scholarly journals Void Hunting

2021 ◽  
Author(s):  
John B. Paustian
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Temporal Variations ◽  
Ambient Noise Tomography ◽  
Active Dissolution ◽  
Near Surface ◽  
Karst Environment ◽  
Active Source ◽  
Seismic Methods ◽  
Spatio Temporal

Karst environments are characterized by voids, i.e. sinkholes and conduits of varying size that arise from the active dissolution of carbonate rock by acidic groundwater. These voids, whether air-, water-, or soil-filled, can be difficult to image using near-surface geophysical methods due to the limited investigation depths of most active-source methods. In addition, due to the significant effort it takes to collect active-source data, investigators are often unable to monitor spatio-temporal variations in the subsurface. The ability to detect, image, and monitor subsurface voids improves the understanding of processes that create and transform voids, a vitally important insight across a variety of scientifc disciplines and engineering applications, including hydrogeology, geotechnical engineering, planetary science and even issues of national security. Using a 54-element nodal array (1C and 3C sensors), I image the subsurface of the USF GeoPark with ambient noise surface wave tomography. I also use complementary active-source geophysical datasets (e.g. 2D ERT) collected at the GeoPark to constrain and/or validate the tomography results. I address two research questions with this study: (1) How do ambient seismic methods complement active-source near-surface methods? (2) Can ambient noise tomography resolve voids in the karst environment? In this thesis, I discuss my answers to these questions and present the current state of surface wave methods in the karst environment, including the feasibility for utilizing ambient noise methods to monitor spatio-temporal changes in sinkhole and conduit formation. In addition to the ability to use seismic methods for temporal monitoring, ambient noise provides lower frequencies than what are achievable with active-source seismic methods. Using frequencies from 5-28 Hz, ambient noise tomography is able to image deeper into the subsurface (up to 100 m at 5 Hz) than previous active-source seismic studies at the GeoPark field site. This study yields a more robust and simple method to image voids in covered karst environments and a long-term installation of ambient seismic nodes enables future investigations of spatio-temporal variations in void structures.

Near-surface Structure of Downtown Jinan, China: Application of Ambient Noise Tomography with a Dense Seismic Array

2019 ◽  
Vol 24 (4) ◽  
pp. 641-652
Author(s):  
Feng Liang ◽  
Zhihui Wang ◽  
Hailong Li ◽  
Kai Liu ◽  
Tao Wang
Keyword(s):  
Surface Wave ◽  
Human Activities ◽  
High Frequency ◽  
Urban Areas ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Shear Velocity ◽  
Ambient Noise Tomography ◽  
Surface Wave Dispersion ◽  
Near Surface

Urban geophysics ups the ante in the world of applied geophysics, which requires innovative thinking and seemingly off-the-wall approaches, if for no other reason than the settings. Ambient-noise-tomography (ANT) can play a pivotal role in yielding subsurfa2ce information in urban areas, which is capable of dealing with challenges related to these scenarios ( e.g., human activities and low signal-to-noise ratio). In this study, the ANT was conducted to investigate the near-surface shear-velocity structure in the surrounding area of the Baotu Spring Park in downtown Jinan, Shandong Province, China. Quiet clear Rayleigh waves have been obtained by the cross-correlation, which indicates that strong human activities, such as moving vehicles and municipal engineering constructions, can produce approximately isotropic distribution of noise sources for high-frequency signals. The direct surface-wave tomographic method with period-dependent ray-tracing was used to invert all surface-wave dispersion data in the period band 0.2-1.5 s simultaneously for 3D variations of shear-velocity (Vs) structure. Our results show a good correspondence to the geological features with thinner Quaternary sediments, the geological structural characteristic of the limestone surrounded by the igneous which has the highest velocity than that of the limestone in the study area, and several concealed faults of which specific location has been detected at depth. The results demonstrate that it is possible to successfully use ANT with high-frequency signal in an urban environment provided a detailed planning and execution is implemented.

Road sinkhole detection with 2D ambient noise tomography

Geophysics ◽  
2021 ◽  
pp. 1-45
Author(s):  
Yao Wang ◽  
Khiem T. Tran ◽  
David Horhota
Keyword(s):  
Ambient Noise ◽  
Cross Correlation ◽  
Traffic Noise ◽  
Experimental Result ◽  
Source Distribution ◽  
Ambient Noise Tomography ◽  
Source Power ◽  
Active Source ◽  
Seismic Methods ◽  
Source Excitation

Seismic methods are often used for detection of pre-collapsed sinkholes (voids) under roadway for remediation to minimize the risk to the safety of the traveling public. While the active-source seismic methods can provide accurate subsurface profiles, they require closing the traffic flow for hours during testing and potentially cause sinkhole collapse due to ground perturbation by source excitation. To address these issues, we present a new 2D ambient noise tomography (2D ANT) method for imaging voids under roadway. Instead of using the approximated Green’s function, whose required assumption of energy balance at both sides of each receiver pair is rarely satisfied, the cross-correlation function of traffic noise recordings is inverted directly to obtain velocity structures. To adopt the concepts of seismic interferometry and derive the model structural kernel, passing-by vehicles are assumed as moving sources along the receiver array. The source power-spectrum density is determined via the reverse-time imaging approach to approximate the source distribution. The 2D ANT method is first demonstrated on a realistic synthetic model with the accurate recovery of the model variable layers and a buried void. To demonstrate its effectiveness to the real-world problems, we successfully applied it to field data for assessment of a repaired sinkhole under the US441 highway, Florida, USA. The field experimental result shows that the method is capable of resolving the subsurface S-wave velocity ( VS) structure and detecting a low-velocity anomaly. The inverted VS profile from the 2D ANT generally agrees with that of 2D active-source full-waveform inversion, including the VS value and depth of the anomaly. To our best knowledge, this is the first study to directly invert the waveform cross-correlation of traffic noise recordings to extract material property at the engineering meter scale (<30 m depth).

scholarly journals Near-surface structure from ambient-noise tomography and horizontal-to-vertical spectral ratio beneath the Nankou-Sunhe fault

2020 ◽  
Vol 33 (5-6) ◽  
pp. 232-238
Author(s):  
Yuting Zhang ◽  
◽  
Hongyi Li ◽  
Yanzhen Li ◽  
Zhijie Wei ◽  
...  
Keyword(s):  
Surface Structure ◽  
Ambient Noise ◽  
Spectral Ratio ◽  
Ambient Noise Tomography ◽  
Near Surface

scholarly journals Determining seismic shear-velocity from ambient noise sources at regional and local scales

2021 ◽  
Author(s):  
◽  
Francesco Civilini
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Shear Velocity ◽  
Volcanic Field ◽  
Geothermal Field ◽  
Near Surface ◽  
Velocity Models ◽  
Geothermal Fields ◽  
Cross Correlations ◽  
Velocity Changes

<p>We present three projects that use different bandwidths of the ambient noise spectrum to solve geophysical problems. Specifically, we use signals within the noise field to determine surface and shear wave velocities, image the shallow and deep crust, and monitor time-dependent deformation resulting from geothermal fluid injection and extraction.  Harrat Al-Madinah, a Cenozoic bimodal alkaline volcanic field in west-central Saudi Arabia, is imaged using shear-velocities obtained from natural ambient seismic noise. To our knowledge, this project is the first analysis of Saudi Arabia structure using ambient noise methods. Surface wave arrivals are extracted from a year's worth of station-pair cross-correlations, which are approximations of the empirical Green's function of the interstation path. We determine group and phase velocity surface wave dispersion maps with a 0.1 decimal degree resolution and resolve a zone of slow surface wave velocity south-east of the city of Medina, which is spatially correlated with the most recent historical eruption (the 1256 CE Medina eruption). Dispersion curves are calculated at each grid-point of the surface-wave velocity maps and inverted to obtain measurements of shear-velocity with depth. The 1D velocity models are then used to produce average shear-velocity models for the volcanic field. A shear-velocity increase ranging from 0.5 to 1.0 km/s, suggesting a layer interface, is detected at approximately 20 km depth and compared to P-wave measurement from a previous refraction study. We compute cross-section profiles by interpolating the inversions into a pseudo-3D model and resolve a zone of slow shear-velocity below the 1256 CE eruption location. These areas are also spatially correlated with low values of Bouguer gravity. We hypothesize that the low shear-velocity and gravity measurements are caused by fluids and fractures created from prior volcanic eruptions.   We use the coda of cross-correlations extracted from ambient noise to determine shear-velocity changes at Rotokawa and Ngatamariki, two electricity producing geothermal fields located in the North Island of New Zealand. Stacks of cross correlations between stations prior to the onset of production are compared to cross correlations of moving stacks in time periods of well stimulation and the onset of electricity production using the Moving Window Cross Spectral technique. An increase between 0.05% to 0.1% of shear-velocity is detected at Rotokawa coinciding with an increase of injection. The shear-velocity subsequently decreases by approximately 0.1% when the rate of production surpasses the rate of injection. A similar amplitude shear-velocity increase is detected at Ngatamariki during the beginning of injection. After the initial increase, the shear-velocity at Ngatamariki fluctuates in response to differences in injection and production rates. A straight-ray pseudo-tomography analysis is conducted at the geothermal fields, which reveals that localized positive velocity changes are co-located with injection wells.  Lastly, we use ambient noise and active sources at the Ngatamariki geothermal field to determine the structure of the top 200 meters using the Refraction Microtremor technique. We deployed a linear 72-channel array of vertical geophones with ten meter spacing at two locations of the geothermal field and determine average 1D and 2D shear-velocity profiles. We were able to image depths between 57 to 93 meters for 2D profiles and up to 165 meters for 1D profiles. A shear-velocity anomaly was detected across one of the lines that coincided with the inferred location of a fault determined from nearby well logs. This suggests that the method can be used to cheaply and quickly constrain near-surface geology at geothermal fields, where ambient noise is abundant and typical reflection and refraction surveys require large inputs of energy and are hindered by attenuation and scattering in near-surface layers.</p>

Local dispersion curve estimation from seismic ambient noise using spatial gradients

2016 ◽  
Vol 4 (3) ◽  
pp. SJ17-SJ27 ◽  
Author(s):  
Pascal Edme ◽  
Shihao Yuan
Keyword(s):  
Ambient Noise ◽  
Dispersion Curves ◽  
Surface Wave Dispersion ◽  
Near Surface ◽  
Local Dispersion ◽  
Time Frequency ◽  
Seismic Ambient Noise ◽  
Spatial Gradients ◽  
Active Source ◽  
Analysis Scheme

A novel acquisition and processing technique is described to derive surface-wave dispersion curves from seismic ambient noise. We have determined that the use of spatial gradients of the wavefield provides new opportunities for high-resolution near-surface characterization with minimal field effort. In contrast to conventional active source data analysis that provides spatially smoothed results from large and dense arrays of receivers, our method provides local phase velocity information from ambient noise using only three closely spaced geophones. A time-frequency domain polarization-based analysis scheme is implemented to (1) detect the useful part of the data satisfying fundamental gradiometry assumptions, (2) estimate the noise source azimuthal distribution, and finally, (3) derive the desired local dispersion curves. The robustness and effectiveness of the developed method is demonstrated using the synthetic and real data, with a comparison to results from active source measurements.

Spurious signals attenuation using SVD-based Wiener filter for near-surface ambient noise surface wave imaging

2020 ◽  
Vol 183 ◽  
pp. 104220
Author(s):  
Chaoqiang Xi ◽  
Binbin Mi ◽  
Tianyu Dai ◽  
Ya Liu ◽  
Ling Ning
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Wiener Filter ◽  
Near Surface ◽  
Wave Imaging ◽  
Spurious Signals

scholarly journals Spatial Autocorrelation of Martian Surface Temperature and Its Spatio-Temporal Relationships with Near-Surface Environmental Factors across China’s Tianwen-1 Landing Zone

2021 ◽  
Vol 13 (11) ◽  
pp. 2206
Author(s):  
Yaowen Luo ◽  
Jianguo Yan ◽  
Fei Li ◽  
Bo Li
Keyword(s):  
Environmental Factors ◽  
Surface Temperature ◽  
Thermal Inertia ◽  
Temporal Variations ◽  
Spatial Aggregation ◽  
Driving Factors ◽  
Martian Surface ◽  
Near Surface ◽  
Landing Zone ◽  
Spatio Temporal

Variations in the Martian surface temperature indicate patterns of surface energy exchange. The Martian surface temperature at a location is similar to those in adjacent locations; but, an understanding of temperature clusters in multiple locations will deepen our knowledge of planetary surface processes overall. The spatial coherence of the Martian surface temperature (ST) at different locations, the spatio-temporal variations in temperature clusters, and the relationships between ST and near-surface environmental factors, however, are not well understood. To fill this gap, we studied an area to the south of Utopia Planitia, the landing zone for the Tianwen-1 Mars Exploration mission. The spatial aggregation of three Martian ST indicators (STIs), including sol average temperature (SAT), sol temperature range (STR), and sol-to-sol temperature change (STC), were quantitatively evaluated using clustering analysis at the global and local scale. In addition, we also detected the spatio-temporal variations in relations between the STIs and seven potential driving factors, including thermal inertia, albedo, dust, elevation, slope, and zonal and meridional winds, across the study area during 81 to 111 sols in Martian years 29–32, based on a geographically and temporally weighted regression model (GTWR). We found that the SAT, STR, and STC were not randomly distributed over space but exhibited signs of significant spatial aggregation. Thermal inertia and dust made the greatest contribution to the fluctuation in STIs over time. The local surface temperature was likely affected by the slope, wind, and local circulation, especially in the area with a large slope and low thermal inertia. In addition, the sheltering effects of the mountains at the edge of the basin likely contributed to the spatial difference in SAT and STR. These results are a reminder that the spatio-temporal variation in the local driving factors associated with Martian surface temperature cannot be neglected. Our research contributes to the understanding of the surface environment that might compromise the survival and operations of the Tianwen-1 lander on the Martian surface.

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