1 Hz) and hence are observing averaged velocity perturbations over significant vertical extent, often to km depths.…”

Section: Discussionmentioning

confidence: 99%

Distributed Acoustic Sensing Using Dark Fiber for Near-Surface Characterization and Broadband Seismic Event Detection

Ajo‐Franklin

Dou

Lindsey

et al. 2019

Sci Rep

393

199

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We present one of the first case studies demonstrating the use of distributed acoustic sensing deployed on regional unlit fiber-optic telecommunication infrastructure (dark fiber) for broadband seismic monitoring of both near-surface soil properties and earthquake seismology. We recorded 7 months of passive seismic data on a 27 km section of dark fiber stretching from West Sacramento, CA to Woodland, CA, densely sampled at 2 m spacing. This dataset was processed to extract surface wave velocity information using ambient noise interferometry techniques; the resulting VS profiles were used to map both shallow structural profiles and groundwater depth, thus demonstrating that basin-scale variations in hydrological state could be resolved using this technique. The same array was utilized for detection of regional and teleseismic earthquakes and evaluated for long period response using records from the M8.1 Chiapas, Mexico 2017, Sep 8th event. The combination of these two sets of observations conclusively demonstrates that regionally extensive fiber-optic networks can effectively be utilized for a host of geoscience observation tasks at a combination of scale and resolution previously inaccessible.

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“…There have been fewer attempts to measure velocity profiles from EGFs using short ( T < 1 s) and intermediate (1 s < T < 3 s) wave periods to identify shallow crustal and sedimentary structures (Chávez‐García & Luzón, 2005; James et al., 2017; Pilz et al., 2012; Savage et al., 2013). In the use of short‐period waves, it is important to establish a reliable criterion in selecting the randomized noise because reconstruction of velocity profiles that relies on the scattered wave energy at depths may incorporate biases from uneven distribution of wave sources (Poli et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

Processing Ambient Noise Data Using Phase Cross‐Correlation and Application Toward Understanding Spatiotemporal Environmental Effects

et al. 2023

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Hydrostratigraphy characterization of the Floridan aquifer system using ambient seismic noise

Cited by 7 publications

References 26 publications

Improved moving window cross‐spectral analysis for resolving large temporal seismic velocity changes in permafrost

Improved moving window cross‐spectral analysis for resolving large temporal seismic velocity changes in permafrost

Distributed Acoustic Sensing Using Dark Fiber for Near-Surface Characterization and Broadband Seismic Event Detection

Processing Ambient Noise Data Using Phase Cross‐Correlation and Application Toward Understanding Spatiotemporal Environmental Effects

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