scholarly journals An upper-mantleS-wave velocity model for Northern Europe from Love and Rayleigh group velocities

2008 ◽  
Vol 175 (3) ◽  
pp. 1154-1168 ◽  
Author(s):  
Christian Weidle ◽  
Valérie Maupin
Keyword(s):  
Wave Velocity ◽  
Velocity Model ◽  
Northern Europe ◽  
Group Velocities

Compressional‐wave velocities in attenuating media: A laboratory physical model study

Geophysics ◽  
2000 ◽  
Vol 65 (4) ◽  
pp. 1162-1167 ◽  
Author(s):  
Joseph B. Molyneux ◽  
Douglas R. Schmitt
Keyword(s):  
Phase Velocity ◽  
Group Velocity ◽  
Wave Velocity ◽  
Propagation Distance ◽  
Compressional Wave ◽  
Arrival Times ◽  
Wave Velocities ◽  
Amplitude Maximum ◽  
Phase And Group Velocities ◽  
Group Velocities

Elastic‐wave velocities are often determined by picking the time of a certain feature of a propagating pulse, such as the first amplitude maximum. However, attenuation and dispersion conspire to change the shape of a propagating wave, making determination of a physically meaningful velocity problematic. As a consequence, the velocities so determined are not necessarily representative of the material’s intrinsic wave phase and group velocities. These phase and group velocities are found experimentally in a highly attenuating medium consisting of glycerol‐saturated, unconsolidated, random packs of glass beads and quartz sand. Our results show that the quality factor Q varies between 2 and 6 over the useful frequency band in these experiments from ∼200 to 600 kHz. The fundamental velocities are compared to more common and simple velocity estimates. In general, the simpler methods estimate the group velocity at the predominant frequency with a 3% discrepancy but are in poor agreement with the corresponding phase velocity. Wave velocities determined from the time at which the pulse is first detected (signal velocity) differ from the predominant group velocity by up to 12%. At best, the onset wave velocity arguably provides a lower bound for the high‐frequency limit of the phase velocity in a material where wave velocity increases with frequency. Each method of time picking, however, is self‐consistent, as indicated by the high quality of linear regressions of observed arrival times versus propagation distance.

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.

Three-dimensional lithospheric S wave velocity model of the NE Tibetan Plateau and western North China Craton

2017 ◽  
Vol 122 (8) ◽  
pp. 6703-6720 ◽  
Author(s):  
Xingchen Wang ◽  
Yonghua Li ◽  
Zhifeng Ding ◽  
Lupei Zhu ◽  
Chunyong Wang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Wave Velocity ◽  
North China Craton ◽  
North China ◽  
Three Dimensional ◽  
Velocity Model ◽  
S Wave ◽  
Ne Tibetan Plateau

scholarly journals Antarctic Upper Mantle Rheology

2021 ◽  
pp. M56-2020-19
Author(s):  
E. R. Ivins ◽  
W. van der Wal ◽  
D. A. Wiens ◽  
A. J. Lloyd ◽  
L. Caron
Keyword(s):  
Wave Velocity ◽  
Upper Mantle ◽  
Effective Viscosity ◽  
Seismic Velocity ◽  
Imaging Techniques ◽  
Three Dimensional ◽  
Velocity Model ◽  
Mantle Flow ◽  
S Wave ◽  
Velocity Changes

AbstractThe Antarctic mantle and lithosphere are known to have large lateral contrasts in seismic velocity and tectonic history. These contrasts suggest differences in the response time scale of mantle flow across the continent, similar to those documented between the northeastern and southwestern upper mantle of North America. Glacial isostatic adjustment and geodynamical modeling rely on independent estimates of lateral variability in effective viscosity. Recent improvements in imaging techniques and the distribution of seismic stations now allow resolution of both lateral and vertical variability of seismic velocity, making detailed inferences about lateral viscosity variations possible. Geodetic and paleo sea-level investigations of Antarctica provide quantitative ways of independently assessing the three-dimensional mantle viscosity structure. While observational and causal connections between inferred lateral viscosity variability and seismic velocity changes are qualitatively reconciled, significant improvements in the quantitative relations between effective viscosity anomalies and those imaged by P- and S-wave tomography have remained elusive. Here we describe several methods for estimating effective viscosity from S-wave velocity. We then present and compare maps of the viscosity variability beneath Antarctica based on the recent S-wave velocity model ANT-20 using three different approaches.

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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