Imaging of Near-Surface Structures at Valhall using Ambient-Seismic-Noise Eikonal Tomography

2011 ◽  
Author(s):  
S. de Ridder ◽  
J. Dellinger
Keyword(s):  
Seismic Noise ◽  
Surface Structures ◽  
Ambient Seismic Noise ◽  
Near Surface

Near‐surface VSstructure by inversion of surface wave estimated from ambient seismic noise

2015 ◽  
Vol 13 (5) ◽  
pp. 447-455 ◽  
Author(s):  
Taghi Shirzad ◽  
Z. Hossein Shomali ◽  
Mojtaba Naghavi ◽  
Rahim Norouzi
Keyword(s):  
Surface Wave ◽  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Near Surface

A linear algorithm for ambient seismic noise double beamforming without explicit crosscorrelations

Geophysics ◽  
2021 ◽  
Vol 86 (1) ◽  
pp. F1-F8
Author(s):  
Eileen R. Martin
Keyword(s):  
Correlation Functions ◽  
Seismic Noise ◽  
Ambient Noise ◽  
Computational Cost ◽  
Body Waves ◽  
Ambient Seismic Noise ◽  
Noise Correlation ◽  
Dense Array ◽  
Near Surface ◽  
Noise Interferometry

Geoscientists and engineers are increasingly using denser arrays for continuous seismic monitoring, and they often turn to ambient seismic noise interferometry for low-cost near-surface imaging. Although ambient noise interferometry greatly reduces acquisition costs, the computational cost of pair-wise comparisons between all sensors can be prohibitively slow or expensive for applications in engineering and environmental geophysics. Double beamforming of noise correlation functions is a powerful technique to extract body waves from ambient noise, but it is typically performed via pair-wise comparisons between all sensors in two dense array patches (scaling as the product of the number of sensors in one patch with the number of sensors in the other patch). By rearranging the operations involved in the double beamforming transform, I have developed a new algorithm that scales as the sum of the number of sensors in two array patches. Compared to traditional double beamforming of noise correlation functions, the new method is more scalable, easily parallelized, and it does not require raw data to be exchanged between dense array patches.

scholarly journals Using ambient seismic noise to study temporal and spatial surface wave velocity structures and ambient noise field characteristics of central South Island, New Zealand

2021 ◽  
Author(s):  
◽  
Rachel Heckels
Keyword(s):  
New Zealand ◽  
Surface Wave ◽  
Wave Velocity ◽  
Seismic Noise ◽  
Shear Velocity ◽  
Southern Alps ◽  
Ambient Seismic Noise ◽  
Near Surface ◽  
Surface Wave Velocity ◽  
Velocity Changes

<p>Ambient seismic noise is used to examine the spatial and temporal surface wave velocity structures and ambient seismic noise fields in the vicinity of different fault zone environments. This study focuses on two distinct regions of central South Island, New Zealand. The Canterbury Plains is a sedimentary basin with many minor faults, which was considered to have low seismic hazard prior to the 2010 – 2011 Canterbury earthquake sequence. We focus on the time period immediately following the 2010 Darfield earthquake, which ruptured the previously unmapped Greendale Fault. The second region of interest is the central Southern Alps. The locked portion of the Alpine Fault currently poses one of the largest seismic hazards for New Zealand. The wealth of data from both permanent and temporary seismic deployments in these regions make them ideal areas in which to assess the effectiveness of ambient noise for velocity modelling in regions surrounding faults at different stages of their seismic cycles.  Temporal velocity changes are measured following the Mw 7.1 Darfield earthquake of 4 September 2010 in the Canterbury Plains. Nine-component cross-correlations are computed from temporary and permanent seismic stations lying on and surrounding the Greendale Fault. Using the Moving-Window Cross-Spectral method, surface wave velocity changes are calculated for the four months immediately following the earthquake until 10 January 2011, for 0.1 — 1.0 Hz. An average increase in seismic velocity of 0.14 ± 0.04 % is determined throughout the region, providing the first such estimate of postseismic relaxation rates in Canterbury. Depth analyses further showed that velocity changes are confined to the uppermost 5 km of the subsurface and we attribute this to postseismic relaxation via crack-healing of the Greendale Fault and throughout the surrounding region.  Rayleigh and Love wave dispersion is examined throughout the Canterbury region. Multi-component cross-correlation functions are analysed for group and phase dispersion curves. These are inverted using frequency-time analysis for 2-D phase and group velocity maps of Rayleigh and Love waves. A high-velocity zone to the southeast of the region coincides with volcanic rocks of Banks Peninsula. Dispersion curves generated from the surface wave tomography are further inverted for one-dimensional shear velocity profiles. These models show a thin, low-velocity near surface layer consistent with the basin sediments, which thins towards the foothills of the Southern Alps. A near-surface damage zone is identified along the length of the Greendale Fault, with consistent reduced Vs velocities to depth of up to 5 km.  Surface and shear wave velocity maps are computed for the central Southern Alps to image the seismic structure of the region. Tomographic surface maps at periods of 5 – 12 s are produced from dispersion measurements of three-component cross-correlation functions. At periods of 5 – 8 s a strong NE-SW trending velocity contrast highlights the Alpine Fault. One-dimensional shear velocity models, computed from the surface wave maps, are in agreement with previous models produced by other conventional methods. An analysis of surface wave amplitudes through signal-to-noise ratios of cross-correlations reveals strong directional effects. Calculated signal-to-noise ratios are up to eight times higher for surface waves travelling north-west than for waves travelling to the south or east. We attribute this to a combination of more energetic ocean wave signals from the Southern Ocean compared to the Tasman Sea.</p>

scholarly journals Monitoring transient changes within overpressured regions of subduction zones using ambient seismic noise

2016 ◽  
Vol 2 (1) ◽  
pp. e1501289 ◽  
Author(s):  
Esteban J. Chaves ◽  
Susan Y. Schwartz
Keyword(s):  
Seismic Noise ◽  
Subduction Zones ◽  
Seismic Velocity ◽  
Fluid Pressure ◽  
Pore Fluid ◽  
Ambient Seismic Noise ◽  
Pore Fluid Pressure ◽  
Near Surface ◽  
Velocity Reduction ◽  
Pressurized Fluids

In subduction zones, elevated pore fluid pressure, generally linked to metamorphic dehydration reactions, has a profound influence on the mechanical behavior of the plate interface and forearc crust through its control on effective stress. We use seismic noise–based monitoring to characterize seismic velocity variations following the 2012 Nicoya Peninsula, Costa Rica earthquake [Mw(moment magnitude) 7.6] that we attribute to the presence of pressurized pore fluids. Our study reveals a strong velocity reduction (~0.6%) in a region where previous work identified high forearc pore fluid pressure. The depth of this velocity reduction is constrained to be below 5 km and therefore not the result of near-surface damage due to strong ground motions; rather, we posit that it is caused by fracturing of the fluid-pressurized weakened crust due to dynamic stresses. Although pressurized fluids have been implicated in causing coseismic velocity reductions beneath the Japanese volcanic arc, this is the first report of a similar phenomenon in a subduction zone setting. It demonstrates the potential to identify pressurized fluids in subduction zones using temporal variations of seismic velocity inferred from ambient seismic noise correlations.

scholarly journals Near‐Surface Environmentally Forced Changes in the Ross Ice Shelf Observed With Ambient Seismic Noise

2018 ◽  
Vol 45 (20) ◽  
Author(s):  
J. Chaput ◽  
R. C. Aster ◽  
D. McGrath ◽  
M. Baker ◽  
R. E. Anthony ◽  
...  
Keyword(s):  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Ice Shelf ◽  
Near Surface ◽  
Ross Ice Shelf

Ambient seismic noise eikonal tomography for near-surface imaging at Valhall

2011 ◽  
Vol 30 (5) ◽  
pp. 506-512 ◽  
Author(s):  
Sjoerd de Ridder ◽  
Joe Dellinger
Keyword(s):  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Surface Imaging ◽  
Near Surface

scholarly journals Synthetic Modeling of Ambient Seismic Noise Tomography Data

2021 ◽  
Vol 873 (1) ◽  
pp. 012096
Author(s):  
Firman Syaifuddin ◽  
Andri Dian Nugraha ◽  
Zulfakriza ◽  
Shindy Rosalia
Keyword(s):  
Seismic Noise ◽  
Ambient Noise ◽  
Noise Analysis ◽  
Reference Signal ◽  
Synthetic Data ◽  
Data Modeling ◽  
The United States ◽  
Ambient Seismic Noise ◽  
Near Surface ◽  
Tomography Method

Abstract Ambient seismic noise tomography is one of the most widely used methods in seismological studies today, especially after a comprehensive Earth noise model was published and noise analysis was performed on the IRIS Global Seismographic Network. Furthermore, the Power Spectral Density technique was introduced to identify background seismic noise in the United States. Many studies have been carried out using the ambient seismic noise tomography method which can be broadly grouped into several groups based on the objectives and research targets, such as to determine the structure of the earth’s crust and the upper mantle, to know the thickness of the sedimentary basins, to know the tectonic settings and geological structures, to know volcanic systems and geothermal systems, knowing near-surface geological features and as a monitoring effort the Ambient Noise Tomography method carried out by repeated measurements or time lapse. In this study, we investigate the characteristics of the ambient noise seismic tomography method, both its advantages and limitations of the method by utilizing synthetic data modeling using a simple geological model. Synthetic data is generated based on 1D dispersion curve forward modelling and the forward modeling of surface waves travel time for each period, which is then convoluted with the wavelets of each periods, then doing reverse correlation using a reference signal to produce synthetic recording data. We found that the estimate target depth and vertical resolution depend on the recorded data periods and the synthetic data modeling can be used as a basis in determining the acquisition design.

scholarly journals Using ambient seismic noise to study temporal and spatial surface wave velocity structures and ambient noise field characteristics of central South Island, New Zealand

2021 ◽  
Author(s):  
◽  
Rachel Heckels
Keyword(s):  
New Zealand ◽  
Surface Wave ◽  
Wave Velocity ◽  
Seismic Noise ◽  
Shear Velocity ◽  
Southern Alps ◽  
Ambient Seismic Noise ◽  
Near Surface ◽  
Surface Wave Velocity ◽  
Velocity Changes

<p>Ambient seismic noise is used to examine the spatial and temporal surface wave velocity structures and ambient seismic noise fields in the vicinity of different fault zone environments. This study focuses on two distinct regions of central South Island, New Zealand. The Canterbury Plains is a sedimentary basin with many minor faults, which was considered to have low seismic hazard prior to the 2010 – 2011 Canterbury earthquake sequence. We focus on the time period immediately following the 2010 Darfield earthquake, which ruptured the previously unmapped Greendale Fault. The second region of interest is the central Southern Alps. The locked portion of the Alpine Fault currently poses one of the largest seismic hazards for New Zealand. The wealth of data from both permanent and temporary seismic deployments in these regions make them ideal areas in which to assess the effectiveness of ambient noise for velocity modelling in regions surrounding faults at different stages of their seismic cycles.  Temporal velocity changes are measured following the Mw 7.1 Darfield earthquake of 4 September 2010 in the Canterbury Plains. Nine-component cross-correlations are computed from temporary and permanent seismic stations lying on and surrounding the Greendale Fault. Using the Moving-Window Cross-Spectral method, surface wave velocity changes are calculated for the four months immediately following the earthquake until 10 January 2011, for 0.1 — 1.0 Hz. An average increase in seismic velocity of 0.14 ± 0.04 % is determined throughout the region, providing the first such estimate of postseismic relaxation rates in Canterbury. Depth analyses further showed that velocity changes are confined to the uppermost 5 km of the subsurface and we attribute this to postseismic relaxation via crack-healing of the Greendale Fault and throughout the surrounding region.  Rayleigh and Love wave dispersion is examined throughout the Canterbury region. Multi-component cross-correlation functions are analysed for group and phase dispersion curves. These are inverted using frequency-time analysis for 2-D phase and group velocity maps of Rayleigh and Love waves. A high-velocity zone to the southeast of the region coincides with volcanic rocks of Banks Peninsula. Dispersion curves generated from the surface wave tomography are further inverted for one-dimensional shear velocity profiles. These models show a thin, low-velocity near surface layer consistent with the basin sediments, which thins towards the foothills of the Southern Alps. A near-surface damage zone is identified along the length of the Greendale Fault, with consistent reduced Vs velocities to depth of up to 5 km.  Surface and shear wave velocity maps are computed for the central Southern Alps to image the seismic structure of the region. Tomographic surface maps at periods of 5 – 12 s are produced from dispersion measurements of three-component cross-correlation functions. At periods of 5 – 8 s a strong NE-SW trending velocity contrast highlights the Alpine Fault. One-dimensional shear velocity models, computed from the surface wave maps, are in agreement with previous models produced by other conventional methods. An analysis of surface wave amplitudes through signal-to-noise ratios of cross-correlations reveals strong directional effects. Calculated signal-to-noise ratios are up to eight times higher for surface waves travelling north-west than for waves travelling to the south or east. We attribute this to a combination of more energetic ocean wave signals from the Southern Ocean compared to the Tasman Sea.</p>

Sign in / Sign up

Export Citation Format

Share Document