S‐wave Splitting Intensity Analysis and Inversion

2018 ◽  
Author(s):  
Daniele Boiero ◽  
Claudio Bagaini
Keyword(s):  
Intensity Analysis ◽  
S Wave ◽  
Wave Splitting ◽  
And Inversion

Guangxi Longtan Reservoir Earthquakes S-Wave Splitting

2017 ◽  
pp. 477-493
Author(s):  
Lijuan Lu ◽  
Bin Zhou ◽  
Xiang Wen ◽  
Shuiping Shi ◽  
Chunheng Yan ◽  
...  
Keyword(s):  
S Wave ◽  
Wave Splitting ◽  
Longtan Reservoir

The 1998 Valhall microseismic data set: An integrated study of relocated sources, seismic multiplets, and S-wave splitting

Geophysics ◽  
2009 ◽  
Vol 74 (5) ◽  
pp. B183-B195 ◽  
Author(s):  
K. De Meersman ◽  
J.-M. Kendall ◽  
M. van der Baan
Keyword(s):  
Seismic Anisotropy ◽  
Amplitude Ratio ◽  
Temporal Variations ◽  
Oil Field ◽  
P Wave ◽  
Wave Form ◽  
S Wave ◽  
Data Set ◽  
Wave Splitting ◽  
Source Mechanisms

We relocate 303 microseismic events recorded in 1998 by sensors in a single borehole in the North Sea Valhall oil field. A semiautomated array analysis method repicks the P- and S-wave arrival times and P-wave polarizations, which are needed to locate these events. The relocated sources are confined predominantly to a [Formula: see text]-thick zone just above the reservoir, and location uncertainties are half those of previous efforts. Multiplet analysis identifies 40 multiplet groups, which include 208 of the 303 events. The largest group contains 24 events, and five groups contain 10 or more events. Within each multiplet group, we further improve arrival-time picking through crosscorrelation, which enhances the relative accuracy of the relocated events and reveals that more than 99% of the seismic activity lies spatially in three distinct clusters. The spatial distribution of events and wave-form similarities reveal two faultlike structures that match well with north-northwest–south-southeast-trending fault planes interpreted from 3D surface seismic data. Most waveform differences between multiplet groups located on these faults can be attributed to S-wave phase content and polarity or P-to-S amplitude ratio. The range in P-to-S amplitude ratios observed on the faults is explained best in terms of varying source mechanisms. We also find a correlation between multiplet groups and temporal variations in seismic anisotropy, as revealed by S-wave splitting analysis. We explain these findings in the context of a cyclic recharge and dissipation of cap-rock stresses in response to production-driven compaction of the underlying oil reservoir. The cyclic nature of this mechanism drives the short-term variations in seismic anisotropy and the reactivation of microseismic source mechanisms over time.

scholarly journals A new acoustic assumption for orthorhombic media

2020 ◽  
Vol 223 (2) ◽  
pp. 1118-1129
Author(s):  
Mohammad Mahdi Abedi ◽  
Alexey Stovas
Keyword(s):  
Wave Propagation ◽  
Conventional Approach ◽  
P Wave ◽  
Model Parameters ◽  
Governing Equations ◽  
S Wave ◽  
S Waves ◽  
Exploration Seismology ◽  
And Inversion ◽  
Approximate Equations

SUMMARY In exploration seismology, the acquisition, processing and inversion of P-wave data is a routine. However, in orthorhombic anisotropic media, the governing equations that describe the P-wave propagation are coupled with two S waves that are considered as redundant noise. The main approach to free the P-wave signal from the S-wave noise is the acoustic assumption on the wave propagation. The conventional acoustic assumption for orthorhombic media zeros out the S-wave velocities along three orthogonal axes, but leaves significant S-wave artefacts in all other directions. The new acoustic assumption that we propose mitigates the S-wave artefacts by zeroing out their velocities along the three orthogonal symmetry planes of orthorhombic media. Similar to the conventional approach, our method reduces the number of required model parameters from nine to six. As numerical experiments on multiple orthorhombic models show, the accuracy of the new acoustic assumption also compares well to the conventional approach. On the other hand, while the conventional acoustic assumption simplifies the governing equations, the new acoustic assumption further complicates them—an issue that emphasizes the necessity of simple approximate equations. Accordingly, we also propose simpler rational approximate phase-velocity and eikonal equations for the new acoustic orthorhombic media. We show a simple ray tracing example and find out that the proposed approximate equations are still highly accurate.

Wave-energy patterns in carotid, brachial, and radial arteries: a noninvasive approach using wave-intensity analysis

2005 ◽  
Vol 289 (1) ◽  
pp. H270-H276 ◽  
Author(s):  
A. Zambanini ◽  
S. L. Cunningham ◽  
K. H. Parker ◽  
A. W. Khir ◽  
S. A. McG. Thom ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Flow Velocity ◽  
Wave Energy ◽  
Wave Speed ◽  
Applanation Tonometry ◽  
Wave Intensity ◽  
Intensity Analysis ◽  
Wave Intensity Analysis ◽  
S Wave ◽  
Ensemble Averaging

The study of wave propagation at different points in the arterial circulation may provide useful information regarding ventriculoarterial interactions. We describe a number of hemodynamic parameters in the carotid, brachial, and radial arteries of normal subjects by using noninvasive techniques and wave-intensity analysis (WIA). Twenty-one normal adult subjects (14 men and 7 women, mean age 44 ± 6 yr) underwent applanation tonometry and pulsed-wave Doppler studies of the right common carotid, brachial, and radial arteries. After ensemble averaging of the pressure and flow-velocity data, local hydraulic work was determined and a pressure-flow velocity loop was used to determine local wave speed. WIA was then applied to determine the magnitude, timings, and energies of individual waves. At all sites, forward-traveling (S) and backward-traveling (R) compression waves were observed in early systole. In mid- and late systole, forward-traveling expansion waves (X and D) were also seen. Wave speed was significantly higher in the brachial (6.97 ± 0.58 m/s) and radial (6.78 ± 0.62 m/s) arteries compared with the carotid artery (5.40 ± 0.34 m/s; P < 0.05). S-wave energy was greatest in the brachial artery (993.5 ± 87.8 mJ/m2), but R-wave energy was greatest in the radial artery (176.9 ± 19.9 mJ/m2). X-wave energy was significantly higher in the brachial and radial arteries (176.4 ± 32.7 and 163.2 ± 30.5 mJ/m2, respectively) compared with the carotid artery (41.0 ± 9.4 mJ/m2; P < 0.001). WIA illustrates important differences in wave patterns between peripheral arteries and may provide a method for understanding ventriculo-arterial interactions in the time domain.

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