Rayleigh Wave Dispersion Curves Research Articles

Imaging the seismic velocity structure of the crust and upper mantle in the northern East African Rift using Rayleigh wave tomography

SUMMARY Understanding the dynamics and evolution of continental rifting is broadly important for our understanding of plate tectonics. The northern East African Rift offers an excellent opportunity to study these processes at an active rift that was initiated by a large magmatic event. Multiple seismic models have been produced to understand the evolution of magmatism which image punctuated slow velocity zones in the asthenosphere. However, the depth extent of the slow velocity bodies has been less well constrained leading to much debate regarding the primary controls on melt generation. Variations between methods, resolution and scale of the seismic models make direct quantitative comparisons challenging. The lack of instrumentation off-rift further limits our understanding of the spatial extent of tectonic and magmatic processes, which is crucial to understanding magmatic continental rifting. In this paper, we jointly invert Rayleigh wave dispersion curves from ambient noise and teleseisms to obtain absolute shear velocity maps at 10–150 km depth. This includes data from a new seismic network located on the Ethiopian Plateau and enhanced resolution at Moho and upper-mantle depths from the joint inversion. At crustal depths, velocities are slowest beneath the Main Ethiopian Rift and the off-rift Ethiopian Plateau (<3.00–3.75 ± 0.04 km s−1, 10–40 km depth) and ongoing magmatic emplacement is required. At 60–80 km depth off-rift, we observe a fast velocity lid (>0.1 km s−1 faster than surroundings), in agreement with previous estimates of lithospheric thickness from receiver functions. The fast lid is not observed within the Main Ethiopian Rift or central Afar which instead are underlain by asthenospheric slow velocity anomalies (<4.05 ± 0.04 km s−1 at 60–120 km depth). This suggests melt is infiltrating the lithosphere within the rift. Furthermore, punctuated asthenospheric slow velocity anomalies (∼110 × 80 km wide) exist in areas that have not undergone significant crustal and plate thinning, potentially indicating melt infiltration may start prior to significant plate deformation. Finally, the punctuated asthenospheric slow velocity zones are not located directly beneath melt-rich crustal regions including those off-rift, suggesting melt migration processes are dynamic and/or may occur laterally.

Shear Velocity from Seismic Ambient Noise to Determine Crustal Structure and Re-Fitting Rock Physics Modeling in Dhafriyah and Kumaite Oil Fields

The current study aims to estimate the cortical structure of this region in Dhafriyah and Kumaite Oilfield. The cross-correlation of ambient seismic noise was applied in Anbar, Karbala, and Amarah to estimate a detailed velocity model for the sedimentary cover using data from three broadband seismic stations. Rayleigh wave dispersion curves were applied to obtain an accurate velocity model of the sedimentary cover. The results show that the crustal structure in the study area has three distinct discontinuities; the first is the discontinuity within the sedimentary cover column with a thickness around 4km (Vs 2.44km/s); the second is the basement rocks with a depth of 12km (Vs 3.17km/s), and the third is the Moho discontinuity with a depth of 46km (Vs 3.87km/s). Thus, the sedimentary thickness in the study area is around 12 km and the continental crust is around 34km. The first one, is done with using final out-puts of the velocity model of ANT (Vp, Vs, RHOB) to refitting rock physics modeling. The results show a good match with seismic cubes results may be used for prospect evaluation across different fields Dhafriyah and Kumaite, reservoir characterization, and formation evaluation.

Crustal S-Wave Velocity Structure Beneath the Northwestern Bohemian Massif, Central Europe, Revealed by the Inversion of Multimodal Ambient Noise Dispersion Curves

The northwestern Bohemian Massif and adjacent areas are a tectonically active region associated with complex geodynamic activities, that manifest as Quaternary volcanism, earthquake swarms in the upper and middle crust, degassing of CO2, and crustal fluid migration. The intricate tectonic evolution and activities of this region reflect the complexity of the crustal structure therein. However, the crustal models derived from previous studies in this area offer different, even contradictory information regarding the existence of a mid-crustal low-velocity zone (LVZ). In this study, we apply the frequency-Bessel transform (F-J) method to extract the fundamental-mode and up to five higher-mode Rayleigh wave dispersion curves from ambient seismic noise data recorded in the study area and perform multimodal ambient noise dispersion curves inversion. The addition of higher-mode dispersion curves enhances the vertical resolution of the velocity structure inversion results. Our models support the view that the general S-wave velocity level of the crust is high within the study area. We detect two S-wave LVZs beneath the study area that are distributed mainly in the middle crust rather than the lower crust, and these LVZs are separated by a high-velocity zone. Considering the results of previous studies in the area, we infer that these S-wave LVZs may be the consequence of crustal fluids, plastic deformation and even partial melting of the felsic middle crust at relatively high crustal temperatures. Furthermore, these S-wave LVZs could be responsible for the origin and foci depth distribution of earthquake swarms. S-wave low-velocity anomalies are also observed in the uppermost mantle beneath the study area. These S-wave models based on the joint inversion of multimodal dispersion curves can provide new references for understanding the tectonic activity and geodynamic evolution of the northwestern Bohemian Massif and adjacent areas.

Rayleigh-Wave Dispersion Curves from Energetic Hurricanes in the Southeastern United States

ABSTRACT Seismic records during energetic storms, similar to earthquake signals, carry information about the Earth’s interior. However, the utility of these records is rare in seismic imaging, because signal onsets in storm-generated microseisms are difficult to pick. The exciting seismic sources are also unsteady. Here, we present a new method for extracting accurate Rayleigh-wave dispersion curves from broadband seismic recordings made during the passage of hurricanes by incorporating Shen et al. (2012) cross-correlation strategy with Wang et al. (2019) frequency–Bessel transform array stacking technique. We show that surface-wave dispersion curves are observed in the seismic recordings made of four hurricanes. Compared with dispersion curves from hurricanes traveling onshore or in the deepwater, dispersion curves have higher signal-to-noise ratios from hurricanes moving near the coast or along the continental shelf. The average dispersion curve obtained from stacked cross correlations of all the four hurricanes agrees closely with that obtained from yearly ambient noise. We utilize the average dispersion curve from hurricanes to obtain a reliable shear-wave velocity (VS) model. Our VS model matches that derived from annual ambient seismic noise results with an average difference less than 0.1 km/s in the crust and uppermost mantle. This study suggests that hurricane-based dispersion curves can be an effective supplement to surface-wave tomography.

Microtremor Survey Method: A New Approach for Geothermal Exploration

Geothermal resources are a type of sustainable and green energy, which can play an important role in emission peaks and carbon neutrality. Determining the best development target area is key to resource development and geophysical methods are commonly used for this purpose. Owing to serious human and industrial interference, the microtremor survey method is often adopted for geothermal exploration in urban areas. It is a passive source method, which is non-invasive and environmentally friendly. In this method, the Rayleigh wave dispersion curve is extracted using spatial autocorrelation based on the vertical component signal at the observation station. A genetic algorithm is used to invert the dispersion curve of one survey point to obtain strata parameters such as layer thickness, S-wave velocity, and density. It provides critical parameters for the cap layer and reservoirs for geothermal exploration. For a chain microtremor measurement, a two-dimensional (2D) apparent S-wave velocity section can be generated. The apparent S-wave velocity is calculated from the phase velocity using the following empirical method: the 2D apparent S-wave velocity section helps to identify the buried channel for heat flow and track the irregular shapes of the reservoirs or cap layers. It has been verified that the microtremor survey method is reliable and accurate compared with borehole materials. As a newly developed non-invasive geophysical method, it can be widely used in geothermal exploration.

Estimation of Shear-Wave Velocity Structures in Taichung, Taiwan, Using Array Measurements of Microtremors

Near-surface S-wave velocity structures (VS) are crucial in site-effect studies and ground-motion simulations or predictions. We explored S-wave velocity structures in Taichung, the second-largest city in Taiwan by population, by employing array measurements of microtremors at a total of 53 sites. First, the fundamental-mode dispersion curves of Rayleigh waves were estimated by adopting the frequency–wavenumber analysis method. Second, the surface-wave inversion technique was used to calculate the S-wave velocity structures of the area. At many sites, observed phase velocities were almost flat, with a phase velocity of approximately 800–1300 m/s in the frequency range of 0.6–2 Hz. A high-velocity zone (VS of 900–1500 m/s) with a convex shape was observed at the shallow S-wave structures of these sites (depths of 50–500 m). On the basis of the inversion results, we constructed two-dimensional and three-dimensional contour maps to elucidate the variations of VS structures in Taichung. According to VS-contour maps at different depths, lowest S-wave velocities are found at the western coastal plain, whereas highest S-wave velocities appear on the eastern side. The S-wave velocity gradually decreases from east to west. Moreover, the S-wave velocity of the Tertiary bedrock is assumed to be 1500 m/s in the area. According to the depth-contour map (VS = 1500 m/s), the depths of the bedrock range from 250 m (the eastern part) to 1550 m (the western part). The thicknesses of the alluvium gradually decrease from west to east. Our results are consistent with the geology of the Taichung area.

Constructing shear velocity models from surface wave dispersion curves using deep learning

Surface wave tomography has been widely used to determine shear wave velocities by inverting surface wave dispersion curves. Conventional least-squares inversions strongly depend on an initial model and Monte Carlo inversion algorithms are usually time-consuming. In this study, we apply a deep neural network (DNN) to surface wave dispersion curves to investigate whether the initial model can be relaxed and whether reliable shear velocity models can be constructed. By applying our method to synthetic and field data, our results show that: (1) by constructing a well-trained DNN model from the global continental CRUST1.0 data, the DNN approach is effective and efficient to determine shear velocity structures using Rayleigh wave dispersion curves; (2) using the well-trained DNN model, no prior model is required, relaxing the requirement of an initial model; (3) the well-trained DNN model can be used to construct pseudo 3D seismic models across different continental areas.

Near-surface velocity inversion from Rayleigh wave dispersion curves based on a differential evolution simulated annealing algorithm

The utilization of urban underground space in a smart city requires an accurate understanding of the underground structure. As an effective technique, Rayleigh wave exploration can accurately obtain information on the subsurface. In particular, Rayleigh wave dispersion curves can be used to determine the near-surface shear-wave velocity structure. This is a typical multiparameter, high-dimensional nonlinear inverse problem because the velocities and thickness of each layer must be inverted simultaneously. Nonlinear methods such as simulated annealing (SA) are commonly used to solve this inverse problem. However, SA controls the iterative process though temperature rather than the error, and the search direction is random; hence, SA always falls into a local optimum when the temperature setting is inaccurate. Specifically, for the inversion of Rayleigh wave dispersion curves, the inversion accuracy will decrease with an increasing number of layers due to the greater number of inversion parameters and large dimension. To solve the above problems, we convert the multiparameter, high-dimensional inverse problem into multiple low-dimensional optimizations to improve the algorithm accuracy by incorporating the principle of block coordinate descent (BCD) into SA. Then, we convert the temperature control conditions in the original SA method into error control conditions. At the same time, we introduce the differential evolution (DE) method to ensure that the iterative error steadily decreases by correcting the iterative error direction in each iteration. Finally, the inversion stability is improved, and the proposed inversion method, the block coordinate descent differential evolution simulated annealing (BCDESA) algorithm, is implemented. The performance of BCDESA is validated by using both synthetic data and field data from western China. The results show that the BCDESA algorithm has stronger global optimization capabilities than SA, and the inversion results have higher stability and accuracy. In addition, synthetic data analysis also shows that BCDESA can avoid the problems of the conventional SA method, which assumes the S-wave velocity structure in advance. The robustness and adaptability of the algorithm are improved, and more accurate shear-wave velocity and thickness information can be extracted from Rayleigh wave dispersion curves. • We convert the high-dimensional inverse problem into multiple low-dimensional optimizations to improve accuracy by using BCD. • We ​use the error as control conditions different from that in SA to avoid the inversion falling into local optima. • We introduce DE to ensure that the iterative error steadily decreases by correcting the iterative error direction.

Characterization of the seismic field at Virgo and improved estimates of Newtonian-noise suppression by recesses

Fluctuations of gravitational forces cause so-called Newtonian noise (NN) in gravitational-wave detectors which is expected to limit their low-frequency sensitivity in upcoming observing runs. Seismic NN is produced by seismic waves passing near a detector’s suspended test masses. It is predicted to be the strongest contribution to NN. Modeling this contribution accurately is a major challenge. Arrays of seismometers were deployed at the Virgo site to characterize the seismic field near the four test masses. In this paper, we present results of a spectral analysis of the array data from one of Virgo’s end buildings to identify dominant modes of the seismic field. Some of the modes can be associated with known seismic sources. Analyzing the modes over a range of frequencies, we provide a dispersion curve of Rayleigh waves. We find that the Rayleigh speed in the NN frequency band 10–20 Hz is very low (≲100 m s−1), which has important consequences for Virgo’s seismic NN. Using the new speed estimate, we find that the recess formed under the suspended test masses by a basement level at the end buildings leads to a 10 fold reduction of seismic NN.

Building a geothermal formation model using microtremor array measurement

A comprehensive understanding of the internal structure and construction of a geomechanical formation model play an important role in developing and using geothermal resources. Formation models help in identifying the channel and cycling modes of the heat flow. Due to urban sprawl and development, constructing a formation model of geothermal resources based on data from traditional geophysical methods is challenging. The microtremor survey method (MSM) is adopted to obtain critical information in Jimo, which is famous for rare seawater geothermal resources in China. Three microtremor survey lines are deployed to identify subsurface structures up to 2 km into the ground. Dispersion curves of Rayleigh waves with frequencies from 0.4 to 10 Hz are extracted using the spatial autocorrelation method. An empirical equation is adopted to obtain the apparent shear wave (S-wave) velocity of each survey point and to plot the apparent S-wave velocity sections. The obtained sections reveal the development of two interacting faults, which form a channel for the heat-flow cycle. Two conceptual models are established to depict the formation and cycling modes of seawater geothermal resources in Jimo, based on the results and analysis. Our model will help verify the geothermal system and scientifically guide the development of unique geothermal resources. Moreover, the developed model verifies that MSM is effective and dependable for identifying fracture zones and strata.

Vestiges of underplating and assembly in the central North China Craton based on S-wave velocities

The destruction of the North China Craton (NCC) is a controversial topic among researchers. In particular, the crustal structure associated with the craton’s destruction remains unclear, even though a large number of seismic studies have been carried out in this area. To investigate the crustal structure and its dynamic implications, we perform noise tomography in the central part of the NCC. In this study, continuous vertical-component waveforms spanning one year from 112 broadband seismic stations are used to obtain the group velocity dispersion curves of Rayleigh waves at different periods, and surface wave tomography is employed to extract the Rayleigh wave group velocity distributions at 9–40 s. Finally, the S-wave velocity structure at depths of 0–60 km is determined by the inversion of pure-path dispersion data. The results show obvious differences in the crustal structure among the Western Block (WB), the Trans-North China Orogen (TNCO) and the Eastern Block (EB). The lower crust of the northern part of the EB exhibits a high-velocity S-wave anomaly, which may be related to magmatic underplating in the lower crust induced by an upwelling mantle plume. The S-wave velocity of the WB is lower than that of the TNCO in the upper and middle crust and is lower than that of both the TNCO and the EB in the lower crust. The crust of the TNCO shows higher S-wave velocities than the WB and EB in the upper and middle crust, and its overall S-wave velocity structure is clearly different from those of the WB and EB, implying that the crustal structure of the TNCO may contain vestiges of the Paleoproterozoic collision between the WB and EB and their subsequent assembly. This study marks the first time these findings are identified for the NCC.

On the Utility of Horizontal-to-Vertical Spectral Ratios of Ambient Noise in Joint Inversion with Rayleigh Wave Dispersion Curves for the Large-N Maupasacq Experiment.

Horizontal-to-Vertical Spectral Ratios (HVSR) and Rayleigh group velocity dispersion curves (DC) can be used to estimate the shallow S-wave velocity () structure. Knowing the structure is important for geophysical data interpretation either in order to better constrain data inversions for P-wave velocity () structures such as travel time tomography or full waveform inversions or to directly study the structure for geo-engineering purposes (e.g., ground motion prediction). The joint inversion of HVSR and dispersion data for 1D structure allows characterising the uppermost crust and near surface, where the HVSR data ( to ) are most sensitive while the dispersion data (1 to ) constrain the deeper model which would, otherwise, add complexity to the HVSR data inversion and adversely affect its convergence. During a large-scale experiment, 197 three-component short-period stations, 41 broad band instruments and 190 geophones were continuously operated for 6 months (April to October 2017) covering an area of approximately with a site spacing of approximately 1 to . Joint inversion of HVSR and DC allowed estimating and, to some extent density, down to depths of around . Broadband and short period instruments performed statistically better than geophone nodes due to the latter’s gap in sensitivity between HVSR and DC. It may be possible to use HVSR data in a joint inversion with DC, increasing resolution for the shallower layers and/or alleviating the absence of short period DC data, which may be harder to obtain. By including HVSR to DC inversions, confidence improvements of two to three times for layers above were achieved. Furthermore, HVSR/DC joint inversion may be useful to generate initial models for 3D tomographic inversions in large scale deployments. Lastly, the joint inversion of HVSR and DC data can be sensitive to density but this sensitivity is situational and depends strongly on the other inversion parameters, namely and . Density estimates from a HVSR/DC joint inversion should be treated with care, while some subsurface structures may be sensitive, others are clearly not. Inclusion of gravity inversion to HVSR/DC joint inversion may be possible and prove useful.

Ambient noise tomography of the Katmai volcanic area, Alaska

We present an ambient noise tomographic study of the mid-crustal magmatic system in the Katmai area, Alaska. Using multi-component (vertical and radial) seismic records at 70 stations deployed at various times over 20 years, we construct corresponding cross-correlograms and extract ~1010 Rayleigh-wave dispersion curves in the periods between 2 and 30 s. These enable us to obtain corresponding group velocity maps and finally a 3-D shear-wave velocity model to a depth of 25 km. The most striking feature is a ~25 km wide low-velocity anomaly beneath the Katmai area at depths of approximately 10 to 20 km, which we interpret as a mid-crustal magma storage zone. Our study complements previous local-scale tomography studies that unveil small upper crustal reservoirs, revealing the likely deep magma source ultimately responsible for the 1912 Novarupta-Katmai eruption.

Reconstruction of a Reference Subsoil Model for the Seismic Microzonation of Gori (Georgia): A Procedure Based on Principal Component Analysis (PCA)

ABSTRACTThis article focuses on the full exploitation of geological and economically viable geophysical surveys for the seismic characterization of the shallow subsoil in the frame of microzonation studies in urban areas where economic resources for detailed seismic response analyses are scarce. In these conditions, the outcomes of inexpensive geophysical surveys (e.g., based on ambient vibration monitoring or surface-wave prospecting) must be fully exploited. To reduce the uncertainties related to these kinds of procedures, their joint interpretation in the light of geological evidence is mandatory. To this purpose, we propose the application of principal component analysis to combine the results of distributed single-station ambient vibration measurements (horizontal-to-vertical spectral ratio [HVSR] technique) to provide a preliminary zonation of the study area. The zones identified in this way are then characterized by considering the available geognostic boreholes, VS profiles deduced by the joint inversion of HVSR curves, and available Rayleigh-wave dispersion curves deduced from active seismic prospecting (multichannel analysis of surface-waves technique). The final outcome allows the definition of a preliminary seismic model of the study area, which is also constrained by the available geological data deduced from on-purpose surveys. The proposed approach has been applied to the city of Gori (Georgia). The proposed approach allowed a reliable assessment of buried geometries, geological domains, and the distribution of lithofacies, which can control the local seismic response. In detail, the major role of paleovalley infills and interfluve domains has been enlightened by adding in evidence concerning the peculiar stratigraphic relationships and buried morphologies, which may determine 1D and 2D resonance effects.

S‐Wave Velocity Structure of the Sichuan‐Yunnan Region, China: Implications for Extrusion of Tibet Plateau and Seismic Activities

AbstractThe Sichuan‐Yunnan region is located at the intersection between the South China Block, the Indian plate, and the Tibet Plateau and is crisscrossed with deep and large faults and is characterized by strong seismic activities and the extrusion of the Tibetan Plateau. Here we employ 1‐year continuous waveforms of the vertical component of 89 broadband seismic stations using noise tomography in this region to evaluate the velocity structure and its implications. Through single station data preprocessing, cross‐correlation calculation, stacking, group velocity dispersion measurement, and quality evaluation, the group velocity dispersion curves of Rayleigh waves for the different periods were extracted in this area. We then use the surface wave tomography method to obtain the Rayleigh wave group velocity distribution of 9–40s. Finally, the S‐wave velocity structure in the depth range of 0–60 km is calculated by pure path dispersion inversion. The results show that a large‐scale low‐velocity anomaly in the lower crust runs through the Sichuan‐Yunnan rhombus block (SYRB) to Yangtze Block from west to east, which might correspond to the extrusion of the Tibetan Plateau or channel flow. On the other hand, the seismic activities are mainly concentrated at the western part of the region, with the earthquakes distributed at the boundary between the low‐ and high‐velocity structures, as well as the adjacent region, which we correlate with the extrusion of the Tibet Plateau.

Site Characterization of Swiss Strong-Motion Stations: The Benefit of Advanced Processing Algorithms

ABSTRACTSince 2009, 91 new strong-motion stations were built for the renewal of the Swiss Strong Motion Network. Another nine stations will be installed until 2022. For each new station, an extensive site characterization study is performed to model the 1D seismic-velocity profile and, for some sites, the liquefaction potential. Geophysical (passive and active surface-wave methods) and geotechnical cone penetration test (CPT) with additional pore-pressure measurement (CPTu) and seismic CPT (SCPT) methods are used. Analyzing the passive and active recordings with a variety of established and advanced methods, the fundamental frequency of the site, the polarization of the wavefield, the Love- and Rayleigh-wave phase-velocity dispersion curves, and the Rayleigh-wave ellipticity function are retrieved. The liquefaction potential is assessed using CPTu. SCPT measurements are sometimes used to determine the shallow underground structure. The benefits of the combination of different appropriate methods are shown for two examples—the borehole station SBUS in Buochs and the upcoming borehole station SCME in Collombey-Muraz. At both the sites, the CPTu measurements show an elevated liquefaction potential. Combining the passive and active data, the dispersion curves for Love and Rayleigh waves and Rayleigh-wave ellipticity curves are retrieved over a wide-frequency range and inverted for the S-wave velocity profile, in which the shallow part is constrained by the active or SCPT data, the intermediate part by the dispersion curves of the passive methods, and the deepest part by the ellipticity information. For Buochs, the 1D SH-wave amplification functions modeled for the velocity profiles are compared with the empirical amplification for earthquake recordings. Finally, an overview of the site characterization results for 52 of the newly installed seismic stations is given.

Extending the formulation of the spatial autocorrelation (SPAC) method to strain, rotation and tilt

SUMMARYThe spatial autocorrelation (SPAC) method has been applied to ambient seismic noise measured by arrays of translational seismometers for inverting phase-velocity dispersion curves of Rayleigh or Love waves for shallow S-wave velocity structure. Recently, it is becoming possible to observe wave spatial gradients such as strain, rotation and tilt owing to the development of dense seismic networks and improving measurement technologies. Therefore, it is desirable to extend the formulation of the SPAC method to strain, rotation and tilt. This study presents analytical expressions of cross-spectra and coherence of the strain, rotation and tilt components that are measured on the free surface. According to the results, both Rayleigh and Love waves contribute to most components of strains. The exceptions are the areal strain and the vertical axial strain (ezz) on the free surface that are affected by only Rayleigh waves. Only Rayleigh waves contribute to the tilts and rotations around the horizontal axes on the free surface, too. On the other hand, only Love waves contribute to the rotation around the vertical axis. Therefore, different kinds of wave spatial gradients are helpful to separate Rayleigh and Love waves correctly. For practical applications, the analytical expression for the radial axial strain (err) component will be applied directly to distributed acoustic sensing data measured with straight sections of a fibre-optic cable. On the other hand, dense observations of rotation and tilt may still be difficult to carry out at present. However, an application of analytical formulations in this study to arrays of at least several three-component rotational seismometers is attractive because it enables us to separately estimate the phase velocities of Rayleigh and Love waves.

Rayleigh Wave Dispersion Curve Inversion with the Artificial Bee Colony Algorithm

Rayleigh wave dispersion curve inversion is a non-linear iterative optimization process with multi-parameter and multi-extrema. It is difficult to carry out inversion and reconstruction of stratigraphic parameters quickly and accurately with a single linear or non-linear inversion for the data processing of Rayleigh waves with complex seismic geological conditions. We proposed a new method that combines artificial bee colony algorithm (ABC) and damped least squares algorithm (DLS) to invert Rayleigh wave dispersion curve. First, food sources are initialized in a large scale of the model based on the prior geological information. Then, after three kinds of bee operators (employed bees, onlooker bees and scout bees) transform each other and perform search optimization with several iterations, the targets are converged near the optimal solution to obtain an initial S-wave velocity model. Finally, the final S-wave velocity model is obtained by local optimization of DLS inversion with fast convergence and strong stability. The correctness of the method has been verified by one high-velocity interlayer model, and it was further applied to a real Rayleigh wave dataset. The results show that our method not only absorbs the advantages of ABC global search optimization and strong adaptability, but also makes full use of the advantages of DLS inversion, such as high accuracy and fast convergence speed. The inversion strategy can effectively suppress the inversion falling into local extrema, get rid of the dependence on an initial model, enhance the inversion stability, further improve the convergence speed and inversion accuracy, while has good anti-noise ability.

The Community Velocity Model V.1.0 of Southwest China, Constructed from Joint Body- and Surface-Wave Travel-Time Tomography

Abstract Southwest China, located at the southeastern margin of the Tibetan plateau, plays an important role for the plateau growth and its material extrusion. It has complicated tectonic environment and strong seismic activities including the 2008 Wenchuan great earthquake. Numerous geophysical studies have been conducted in southwest China. However, a community velocity model (CVM) in this region is still not available, which makes it difficult to have a consistent catalog of earthquake locations and focal mechanisms and a consistent velocity model for simulating strong ground motions and evaluating earthquake hazards. In this study, we aim at building a high-resolution CVM (both VP and VS) of the crust and uppermost mantle in southwest China along with earthquake locations by joint inversion of body- and surface-wave travel-time data. In total, we have assembled 386,958 P- and 372,662 S-wave first arrival times and nearly 8100 Rayleigh-wave dispersion curves in the period band of 5–50 s. A multigrid strategy is adopted in the joint inversion. A coarser horizontal grid interval of 0.5° is first used and then a finer grid interval of 0.25° is used with initial models interpolated from the coarser-grid inverted velocity models. The spatial resolution of both VP and VS models can reach up to 0.5° horizontally and 10 km vertically according to the checkerboard tests. The comparisons of our inverted VP and VS models with those from other studies show general consistency in large-scale features. The inverted models are further validated by P-wave arrival times from active sources and Rayleigh-wave data. In general, our velocity models show two low-velocity zones in the middle-lower crust and a prominent high-velocity region in between them. Our new models have been served as the first version of the CVM in southwest China (SWChinaCVM-1.0) for future studies.

Multi-method site characterization to verify the hard rock (Site Class A) assumption at 25 seismograph stations across Eastern Canada

Site characterization is a crucial component in assessing seismic hazard, typically involving in situ shear-wave velocity ( VS) depth profiling, and measurement of site amplification including site period. Noninvasive methods are ideal for soil sites and become challenging in terms of field logistics and interpretation in more complex geologic settings including rock sites. Multiple noninvasive active- and passive-seismic techniques are applied at 25 seismograph stations across Eastern Canada. It is typically assumed that these stations are installed on hard rock. We investigate which site characterization methods are suitable at rock sites as well as confirm the hard rock assumption by providing VS profiles. Active-source compression-wave refraction and surface wave array techniques consistently provide velocity measurements at rock sites; passive-source array testing is less consistent but it is our most suitable method in constraining the rock VS. Bayesian inversion of Rayleigh wave dispersion curves provides quantitative uncertainty in the rock VS. We succeed in estimating rock VS at 16 stations, with constrained rock VS estimates at 7 stations that are consistent with previous estimates for Precambrian and Paleozoic rock types. The National Building Code of Canada uses solely the time-averaged shear-wave velocity of the upper 30 m ( VS30) to classify rock sites. We determine a mean VS30 of ∼ 1600 m/s for 16 Eastern Canada stations; the hard rock assumption is correct (>1500 m/s) but not as hard as often assumed (∼2000 m/s). Mean variability in VS30 is ∼400 m/s and can lead to softer rock classifications, in particular, for Paleozoic rock types with lower average rock VS near the hard/soft rock boundary. Microtremor and earthquake horizontal-to-vertical spectral ratios are obtained and provide site period classifications as an alternative to VS30.