Near-surface Velocity Structure Research Articles

Subsurface Imaging Using Interferometry of Distributed Acoustic Sensing Ambient Noise Measurement along a Dark Fiber Line: A Case Study in Downtown Reno, Nevada

ABSTRACT Distributed acoustic sensing (DAS) technology is an emerging field of seismic sensing that enables recording ambient noise seismic data along the entire length of a fiber-optic cable at meter-scale resolution. Such a dense spatial resolution of recordings over long distances has not been possible using traditional methods because of limited hardware resources and logistical concerns in an urban environment. The low spatial resolution of traditional passive seismic acquisition techniques has limited the accuracy of the previously generated velocity profiles in many important urban regions, including the Reno-area basin, to the top 100 m of the underlying subsurface. Applying the method of seismic interferometry to ambient noise strain rate data obtained from a dark-fiber cable allows for generating noise cross correlations, which can be used to infer shallow and deep subsurface properties and basin geometry. We gathered DAS ambient noise seismic data for this study using a 12 km portion of a dark-fiber line in Reno, Nevada. We used gathered data to generate and invert dispersion curves to estimate the near-surface shear-wave velocity structure. Comparing the generated velocity profiles with previous regional studies shows good agreement in determining the average depth to bedrock and velocity variations in the analyzed domain. A synthetic experiment is also performed to verify the proposed framework further and better understand the effect of the infrastructural cover along the cable. The results obtained from this research provide insight into the application of DAS using dark-fiber lines in subsurface characterization in urban environments. It also discusses the potential effects of the conduit that covers such permanent fiber installations on the produced inversion results.

3D near-surface P-wave velocity structure imaging with Distributed Acoustic Sensing and electric hammer source

Distributed Acoustic Sensing (DAS) is an emerging technique for ultra-dense seismic observation, which provides a new method for high-resolution sub-surface seismic imaging. Recently a large number of linear DAS arrays have been used for two-dimensional S-wave near-surface imaging in urban areas. In order to explore the feasibility of three-dimensional (3D) structure imaging using a DAS array, we carried out an active source experiment at the Beijing National Earth Observatory. We deployed a 1 ​km optical cable in a rectangular shape, and the optical cable was recast into 250 sensors with a channel spacing of 4 ​m. The DAS array clearly recorded the P, S and surface waves generated by a hammer source. The first-arrival P wave travel times were first picked with a Short-Term Average/Long-Term Average (STA/LTA) method and further manually checked. The P-wave signals recorded by the DAS are consistent with those recorded by the horizontal components of short-period seismometers. At shorter source-receiver distances, the picked P-wave arrivals from the DAS recording are consistent with vertical component recordings of seismometers, but they clearly lag behind the latter at greater distances. This is likely due to a combination of the signal-to-noise ratio and the polarization of the incoming wave. Then, we used the TomoDD software to invert the 3D P-wave velocity structure for the uppermost 50 ​m with a resolution of 10 ​m. The inverted P-wave velocity structures agree well with the S-wave velocity structure previously obtained through ambient noise tomography. Our study indicates the feasibility of 3D near-surface imaging with the active source and DAS array. However, the inverted absolute velocity values at large depths may be biased due to potential time shifts between the DAS recording and seismometer at large source-receiver distances.

Fireworks: A Potential Artificial Source for Imaging Near-Surface Structures

Abstract Seismic waves induced by incident acoustic waves from air disturbances can be used to image near-surface structures. In this article, we analyze seismic waveforms recorded by a dense array on the Xishancun landside in Li County, Sichuan Province, southwest China during the Lunar New Year’s Eve (27 January 2017). A total of eight event clusters have been identified as a result of firework explosions. For each cluster, which comprises dozens of individual events with high similarity, we manually pick arrival times of the first event recorded by the array and locate it with a grid-search method. We then rotate three-component waveforms of all events from the east, north, and vertical coordinate system to the local LQT coordinates (L, positive direction perpendicular to the landslide surface and pointing downwards; Q, positive direction is from the launch location of firework to the station along the landslide surface; T, perpendicular to the plane formed by the L and Q directions, and the selected positive direction of the T axis makes LQT form the left-hand coordinate system), and stack the LQT components for those events with cross-correlation values CC ≥ 0.8 with respect to the first event. Characteristics of the stacked LQT components are also examined. The particle motions at each station are retrograde ellipse in the frequency range of ∼5–50 Hz, suggesting air-coupled Rayleigh waves generated by the firework explosions. Spectrograms of the Rayleigh waves also show clear dispersions, which might be used to image near-surface velocity structures. Although we cannot directly extract the phase velocities due to the limitation of the seismic array, our study shows that the fireworks might provide a low-cost and easy-to-use seismic source for imaging near-surface structures.

Characteristic evaluation of passive seismic ellipticity method in urban shield tunnel

In recent years, engineering examples have shown that traditional surface-wave detection methods are easily limited in areas with small space and heavy traffic. The horizontal-to-vertical spectral ratio survey method has become increasingly prevalent in site measurements and is favored by geophysicists for its ability to detect near-surface velocity structures with greater sensitivity than phase velocities. Based on the phase difference method and polarization filtering, we proposed a passive seismic ellipticity method. The objective of this method is to extract the Rayleigh waves from ambient noise recordings and the analysis of ellipticity dispersion characteristic. This method was applied to an actual case study. Specifically, the velocity dispersion profile of the site is obtained using the active-source surface-wave method. Then, we compared the results obtained by the passive seismic ellipticity method with those obtained by the active-source surface-wave method and the field data, to evaluate the accuracy of results. The results demonstrate that the proposed method can effectively detect the location of subsurface shield tunnels and has the characteristics of simple data processing steps, less interference, and high stability of results. This demonstrates the necessity of using the phase difference method to select segments dominated by Rayleigh waves in ambient noise recordings and applying polarization filtering before calculating ellipticity. The paper provides an actual case study for the application and promotion of the passive seismic ellipticity method and has significant practical value and reference significance.

Seismic stereometry: an alternative two-station algorithm to seismic interferometry for analysing car-generated seismic signals

SUMMARY Human activities generate seismic waves, which have been traditionally analysed by seismic interferometry. However, this processing technique often neglects the seismic source distribution and is prone to introducing biases in interpretations. This study proposes an alternative processing technique known as seismic stereometry to analyse seismic signals generated by cars. The proposed algorithm exploits the highly coherent wavefields recorded by dense seismic arrays and directly measures the seismic wave traveltime differences between sensors. By doing so, it intrinsically considers the seismic source distribution. Traveltime differences can be used to invert the positions of vehicles and the near-surface velocity structures. We demonstrate the analysis using a dense seismic array deployed atop a southern San Andreas Fault segment and invert the shallow S-wave velocity using seismic waves generated by only one car. The velocity inversion result reveals a clear contrast across the fault, consistent with previous studies. The developed technique, combined with the distributed acoustic sensing technology, has great potential for applications in the urban environment.

An Envelope Travel-Time Objective Function for Reducing Source–Velocity Trade-Offs in Wave-Equation Tomography

In conventional cross-correlation (CC)-based wave-equation travel-time tomography, wrong source wavelets can result in inaccurate velocity inversion results, which is known as the source–velocity trade-off. In this study, an envelope travel-time objective function is developed for wave-equation tomography to alleviate the non-uniqueness and uncertainty due to wrong source wavelets. The envelope of a seismic signal helps reduce the waveform fluctuations/distortions caused by variations of the source time function. We show that for two seismic signals generated with different source wavelets, the travel-time shift calculated by cross-correlation of their envelopes is more accurate compared to that obtained by directly cross-correlating their waveforms. Then, the CC-based envelope travel-time (ET) objective function is introduced for wave-equation tomography. A new adjoint source has also been derived to calculate the sensitivity kernels. In the numerical inversion experiments, a synthetic example with cross-well survey is first given to show that compared to the traditional CC travel-time objective function, the ET objective function is relatively insensitive to source wavelet variations and can reconstruct the elastic velocity structures more reliably. Finally, the effectiveness and advantages of our method are verified by inversion of early arrivals in a practical seismic survey for recovering near-surface velocity structures.

Evaluation of the 3D Near-Surface Velocity Structure in an Urban Environment from Ambient Noise Array Tomography: The Case of the City of Thessaloniki (Northern Greece)

Abstract We examine the implementation of ambient noise array tomography in an urban environment to assess the 3D near-surface shear wave velocity (VS) structure at an intermediate spatial scale (∼1 km2, depth range 200–300 m). The application employs cross correlation traces of vertical component ambient noise recordings from a local network installed in Thessaloniki city (Northern Greece), allowing the determination of Rayleigh wave travel times for the frequency range of 1.5–14 Hz. The results confirm the presence of a complex subsurface with strong lateral variations in the geology, with travel times varying up to almost one order of magnitude. A surface wave travel time tomography approach was applied for each frequency to determine the spatial variability of the group velocity, involving the use of approximate Fresnel volumes, as well as damping and spatial smoothing constraints to stabilize the results. We also employed an interfrequency smoothing scheme to obtain smooth but data-compatible dispersion curves at the cost of inverting all travel time data simultaneously. Following the application of several quality cutoff criteria, we reconstructed local group slowness dispersion curves for a predefined tomographic grid in the study area. The final 3D velocity model was determined by a modified Monte Carlo inversion of these dispersion curves and the spatial integration of the obtained 1D VS profiles. Different model parameterizations were tested for the inversion to determine the optimal datafit. The final 3D velocity model is in a very good agreement with the local geology, previous larger scale studies, and other geophysical surveys, providing additional structural constraints (such as hidden fault identification) for the complex sedimentary deposits and bedrock formation in Thessaloniki, up to the depth of ∼250–300 m. The introduction of the aforementioned modifications to the ambient noise array tomography suggests that it can be efficiently adjusted and employed as a reliable tool for imaging the 3D seismic structure in urban environments with complex geology.

Curvelet-Based Joint Waveform and Envelope Inversion of Early-Arrival Imaging Shallow Geological Structure

Abstract Near-surface imaging structures often plays a significant role in the field of environmental and engineering geophysics. Early-arrival waveform inversion (EWI) is state-of-the-art method to imaging near-surface structures due to its high resolution. However, the method faces with cycle-skipping issue which might lead to an unexpected local minimum. Envelope inversion (EI) could deal with this issue which contributes to the ultralow-frequency information extracted from the envelope but has a low resolution. We have developed a curvelet-based joint waveform and envelope inversion (CJWEI) method for inverting imaging near-surface velocity structures. By inverting two types of data, we are able to recover the low- and high-wavenumber structures and mitigate the cycle-skipping problem. Curvelet transform was used to decompose seismic data into different scales and provide a multiscale inversion strategy to further reduce non-uniqueness of waveform inversion efficiently. With synthetic test and real data application, we demonstrate that our method can constrain the anomalies and hidden layers in the shallow structure more efficiently as well as is robust in terms of noise. The proposed multiscale joint inversion offers a computational efficiency and high precision to imaging fine-scale shallow underground structures.

Geometrical-Feature-Preserving Adjoint Tomography of Near-Surface Structure with Seismic Early Arrival

Early arrival waveform inversion (EWI) is an essential approach to obtaining velocity structures in near-surface. Due to suffering from a cycle‐skipping issue, it is difficult to reach the global minima for conventional EWI with the misfit function of least-squares norm (L2‐norm). Following the optimal transportation theory, we developed an EWI solution with a new objective function based on quadratic‐Wasserstein‐metric (W2-norm) to maintain the geometric characteristics of the distribution and improve the stability and convexity of the inverse problem. First, we gave the continuous form of the adjoint source and the Frechet gradient of the Wasserstein metric for seismic early arrival, which leads to an easy and efficient way to implement in the adjoint-state method. Then, we conducted two synthetic experiments on the target model containing some velocity anomalies and hidden layers to test its effectiveness in mapping accurate and high-resolution near-surface velocity structure. The results show that the W2-normed EWI can mitigate cycle-skipping issues compared with the L2-normed EWI. In addition, it can deal with hidden layers and is robust in terms of noise. The application to a real dataset indicates that this new solution can recover more details in the shallow structure, especially in the aspect of dealing with hidden layers.

Metallic mineral exploration by using ambient noise tomography in Ashele copper mine, Xinjiang, China

Rapid advances in the seismic exploration method have allowed its application in metallic mineral exploration. However, 2D seismic profiles are often insufficient to describe the shape and areal extent of ore-bearing rock masses away from survey lines. Although more complete, collecting 3D seismic data is expensive, time consuming, and may require considerable investment in surface access. The combination of ambient noise tomography and 2D seismic reflection exploration methods can produce acceptable results relatively quickly and at a low cost. The enormous Ashele copper deposit in northwest China is a typical deposit formed by volcanic eruption. It is rich in resources and possesses good prospecting potential in its deeper and peripheral areas. We performed ambient noise tomography to investigate a near-surface 3D S-wave velocity ([Formula: see text]) structure above a depth of 0.7 km in the Ashele mining area (approximately 8 × 12 km) using 25 days of continuous ambient noise data. From the combined interpretation of the 3D [Formula: see text] structure and the existing 2D seismic reflection profile, we infer that there may be ore-bearing rock masses in the western and northern sides of the research area. We report the discovery of an ancient volcano at a depth of 500 m on the western side of this region. The banded velocity anomalies and the existence of the ancient volcano signify the formation process of a bimodal volcanic rock association. It has been proven that the combination of ambient noise tomography and 2D seismic reflection exploration methods can produce important results in metallic mineral exploration. Therefore, ambient noise tomography can be used as an economical, convenient, and efficient method for future explorations, complementing the 2D seismic reflection exploration method.

重合前バイブロサイス記録を用いたノイズ除去と表層付近の速度の推定

We develop signal processing and imaging techniques for characterizing subsurface structure with utilizing raw vibroseis shot data before sweep correction. Vibroseis shots are often used for a land seismic survey, and the raw data of observation are typically converted to impulse-shot records with correlation of shot sweep and stacking. However, as we demonstrated here, the raw data are useful for providing additional valuable information. One opportunity we have is to clean up the vibroseis shot gathers by removing traffic noise in the raw data. Traffic noise is one of the strongest kinds of noise in the frequency range overlapped to the vibroseismic shots, and this noise contaminates the shot gathers. Diversity stacking helps to improve the signal-to-noise ratio （SNR）, but we develop a more advanced, and traffic-noise-oriented, filter with a machine-learning approach. This filter improves the SNR of shot gathers. Another opportunity is for near-surface velocity structure modeling. Near surface is important to know for topography correction of imaging （static collection） and shot and/or receiver couplings. However, the conventional vibroseismic shot geometry is not suitable to estimate these structures. We use ambient noise data recorded during the vibroseismic shot survey. Each sweep shot is 38 seconds and more than 10 sweep shots are repeated at each shot location. This means that we have 380 seconds of continuous data at each location. We use these data to extract surface waves using seismic interferometry, and estimate near-surface S-wave velocities from the surface waves. The velocity image provides detailed information of the structure at top 50 m along the entire survey.

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.

A high-resolution dispersion imaging method of seismic surface waves based on chirplet transform

Abstract The surface-wave analysis method is widely adopted to build a near-surface shear-wave velocity structure. Reliable dispersion imaging results form the basis for subsequent picking and inversion of dispersion curves. In this paper, we present a high-resolution dispersion imaging method (CSFK) of seismic surface waves based on chirplet transform (CT). CT introduces the concept of chirp rate, which could focus surface-wave dispersion energy well in time-frequency domain. First, each seismic trace in time-distance domain is transformed to time-frequency domain by CT. Thus, for each common frequency gather, we obtain a series of 2D complex-valued functions of time and distance, which are called pseudo-seismograms. Then, we scan a series of group velocities to obtain the slanting-phase function and perform a spatial Fourier transform on the slanting-phase function to get its amplitude. In addition, power operation is adopted to increase the amplitude difference between dispersion energy and noise. Finally, we generate the dispersion image by searching for the maximum amplitude of a slanting-phase function. Because the CSFK method considers the position of surface-wave energy in the time-frequency domain, this largely eliminates the noise interference from other time locations and improves the resolution and signal-to-noise ratio of the dispersion image. The results of synthetic test and field dataset processing demonstrate the effectiveness of the proposed method. In addition, we invert all 120 sets of dispersion curves extracted from reflected wave seismic data acquired for petroleum prospecting. The one-dimensional inversion shear-wave velocity models are interpolated into a two-dimensional profile of shear-wave velocity, which is in good agreement with the borehole data.

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.

Shallow Shear-Wave Velocity Structure beneath the West Lake Area in Hangzhou, China, from Ambient-Noise Tomography

Urban geophysical exploration plays an important role in the sustainable development of and the mitigation of geological hazards in metropolitan areas. However, it is not suitable to implement active seismic methods in densely populated urban areas. The rapidly developing ambient-noise tomography (ANT) method is a promising technique for imaging the near-surface seismic velocity structure. We selected the West Lake area of the city of Hangzhou as a case study to probe the shallow subsurface shear-wave velocity (Vs) structure using ANT. We conducted seismic interferometry on the ambient-noise data recorded by 28 seismograph stations during a time period of 17 days. Fundamental-mode Rayleigh-wave group- and phase-velocity dispersion data were measured from cross-correlation functions and then inverted for a 3D Vs model of the uppermost 1 km that covers an area of about 7 km × 8 km. The tomographic results reveal two prominent anomalies, with high velocities in the southwest and low velocities in the northeast. The fast anomaly corresponds to the presence of limestone and sandstone, whereas the slow anomaly is due to the relatively low-velocity rhyolite and volcanic tuff in the area. The boundary between the two anomalies lies to the NE of an NW–SE trending fault, indicating that the fault dips toward the NE. In addition, the pronounced low-velocity anomalies appear under the Baoshi mountain, likely due to the thick rhyolite and volcanic tuff beneath the extinct volcano. Our results correlate well with regional geological features and suggest that ANT could be a promising technique for facilitating the exploration of urban underground space.

Automatic picking of multi-mode surface-wave dispersion curves based on machine learning clustering methods

The surface-wave analysis method is widely adopted to build near-surface shear-wave velocity structure. Automatic picking of surface-wave dispersion curves is a problem that needs to be solved, especially when dealing with a large amount of data. In this paper, we proposed an automatic picking method of multi-mode surface-wave dispersion curves based on unsupervised machine learning methods. Firstly, seismic data is transformed to two-dimensional dispersion image by dispersion imaging method. The discrete dispersion image points are separated into two clusters: dispersion energy and background noise by Gaussian mixture model clustering method. Then the dispersion energy points are projected into frequency-velocity domain, and are distinguished as different surface-wave modes by the density-based spatial clustering of applications with noise algorithm. Finally, multi-mode dispersion curves are obtained by searching for the local peaks in different mode areas of surface waves. Particle filter is used to smooth the picked dispersion curves to eliminate the influence of noise. The synthetic tests show that the automatically picked dispersion curves can match the theoretical dispersion curves well. We also applied the proposed method to the picking of dispersion curves of two field data. The automatically picked dispersion curves are applied to the subsequent inversion. In the second field data, the one-dimensional inversion results are interpolated to obtain the near-surface three-dimensional velocity model of the work area. The inversion results are in good agreement with borehole data, which further proves the accuracy and efficiency of the automatic picking method for multi-mode dispersion curves.

Spurious signals attenuation using SVD-based Wiener filter for near-surface ambient noise surface wave imaging

In recent years, high-frequency passive surface wave methods based on seismic interferometry have been applied to estimate near-surface shear wave velocity structure in urban geophysical investigations. One of key steps of using surface-wave methods is to image the dispersion energy and identify different modes of surface waves. In the dispersion image generated by multichannel analysis of passive surface waves method, however, a type of “crossed” artifacts usually overlaps and smears the true dispersion energy in a high frequency range. The “crossed” artifacts are spatial aliasing of a reverse-directional propagating wave with a directional velocity scan. In urban areas, the coherent noise signals could be repetitively induced by traffic in a short time segment, which will produce repetitive signals in the cross-correlation function, leading to spurious reverse-directional propagating waves in the causal or acausal part. We propose to use the Wiener filter based on singular value decomposition (SVD) to attenuate the spurious signals in the cross-correlation functions so as to reduce “crossed” artifacts in the dispersion image. A synthetic example demonstrates that the “crossed” artifacts related to spurious signals in the dispersion image can be well attenuated by applying the SVD-based Wiener filter (SVDWF) to cross-correlation functions. Two field examples suggest that high-mode dispersion energy in the dispersion images generated from the SVDWF denoised cross-correlation functions becomes more continuous and clearer in high frequency bands, which benefits from the advantages of both SVD and Wiener filters.

A generic soil velocity model that accounts for near-surface conditions and deeper geologic structure

Near-surface soil conditions can significantly alter the amplitude and frequency content of incoming ground motions – often with profound consequences for the built environment – and are thus important inputs to any ground-motion prediction. Previous soil-velocity models (SVM) have predicted shear-wave velocity profiles based on the time-averaged shear-wave velocity in the upper 30 m (VS30). This article presents a generic soil-velocity model that accounts both for near-surface conditions (VS30) and deeper geologic structure, as represented to the depth at which the profile reaches a velocity of 1.0 km/s (Z1.0). To demonstrate the advantages of our new SVM, we apply it to the Cascadia Region of North America, where numerous geologic basins and glaciated landscapes give rise to a wide range of VS30 and Z1.0 combinations. This soil velocity model yields good estimates of site response across all site conditions, and significantly improves upon a model calibrated using only VS30 data. In conjunction with existing models that describe the deep velocity structure of the region (e.g., (Stephenson et al., 2017) [27]; the proposed model is particularly suited for use in regional-scale predictions of site response, liquefaction, landslides, infrastructure damage, and loss. The proposed methodology is broadly applicable to the development of SVMs elsewhere, and with improved understanding of near-surface and deep velocity structures, can facilitate more accurate ground-motion predictions globally.

Refraction wavefield migration

Refraction methods are often applied to model and image near-surface velocity structures. However, near-surface imaging is very challenging, and no single method can resolve all of the land seismic problems across the world. In addition, deep interfaces are difficult to image from land reflection data due to the associated low signal-to-noise ratio. Following previous research, we have developed a refraction wavefield migration method for imaging shallow and deep interfaces via interferometry. Our method includes two steps: converting refractions into virtual reflection gathers and then applying a prestack depth migration method to produce interface images from the virtual reflection gathers. With a regular recording offset of approximately 3 km, this approach produces an image of a shallow interface within the top 1 km. If the recording offset is very long, the refractions may follow a deep path, and the result may reveal a deep interface. We determine several factors that affect the imaging results using synthetics. We also apply the novel method to one data set with regular recording offsets and another with far offsets; both cases produce sharp images, which are further verified by conventional reflection imaging. This method can be applied as a promising imaging tool when handling practical cases involving data with excessively weak or missing reflections but available refractions.

Single-station seismic microzonation using 6C measurements

Microzonation is one of the essential tools in seismology to mitigate earthquake damage by estimating the near-surface velocity structure and developing land usage plans and intelligent building design. The number of microzonation studies increased in the last few years as induced seismicity becomes more relevant, even in low-risk areas. While of vital importance, especially in densely populated cities, most of the traditional techniques suffer from different shortcomings. The microzonation technique presented here tries to reduce the existing ambiguity of the inversion results by the combination of single-station six-component (6C) measurements, including three translational and three rotational motions, and more traditional H/V techniques. By applying this new technique to a microzonation study in the downtown area of Munich (Germany) using an iXblue blueSeis-3A rotational motion sensor together with a Nanometrics Trillium Compact seismometer, we were able to estimate Love and Rayleigh wave dispersion curves. These curves together with H/V spectral ratios are then inverted to obtain P- and S-wave velocity profiles of the upper 100 m. In addition, there is a good correlation between the estimated velocity models and borehole-derived lithology, indicating the potential of this single-station microzonation approach.