scholarly journals Seismic observations with broadband instruments at Santorini volcano

2018 ◽  
Vol 40 (3) ◽  
pp. 1150 ◽  
Author(s):  
A. Kolaitis ◽  
P. Papadimiriou ◽  
I. Kassaras ◽  
K. Makropoulos
Keyword(s):  
Low Frequency ◽  
Volcanic Tremor ◽  
Velocity Model ◽  
Dominant Frequency ◽  
Depth Range ◽  
Traveltime Inversion ◽  
Time Frequency ◽  
Inversion Procedure ◽  
Santorini Volcano ◽  
Better Than

Two arrays equipped with broadband sensors were installed for a period of 10 months, in order to study the seismic activity in the area of Santorini (Thira) volcano. During these periods, about 330 earthquakes were recorded and located within a radius of 50 km from the center of the caldera. An iterative damped traveltime inversion procedure yielded a local 1-D Ρ-wave velocity model and improved locations with an accuracy better than 5 Km in both horizontal and vertical components for 135 earthquakes. Those are mainly distributed within a depth range 5-18 Km, in the vicinity of the submarine Kolumbo Reef (NE of Santorini Island). Signal analysis of the recorded volcanic earthquakes including typical Fourier transformations and several operations in the time-frequency domain, allowed their dominant frequency determination and their classification into three groups based on waveform appearance and frequency content: (1) highfrequency events; (2) low-frequency events; and (3) volcanic tremor. Frequencytime analysis of tremor, detected at three stations, revealed two kinds of harmonic tremor with one sharp peak, at 3-5 Hz and 8.5-10 Hz.

scholarly journals Experimental Investigation on Time-Frequency Characteristics of Microseismic Signals in the Damage Evolution Process of Coal and Rock

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 809
Author(s):  
Wei Yang ◽  
Chengwu Li ◽  
Rui Xu ◽  
Xunchang Li
Keyword(s):  
Damage Evolution ◽  
Resonance Effect ◽  
Low Frequency ◽  
Dominant Frequency ◽  
Frequency Characteristics ◽  
Evolution Process ◽  
Deformation And Failure ◽  
Time Frequency ◽  
Rock Materials ◽  
Damage Degree

The deformation and failure of coal and rock materials is the primary cause of many engineering disasters. How to accurately and effectively monitor and forecast the damage evolution process of coal and rock mass, and form a set of prediction methods and prediction indicators is an urgent engineering problems to be solved in the field of rock mechanics and engineering. As a form of energy dissipation in the deformation process of coal and rock, microseismic (MS) can indirectly reflect the damage of coal and rock. In order to analyze the relationship between the damage degree of coal and rock and time-frequency characteristics of MS, the deformation and fracture process of coal and rock materials under different loading modes was tested. The time-frequency characteristics and generation mechanism of MS were analyzed under different loading stages. Meanwhile, the influences of properties of coal and rock materials on MS signals were studied. Results show that there is an evident mode cutoff point between high-frequency and low-frequency MS signals. The properties of coal and rock, such as the development degree of the original fracture, particle size and dense degree have a decisive influence on the amplitude, frequency, energy and other characteristic parameters of MS signals. The change of MS parameters is closely related to material damage, but has no strong relation with the loading rate. The richness of MS signals before the main fracture depends on the homogeneity of materials. With the increase of damage, the energy release rate increases, which can lead to the widening of MS signals spectrum. The stiffness and natural frequency of specimens decreases correspondingly. Meanwhile, the main reason that the dominant frequency of MS detected by sensors installed on the surface of coal and rock materials is mainly low-frequency is friction loss and the resonance effect. In addition, the spectrum and energy evolution of MS can be used as a characterization method of the damage degree of coal and rock materials. Furthermore, the results can provide important reference for prediction and early warning of some rock engineering disasters.

Full-traveltime inversion

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. R261-R274 ◽  
Author(s):  
Yi Luo ◽  
Yue Ma ◽  
Yan Wu ◽  
Hongwei Liu ◽  
Lei Cao
Keyword(s):  
Wave Equation ◽  
Seismic Data ◽  
Low Frequency ◽  
Velocity Model ◽  
New Wave ◽  
Severe Problem ◽  
Reflected Waves ◽  
Traveltime Inversion ◽  
Velocity Models ◽  
Kinematic Information

Many previously published wave-equation-based methods, which attempt to automatically invert traveltime or kinematic information in seismic data or migrated gathers for smooth velocities, suffer a common and severe problem — the inversions are involuntarily and unconsciously hijacked by amplitude information. To overcome this problem, we have developed a new wave-equation-based traveltime inversion methodology, referred to as full-traveltime (i.e., fully dependent on traveltime) inversion (FTI), to automatically estimate a kinematically accurate velocity model from seismic data. The key idea of FTI is to make the inversion fully dependent on traveltime information, and thus prevent amplitude interference during inversion. Under the assumption that velocity perturbations cause only traveltime changes, we have derived the FTI method in the data and image domains, which are applicable to transmitted arrivals and reflected waves, respectively. FTI does not require an accurate initial velocity model or low-frequency seismic data. Synthetic and field data tests demonstrate that FTI produces satisfactory inversion results, even when using constant velocity models as initials.

scholarly journals Seismic shot-encoding schemes for waveform inversion

2020 ◽  
Vol 17 (5) ◽  
pp. 906-913 ◽  
Author(s):  
Edwin Fagua Duarte ◽  
Carlos A N da Costa ◽  
João M de Araújo ◽  
Yanghua Wang ◽  
Ying Rao
Keyword(s):  
Waveform Inversion ◽  
Random Phase ◽  
Computational Cost ◽  
Velocity Model ◽  
Dominant Frequency ◽  
Seismic Waveform ◽  
Rotation Scheme ◽  
Iterative Inversion ◽  
Inversion Procedure ◽  
The Time Domain

Abstract A shot-encoding technique can be used in seismic waveform inversion to significantly reduce the computational cost by reducing the number of seismic simulations in the inversion procedure. Here we developed two alternative shot-encoding schemes to perform simultaneous-sources waveform inversion. The first scheme (I) encodes shot gathers with random-phase rotations applied to seismic traces. The second scheme (II) encodes shot gathers with random static time shifts. The well-known polarity encoding scheme (III) is just a special case of the random-phase rotation scheme. The second scheme is a variation of the conventional static shift encoding (IV), but the static time shifts in the second scheme are limited to one period of the dominant frequency. All encoded shot gathers are added up into a single super-shot gather for seismic waveform inversion. We perform the time-domain waveform inversion, using these shot-encoding schemes in conjunction with a restarted L-BFGS algorithm in the iterative inversion. The effectiveness and efficiency analyses demonstrate that the two shot-encoding schemes (I and II) proposed in this paper may improve the convergence of the iterative inversion, reduce the crosstalk effect among shots and consequently produce a subsurface velocity model with a high resolution.

High Resolution Time-Frequency Analysis Base on Ricker Atom Matching Pursuit Decomposition

2013 ◽  
Vol 284-287 ◽  
pp. 3115-3119
Author(s):  
Wei Song ◽  
Jia Hui Zuo ◽  
Peng Cheng Hu
Keyword(s):  
Frequency Analysis ◽  
Matching Pursuit ◽  
Low Frequency ◽  
Seismic Signal ◽  
Dominant Frequency ◽  
Frequency Resolution ◽  
Frequency Variation ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
The Impact

The high accuracy time-frequency representation of non-stationary signals is one of the key researches in seismic signal analysis. Low-frequency part of the seismic data often has a higher frequency resolution, on the contrary it tends to have lower frequency resolution in the high frequency part. It’s difficult to fine characterize the time-frequency variation of non-stationary seismic signals by conventional time-frequency analysis methods due to the limitation of the window function. Therefore based on the Ricker wavelet, we put forward the matching pursuit seismic trace decomposition method. It decomposes the seismic records into a series of single component atoms with different centre time, dominant frequency and energy, by making use of the Wigner-Ville distribution, has the time-frequency resolution of seismic signal reach the limiting resolution of the uncertainty principle and skillfully avoid the impact of interference terms in conventional Wigner-Ville distribution.

Automatic traveltime inversion via sparse decomposition of seismic data

Geophysics ◽  
2018 ◽  
Vol 83 (6) ◽  
pp. R659-R668 ◽  
Author(s):  
Bo Feng ◽  
Huazhong Wang ◽  
Ru-Shan Wu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Velocity Model ◽  
Inversion Method ◽  
Traveltime Inversion ◽  
Sparse Decomposition ◽  
Reflection Seismic ◽  
New Strategy ◽  
Gradient Based ◽  
Intersection Criterion

We have developed an automatic traveltime inversion (ATI) method to estimate the macrovelocity model from reflection seismic data. First, we extract the kinematic information (i.e., source/receiver ray parameters, traveltime, and source/receiver coordinates) of locally coherent events using a sparse-decomposition method. And then we evaluate a new strategy to calculate the reflection traveltime residual based on a ray-intersection criterion, eliminating the influence of seismic amplitude to the estimation of the traveltime residual. The velocity model can be updated iteratively by minimizing the traveltime residual functional with a gradient-based method. To obtain a smooth gradient free of artifacts, we first estimate the high-wavenumber components of the functional gradient with a total variation (TV) regularization method and then subtract it from the full gradient. Because the reflection traveltime residual calculation and velocity update are fully automated procedures, the proposed traveltime inversion method is referred to as ATI. We determine with 2D synthetic and field examples that ATI does not need a good starting model. Furthermore, it requires neither low-frequency seismic data nor long-offset acquisition. Nevertheless, the proposed traveltime residual calculation strategy is only valid for the 2D case, which limits its 3D applicability. We explore a possible solution for 3D extension.

First-arrival traveltime inversion of seismic diving waves observed on undulant surface

2021 ◽  
Vol 225 (2) ◽  
pp. 1020-1031
Author(s):  
Huachen Yang ◽  
Jianzhong Zhang ◽  
Kai Ren ◽  
Changbo Wang
Keyword(s):  
Turning Points ◽  
Analytical Formula ◽  
Velocity Model ◽  
Western China ◽  
Inversion Method ◽  
Mountain Area ◽  
Traveltime Inversion ◽  
Static Correction ◽  
Velocity Models ◽  
First Arrival

SUMMARY A non-iterative first-arrival traveltime inversion method (NFTI) is proposed for building smooth velocity models using seismic diving waves observed on irregular surface. The new ray and traveltime equations of diving waves propagating in smooth media with undulant observation surface are deduced. According to the proposed ray and traveltime equations, an analytical formula for determining the location of the diving-wave turning points is then derived. Taking the influence of rough topography on first-arrival traveltimes into account, the new equations for calculating the velocities at turning points are established. Based on these equations, a method is proposed to construct subsurface velocity models from the observation surface downward to the bottom using the first-arrival traveltimes in common offset gathers. Tests on smooth velocity models with rugged topography verify the validity of the established equations, and the superiority of the proposed NFTI. The limitation of the proposed method is shown by an abruptly-varying velocity model example. Finally, the NFTI is applied to solve the static correction problem of the field seismic data acquired in a mountain area in the western China. The results confirm the effectivity of the proposed NFTI.

scholarly journals Complex Principal Component Analysis of Antarctic Ice Sheet Mass Balance

2021 ◽  
Vol 13 (3) ◽  
pp. 480
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Principal Component Analysis ◽  
Ice Sheet ◽  
Low Frequency ◽  
Principal Component ◽  
Equatorial Pacific ◽  
Mass Change ◽  
Frequency Variation ◽  
Periodic Signal ◽  
Time Frequency ◽  
The Antarctic

Ice sheet changes of the Antarctic are the result of interactions among the ocean, atmosphere, and ice sheet. Studying the ice sheet mass variations helps us to understand the possible reasons for these changes. We used 164 months of Gravity Recovery and Climate Experiment (GRACE) satellite time-varying solutions to study the principal components (PCs) of the Antarctic ice sheet mass change and their time-frequency variation. This assessment was based on complex principal component analysis (CPCA) and the wavelet amplitude-period spectrum (WAPS) method to study the PCs and their time-frequency information. The CPCA results revealed the PCs that affect the ice sheet balance, and the wavelet analysis exposed the time-frequency variation of the quasi-periodic signal in each component. The results show that the first PC, which has a linear term and low-frequency signals with periods greater than five years, dominates the variation trend of ice sheet in the Antarctic. The ratio of its variance to the total variance shows that the first PC explains 83.73% of the mass change in the ice sheet. Similar low-frequency signals are also found in the meridional wind at 700 hPa in the South Pacific and the sea surface temperature anomaly (SSTA) in the equatorial Pacific, with the correlation between the low-frequency periodic signal of SSTA in the equatorial Pacific and the first PC of the ice sheet mass change in Antarctica found to be 0.73. The phase signals in the mass change of West Antarctica indicate the upstream propagation of mass loss information over time from the ocean–ice interface to the southward upslope, which mainly reflects ocean-driven factors such as enhanced ice–ocean interaction and the intrusion of warm saline water into the cavities under ice shelves associated with ice sheets which sit on retrograde slopes. Meanwhile, the phase signals in the mass change of East Antarctica indicate the downstream propagation of mass increase information from the South Pole toward Dronning Maud Land, which mainly reflects atmospheric factors such as precipitation accumulation.

Methods to isolate retrograde and prograde Rayleigh-wave signals

2019 ◽  
Vol 219 (2) ◽  
pp. 975-994 ◽  
Author(s):  
Gabriel Gribler ◽  
T Dylan Mikesell
Keyword(s):  
Rayleigh Wave ◽  
Time Domain ◽  
Fundamental Mode ◽  
Poisson Ratio ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Low Frequencies ◽  
Retrograde Motion ◽  
Mode Identification ◽  
Time Frequency

SUMMARY Estimating shear wave velocity with depth from Rayleigh-wave dispersion data is limited by the accuracy of fundamental and higher mode identification and characterization. In many cases, the fundamental mode signal propagates exclusively in retrograde motion, while higher modes propagate in prograde motion. It has previously been shown that differences in particle motion can be identified with multicomponent recordings and used to separate prograde from retrograde signals. Here we explore the domain of existence of prograde motion of the fundamental mode, arising from a combination of two conditions: (1) a shallow, high-impedance contrast and (2) a high Poisson ratio material. We present solutions to isolate fundamental and higher mode signals using multicomponent recordings. Previously, a time-domain polarity mute was used with limited success due to the overlap in the time domain of fundamental and higher mode signals at low frequencies. We present several new approaches to overcome this low-frequency obstacle, all of which utilize the different particle motions of retrograde and prograde signals. First, the Hilbert transform is used to phase shift one component by 90° prior to summation or subtraction of the other component. This enhances either retrograde or prograde motion and can increase the mode amplitude. Secondly, we present a new time–frequency domain polarity mute to separate retrograde and prograde signals. We demonstrate these methods with synthetic and field data to highlight the improvements to dispersion images and the resulting dispersion curve extraction.

scholarly journals Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function

2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu
Keyword(s):  
Frequency Domain ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Local Correlation ◽  
Time Frequency ◽  
Model Dependence ◽  
Full Waveform ◽  
Frequency Components

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.

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