An official website of the United States government
Abstract This article documents a comprehensive subsurface imaging experiment using seismic waves in a well-studied outdoor laboratory at Newberry, Florida, which is known for significant spatial variability, karstic voids, and underground anomalies. The experiment used approximately two kilometers of distributed acoustic sensing (DAS) fiber-optic cable, forming a dense 2D array of 1920 horizontal-component channels, and a 2D array of 144 SmartSolo three-component nodal seismometers, to sense active-source and passive-wavefield seismic waves. The active-source data were generated using a powerful, triaxial vibroseis shaker truck (T-Rex) and impact sources (accelerated weight drop and an eight-pound sledgehammer) that were simultaneously recorded by both the DAS and nodal seismometers. The vibroseis truck was used to excite the ground in three directions (two horizontal and one vertical) at 260 locations inside and outside the instrumented array, whereas the impact sources were used at 268 locations within the instrumented array. The passive-wavefield data recorded using the nodal seismometers comprised 48 hr of ambient noise collected over a period of four days in four 12-hour time blocks, whereas the passive wavefield data collected using DAS consisted of four hours of ambient noise recordings. This article aims to provide a comprehensive overview of the testing site, experiment layout, the DAS and nodal seismometer acquisition parameters, and implemented raw data processing steps. Although potential use cases, such as surface-wave testing, full-waveform inversion, and ambient noise tomography, are discussed relative to example data, the focus of this article is on documenting this unique data set and presenting its initial data quality rather than on generating subsurface imaging results. The raw and processed data, along with detailed documentation of the experiment and Python tools to aid in visualizing the DAS data set, have been made publicly available.
more »
« less
Active-source and Passive-wavefield DAS and Nodal Station Measurements at the Newberry Florida Site
This is a comprehensive subsurface imaging experiment in Newberry, Florida using stress waves. The site is spatially variable and contains karstic surface and underground voids and anomalies. The sensing technologies used comprised a dense 2D array of 1920 DAS channels and a 12 x 12 grid of 144 SmartSolo 3C nodal stations, which covered an area of 155 m x 75 m and were used to record both active-source and passive-wavefield data. The active-source data was generated by a variety of vibrational and impact sources, namely: a powerful three-dimensional vibroseis shaker truck, a 40-kg propelled energy generator (PEG-40kg), and an 8-lb sledgehammer. The vibroseis shaker truck was used to vibrate the ground in the three directions at 260 locations inside and outside the instrumented area, while the impact sources were used at 268 locations inside the instrumented area. In addition to active source data, four hours of ambient noise were recorded using the DAS, while the nodal stations recorded 48 hours of ambient noise in four 12-hour increments over a period of four days. The waveforms obtained from the 1920 DAS channels for every active-source shot or passive-wavefield time block were extracted, processed, and stored in H5 files. These files can be easily visualized using a Python script incorporated with the open-access dataset. Additionally, the three-component data gathered from each SmartSolo nodal station were consolidated into a single miniSEED file, and the data from all 144 nodal stations obtained during each active-source shot or passive-wavefield time block were extracted and saved into a separate folder. We anticipate that this dataset will be a valuable resource for researchers developing techniques for void and anomaly detection using noninvasive, stress wave-based subsurface imaging techniques.
more »
« less
- Award ID(s):
- 2120155
- PAR ID:
- 10463233
- Publisher / Repository:
- Designsafe-CI
- Date Published:
- Subject(s) / Keyword(s):
- DAS SmartSolo Nodal Stations Vibroseis Shaker Truck T-Rex FWI Imaging Surface Wave Inversion Ambient Noise
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
There is a growing need to characterize the engineering material properties of the shallow subsurface in three dimensions for advanced engineering analyses. However, imaging the near-surface in three dimensions at spatial resolutions required for such purposes remains in its infancy and requires further study before it can be adopted into practice. To enable and accelerate research in this area, we present a large subsurface imaging data set acquired using a dense network of three-component (3C) nodal stations acquired in 2019 at the Garner Valley Downhole Array (GVDA) site. Acquisition of this data set involved the deployment of 196 stations positioned on a 14 × 14 grid with a 5 m spacing. The array was used to acquire active-source data generated by a vibroseis truck and an instrumented sledgehammer, and passive-wavefield data containing ambient noise. The active-source acquisition included 66 vibroseis and 209 instrumented sledgehammer source locations. Multiple source impacts were recorded at each source location to enable stacking of the recorded signals. The active-source recordings are provided in terms of both raw, uncorrected units of counts and corrected engineering units of meters per second. For each source impact, the force output from the vibroseis or instrumented sledgehammer was recorded and is provided in both raw counts and engineering units of kilonewtons. The passive-wavefield data include 28 h of ambient noise recorded over two nighttime deployments. The data set is shown to be useful for active-source and passive-wavefield three-dimensional imaging and other subsurface characterization techniques, which include horizontal-to-vertical spectral ratios (HVSRs), multichannel analysis of surface waves (MASW), and microtremor array measurements (MAM).more » « less
-
Active-source data acquisition included 66 vibroseis and 209 instrumented sledge hammer source locations. Multiple source impacts were recorded at each source location to enable stacking of the recorded signal. The source impacts at each source location have been aligned using cross-correlation, but to provide the most flexibility are provided unstacked (i.e., the signals from each source impact are provided separately). The active-source recordings are provided in terms of both raw, uncorrected units of counts and corrected, engineering units of meters per second. For each source impact, the force output from the vibroseis or instrumented sledge hammer was recorded and is provided in both raw counts and engineering units of kilonewtons. The passive-wavefield data includes 28 hours of ambient noise recorded over two night-time deployments. The passive-wavefield data is provided in raw counts, however, the instrument response files are provided should instrument correction be required in the future. The dataset can be used for active-source and passive-wavefield three-dimensional imaging, as well as other subsurface characterization techniques which include: horizontal-to-vertical spectral ratios, multichannel analysis of surface waves, and microtremor array measurements.more » « less
-
SUMMARY In this study, I demonstrate that distributed acoustic sensing (DAS) raw strain rate data can directly be used to estimate spectral source parameters through an Empirical Green's Function (EGF) deconvolution analysis. Previously, DAS had been widely used in passive seismology to image the subsurface and analyze ground motion variations by converting strain or strain rate to particle velocity or acceleration prior to analysis. In this study, spectral analysis is applied to the PoroTomo joint DAS and seismic Nodal array in the Brady Hot Springs geothermal field to obtain source parameters for two M4 earthquakes via EGF analysis, where nearly collocated smaller events are used as an EGF to remove path and site effects. The EGF workflow is applied to raw DAS strain rate data without conversion to particle velocities and raw Nodal seismic data. The DAS and Nodal results are very consistent with similar features of spectral ratios, corner frequencies and moment ratios for the same event pairs. The uncertainty due to stacked spectral measurement is much lower on the DAS array, suggesting better stability of spectral shape measurement, possibly due to the much denser spatial sampling. The uncertainty due to model fitting is similar between DAS and Nodal arrays with slightly lower uncertainty on the DAS array. These observations demonstrate potential for directly using the strain rate measurements from DAS arrays for earthquake source characterizations.more » « less
-
SUMMARY Distributed acoustic sensing (DAS) networks promise to revolutionize observational seismology by providing cost-effective, highly dense spatial sampling of the seismic wavefield, especially by utilizing pre-deployed telecomm fibre in urban settings for which dense seismic network deployments are difficult to construct. However, each DAS channel is sensitive only to one projection of the horizontal strain tensor and therefore gives an incomplete picture of the horizontal seismic wavefield, limiting our ability to make a holistic analysis of instrument response. This analysis has therefore been largely restricted to pointwise comparisons where a fortuitious coincidence of reference three-component seismometers and colocated DAS cable allows. We evaluate DAS instrument response by comparing DAS measurements from the PoroTomo experiment with strain-rate wavefield reconstructed from the nodal seismic array deployed in the same experiment, allowing us to treat the entire DAS array in a systematic fashion irrespective of cable geometry relative to the location of nodes. We found that, while the phase differences are in general small, the amplitude differences between predicted and observed DAS strain rates average a factor of 2 across the array and correlate with near-surface geology, suggesting that careful assessment of DAS deployments is essential for applications that require reliable assessments of amplitude. We further discuss strategies for empirical gain corrections and optimal placement of point sensor deployments to generate the best combined sensitivity with an already deployed DAS cable, from a wavefield reconstruction perspective.more » « less
