scholarly journals Shallow velocity model in the area of Pozzo Pitarrone, Mt. Etna, from single station, array methods and borehole data

2016 ◽  
Vol 59 (4) ◽  
Author(s):  
Luciano Zuccarello ◽  
Mario Paratore ◽  
Mario La Rocca ◽  
Ferruccio Ferrari ◽  
Alfio Messina ◽  
...  
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Seismic Noise ◽  
Velocity Model ◽  
P Wave ◽  
Borehole Data ◽  
P Wave Velocity ◽  
Single Station ◽  
Mt Etna

<p>Seismic noise recorded by a temporary array installed around Pozzo Pitarrone, NE flank of Mt. Etna, have been analysed with several techniques. Single station HVSR method and SPAC array method have been applied to stationary seismic noise to investigate the local shallow structure. The inversion of dispersion curves produced a shear wave velocity model of the area reliable down to depth of about 130 m. A comparison of such model with the stratigraphic information available for the investigated area shows a good qualitative agreement. Taking advantage of a borehole station installed at 130 m depth, we could estimate also the P-wave velocity by comparing the borehole recordings of local earthquakes with the same event recorded at surface. Further insight on the P-wave velocity in the upper 130 m layer comes from the surface reflected wave observable in some cases at the borehole station. From this analysis we obtained an average P-wave velocity of about 1.2 km/s, compatible with the shear wave velocity found from the analysis of seismic noise.</p>

Shear-Wave Velocity Model of the Bohemian Massif Crust from Ambient Noise Tomography

2020 ◽  
Author(s):  
Jiří Kvapil ◽  
Jaroslava Plomerová ◽  
Vladislav Babuška ◽  
Hana Kampfová Exnerová ◽  
Luděk Vecsey ◽  
...  
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Seismic Noise ◽  
Ambient Noise ◽  
Velocity Model ◽  
Receiver Functions ◽  
P Wave ◽  
Ambient Noise Tomography ◽  
Moldanubian Unit

&lt;p&gt;&lt;span&gt;&lt;span&gt;The current knowledge of the structure of the Bohemian Massif (BM) crust is mostly based on interpretation of refraction and reflection seismic experiments performed along 2D profiles. The recent development of ambient noise tomography, in combination with dense networks of permanent seismic stations and arrays of passive seismic experiments, provides unique opportunity to build the high-resolution 3D velocity model of the BM crust from long sequences of ambient seismic noise data.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;&lt;span&gt;The new 3D shear-wave velocity model is built from surface-wave group-velocity dispersion measurements derived from ambient seismic noise cross-correlations by conventional two-step inversion approach. First, the 2D fast marching travel time tomography is applied to regularise velocity dispersions. Second, the stochastic inversion is applied to compute 1D shear-wave velocity profiles beneath each location of the processing grid.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;&lt;span&gt;We processed continuous waveform data from 404 seismic stations (permanent and temporary stations of passive experiments BOHEMA I-IV, PASSEQ, EGER RIFT, ALPARRAY-EASI and ALPARRAY-AASN) in a broader region of the BM (in an area of 46-54&lt;/span&gt;&lt;/span&gt;&lt;sup&gt;&lt;span&gt;&lt;span&gt;0 &lt;/span&gt;&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;&lt;span&gt;N 7-21&lt;/span&gt;&lt;/span&gt;&lt;sup&gt;&lt;span&gt;&lt;span&gt;0 &lt;/span&gt;&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;&lt;span&gt;E). The overlapping period of each possible station-pair and cross-correlation quality review resulted in more than 21,000 dispersion curves, which further served as an input for surface-wave inversion &lt;/span&gt;&lt;/span&gt;&lt;span&gt;&lt;span&gt;at h&lt;/span&gt;&lt;/span&gt;&lt;span&gt;&lt;span&gt;igh-density grid with the cell size of 22 km. &lt;/span&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;&lt;span&gt;We present the new high-resolution 3D shear-wave velocity model of the BM crust and uppermost mantle with preliminary tectonic interpretations. We compare this model with a compiled P-wave velocity model from the 2D seismic refraction and wide-angle reflection experiments and with the crustal thickness (Moho depth) extracted from P-wave receiver functions (see Kampfov&amp;#225; Exnerov&amp;#225; et al., EGU2020_SM4.3). 1D velocity profiles resulting from the stochastic inversions exhibit regional variations, which are characteristic for individual units of the BM. Velocities within the upper crust of the BM are ~0.2 km/s higher than those in its surroundings. The highest crustal velocities occur in its southern part (Moldanubian unit). The velocity model confirms, in accord with results from receiver functions and other seismic studies, a relatively thin crust in the Saxothuringian unit, whilst thickness of the Moldanubian crust is at least 36 km in its central and southern parts. The most distinct interface with a velocity inversion at the depth of about 20 to 25 km occurs in the Moldanubian unit. The velocity decrease in the lower crust reflects probably its transversely isotropic structure.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;

Shear wave velocity model of the ABANICO formation underlying The santiago City Metropolitan Area, chile, using ambient seismic noise tomography

2020 ◽  
Author(s):  
J Salomón ◽  
C Pastén ◽  
S Ruiz ◽  
F Leyton ◽  
M Sáez ◽  
...  
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Metropolitan Area ◽  
Shear Wave Velocity ◽  
Seismic Noise ◽  
Velocity Model ◽  
Dispersion Curves ◽  
Ambient Seismic Noise ◽  
Travel Times ◽  
Abanico Formation

Summary The seismic response of the Santiago City, the capital of Chile with more than 5.5 million inhabitants, is controlled by the properties of the shallower quaternary deposits and the impedance contrast with the underlying Abanico formation, among other factors. In this study, we process continuous records of ambient seismic noise to perform an ambient seismic noise tomography with the aim of defining the shallower structure of the Abanico formation underneath the densely populated metropolitan area of Santiago, Chile. The seismic signals were recorded by a network consisting of 29 broadband seismological stations and 12 accelerograph stations, located in a 35 × 35 km2 quadrant. We used the average coherency of the vertical components to calculate dispersion curves from 0.1 to 5 Hz and Bootstrap resampling to estimate the variance of the travel times. The reliable frequency band of the dispersion curves was defined by an empirical method based on sign normalization of the coherency real part. The ambient noise tomography was solved on a domain discretized into 256 2 × 2 km2 cells. Using a regularized weighted least squares inversion, we inverted the observed travel-times between stations, assuming straight ray paths, in order to obtain 2D phase velocity maps from 0.2 Hz to 1.1 Hz, linearly spaced every 0.05 Hz, in 157 of the 256 square cells of the domain. In each square cell with information, dispersion curves were assembled and used to invert shear wave velocity profiles, which were interpolated using the ordinary Kriging method to obtain a 3D shear wave velocity model valid from 0.6 to 5 km depth. The 3D velocity model shows that the Abanico formation is stiffer in the south of the study area with larger velocity anomalies towards the shallower part of the model. The value of the shear wave velocity narrows with depth, reaching an average value of 3.5 km/s from 3 to 5 km depth.

Shallow Shear-Wave Velocity Structure in Oklahoma Based on the Joint Inversion of Ambient Noise Dispersion and Teleseismic P-Wave Receiver Functions

2020 ◽  
Author(s):  
Jiayan Tan ◽  
Charles A. Langston ◽  
Sidao Ni
Keyword(s):  
Surface Wave ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Ambient Noise ◽  
Sedimentary Basins ◽  
Velocity Model ◽  
Receiver Functions ◽  
P Wave ◽  
Velocity Models

ABSTRACT Ambient noise cross-correlations, used to obtain fundamental-mode Rayleigh-wave group velocity estimates, and teleseismic P-wave receiver functions are jointly modeled to obtain a 3D shear-wave velocity model for the crust and upper mantle of Oklahoma. Broadband data from 82 stations of EarthScope Transportable Array, the U.S. National Seismic Network, and the Oklahoma Geological Survey are used. The period range for surface-wave ambient noise Green’s functions is from 4.5 to 30.5 s constraining shear-wave velocity to a depth of 50 km. We also compute high-frequency receiver functions at these stations from 214 teleseismic earthquakes to constrain individual 1D velocity models inferred from the surface-wave tomography. Receiver functions reveal Ps conversions from the Moho, intracrustal interfaces, and shallow sedimentary basins. Shallow low-velocity zones in the model correlate with the large sedimentary basins of Oklahoma. The velocity model significantly improves the agreement of synthetic and observed seismograms from the 6 November 2011 Mw 5.7 Prague, Oklahoma earthquake suggesting that it can be used to improve earthquake location and moment tensor inversion of local and regional earthquakes.

scholarly journals Passive processing of active nodal seismic data: Estimation of V<sub>P</sub> / V<sub>S</sub>-ratios to characterize structure and hydrology of an alpine valley infill

2019 ◽  
Author(s):  
Michael Behm ◽  
Feng Cheng ◽  
Anna Patterson ◽  
Gerilyn Soreghan
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Ratio ◽  
Velocity Model ◽  
P Wave ◽  
Similar Data ◽  
S Wave ◽  
Alpine Valley ◽  
Active Source

Abstract. The advent of cable-free nodal arrays for conventional seismic reflection and refraction experiments is changing the acquisition style for active source surveys. Instead of triggering short recording windows for each shot, the nodes are continuously recording over the entire acquisition period from the first to the last shot. The main benefit is a significant increase in geometrical and logistical flexibility. As a by-product, a significant amount of continuous data might also be collected. These data can be analysed with passive seismic methods and therefore offer the possibility to complement subsurface characterization at marginal additional cost. We present data and results from a 2.4 km long active source profile which has been recently acquired in Western Colorado (US) to characterize the structure and sedimentary infill of an over-deepened alpine valley. We show how the leftover passive data from the active source acquisition can be processed towards a shear wave velocity model with seismic interferometry. The shear wave velocity model supports the structural interpretation of the active P-wave data, and the P-to-S-wave velocity ratio provides new insights into the nature and hydrological properties of the sedimentary infill. We discuss the benefits and limitations of our workflow and conclude with recommendations for acquisition and processing of similar data sets.

scholarly journals Passive processing of active nodal seismic data: estimation of <i>V</i><sub>P</sub>∕<i>V</i><sub>S</sub> ratios to characterize structure and hydrology of an alpine valley infill

Solid Earth ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 1337-1354 ◽  
Author(s):  
Michael Behm ◽  
Feng Cheng ◽  
Anna Patterson ◽  
Gerilyn S. Soreghan
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Ratio ◽  
Velocity Model ◽  
P Wave ◽  
S Wave ◽  
Alpine Valley ◽  
Active Source ◽  
Passive Seismic

Abstract. The advent of cable-free nodal arrays for conventional seismic reflection and refraction experiments is changing the acquisition style for active-source surveys. Instead of triggering short recording windows for each shot, the nodes are continuously recording over the entire acquisition period from the first to the last shot. The main benefit is a significant increase in geometrical and logistical flexibility. As a by-product, a significant amount of continuous data might also be collected. These data can be analyzed with passive seismic methods and therefore offer the possibility to complement subsurface characterization at marginal additional cost. We present data and results from a 2.4 km long active-source profile, which have recently been acquired in western Colorado (US) to characterize the structure and sedimentary infill of an over-deepened alpine valley. We show how the “leftover” passive data from the active-source acquisition can be processed towards a shear wave velocity model with seismic interferometry. The shear wave velocity model supports the structural interpretation of the active P-wave data, and the P-to-S-wave velocity ratio provides new insights into the nature and hydrological properties of the sedimentary infill. We discuss the benefits and limitations of our workflow and conclude with recommendations for the acquisition and processing of similar datasets.

Reconnaissance seismic refraction-reflection surveys in northwestern New Mexico

1984 ◽  
Vol 74 (4) ◽  
pp. 1263-1274
Author(s):  
Lawrence H. Jaksha ◽  
David H. Evans
Keyword(s):  
New Mexico ◽  
Wave Velocity ◽  
Lower Crust ◽  
Seismic Waves ◽  
Seismic Refraction ◽  
Velocity Model ◽  
P Wave ◽  
Uppermost Mantle ◽  
P Wave Velocity ◽  
Crustal Thinning

Abstract A velocity model of the crust in northwestern New Mexico has been constructed from an interpretation of direct, refracted, and reflected seismic waves. The model suggests a sedimentary section about 3 km thick with an average P-wave velocity of 3.6 km/sec. The crystalline upper crust is 28 km thick and has a P-wave velocity of 6.1 km/sec. The lower crust below the Conrad discontinuity has an average P-wave velocity of about 7.0 km/sec and a thickness near 17 km. Some evidence suggests that velocity in both the upper and lower crust increases with depth. The P-wave velocity in the uppermost mantle is 7.95 ± 0.15 km/sec. The total crustal thickness near Farmington, New Mexico, is about 48 km (datum = 1.6 km above sea level), and there is evidence for crustal thinning to the southeast.

scholarly journals Shear-wave velocity structure at Mt. Etna from inversion of Rayleigh-wave dispersion patterns (2 s < T < 20 s)

2010 ◽  
Vol 53 (2) ◽  
Author(s):  
Luigia Cristiano ◽  
Simona Petrosino ◽  
Gilberto Saccorotti ◽  
Matthias Ohrnberger ◽  
Roberto Scarpa
Keyword(s):  
Rayleigh Wave ◽  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Velocity Structure ◽  
Wave Dispersion ◽  
Dispersion Patterns ◽  
Mt Etna ◽  
Rayleigh Wave Dispersion ◽  
Shear Wave Velocity Structure

Multi-parameter model building for the Qiuyue structure using four-component ocean-bottom seismometer data

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Yuzhu Liu ◽  
Xinquan Huang ◽  
Jizhong Yang ◽  
Xueyi Liu ◽  
Bin Li ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Velocity Analysis ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Ocean Bottom Seismometer ◽  
Full Waveform ◽  
P Wave Velocity

Thin sand-mud-coal interbedded layers and multiples caused by shallow water pose great challenges to conventional 3D multi-channel seismic techniques used to detect the deeply buried reservoirs in the Qiuyue field. In 2017, a dense ocean-bottom seismometer (OBS) acquisition program acquired a four-component dataset in East China Sea. To delineate the deep reservoir structures in the Qiuyue field, we applied a full-waveform inversion (FWI) workflow to this dense four-component OBS dataset. After preprocessing, including receiver geometry correction, moveout correction, component rotation, and energy transformation from 3D to 2D, a preconditioned first-arrival traveltime tomography based on an improved scattering integral algorithm is applied to construct an initial P-wave velocity model. To eliminate the influence of the wavelet estimation process, a convolutional-wavefield-based objective function for the preprocessed hydrophone component is used during acoustic FWI. By inverting the waveforms associated with early arrivals, a relatively high-resolution underground P-wave velocity model is obtained, with updates at 2.0 km and 4.7 km depth. Initial S-wave velocity and density models are then constructed based on their prior relationships to the P-wave velocity, accompanied by a reciprocal source-independent elastic full-waveform inversion to refine both velocity models. Compared to a traditional workflow, guided by stacking velocity analysis or migration velocity analysis, and using only the pressure component or other single-component, the workflow presented in this study represents a good approach for inverting the four-component OBS dataset to characterize sub-seafloor velocity structures.

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