Multichannel Analysis Of Surface Waves Research Articles

Application of seismic refraction and MASW methods for investigating the Spillway Fault trace along the western side of the Aswan High Dam, Egypt

AbstractAn earthquake of local magnitude ML = 4.6 occurred on November 7, 2010, 4.5 km northwest of the Aswan High Dam on the Spillway Fault. In the Aswan metropolitan region this earthquake was felt intensely. As no surface rupture was found, the focal mechanism and the distribution of seismic activity was one of the tools used for finding fault dimensions. The composite fault-plane solutions for the observed events on the Spillway Fault showed a left lateral strike-slip faulting with normal-fault component striking NNW-SSE. Also, remote sensing techniques were applied for the detection and identification of the geomorphology and geometry of the Spillway Fault. In this research, sub-surface layers and structures are delineated utilizing near-surface seismic techniques. Furthermore, the area’s supposed path and position of the Spillway Fault are also investigated. Two active seismic techniques, Seismic Refraction and Multi-Channel Analysis of Surface Waves (MASW), are utilized for recording near-surface seismic wave data at 9 sites. The seismic refraction profiles are conducted as a 2D cross-section on the trace of the detected Spillway Fault in the study area to evaluate the maximum depth of penetration of the P-wave for fault investigation. The constructed 2D seismic and structural sections from P-wave results show that the obtained average depth of about 30 m. In addition, the estimated P-wave velocities extend from 600 m/s to over 6500 m/s. Some lateral variation in the seismic wave velocities in all layers may represent fault zones. Moreover, the 1D MASW technique is conducted to estimate the velocities of the shear wave for the upper 30 m (Vs30) to provide the site classes and soil characteristics along both sides of the detected Spillway Fault trace in the study area. The calculated Vs30 values emphasized the idea of the existence of a normal dip-slip fault trace which divides the study area into two different lithological parts. The first part is located on the eastern side and characterized by almost class B (hard rock, according to NEHRP classification), while the other part is located to the west, and shows almost class type C (denoted as dense soil and soft rock soil).

Urban subsurface exploration improved by denoising of virtual shot gathers from distributed acoustic sensing ambient noise

SUMMARY Ambient noise tomography on the basis of distributed acoustic sensing (DAS) deployed on existing telecommunication networks provides an opportunity to image the urban subsurface at regional scales and high-resolution. This capability has important implications in the assessment of the urban subsurface’s potential for sustainable and safe utilization, such as geothermal development. However, extracting coherent seismic signals from the DAS ambient wavefield in urban environments at low cost remains a challenge. One obstacle is the presence of complex sources of noise in urban environments, which may not be homogeneously distributed. Consequently, long recordings are required for the calculation of high-quality virtual shot gathers, which necessitates significant time and computational cost. In this paper, we present the analysis of 15 d of DAS data recorded on a pre-existing fibre optic cable (dark fibres), running along an 11-km-long major road in urban Berlin (Germany), hosting heavy traffic including vehicles and trains. To retrieve virtual shot gathers, we apply interferometric analysis based on the cross-correlation approach where we exclude low-quality virtual shot gathers to increase the signal-to-noise ratio of the stacked gathers. Moreover, we modify the conventional ambient noise interferometry workflow by incorporating a coherence-based enhancement approach designed for wavefield data recorded with large-N arrays. We then conduct multichannel analysis of surface waves to retrieve 1-D velocity models for two exemplary fibre subsegments, and compare the results of the conventional and modified workflows. The resulting 1-D velocity models correspond well with available lithology information. The modified workflow yields improved dispersion spectra, particularly in the low-frequency band (<1 Hz) of the signal. This leads to an increased investigation depth along with lower uncertainties in the inversion result. Additionally, these improved results were achieved using significantly less data than required using conventional approaches, thus opening the opportunity for shortening required acquisition times and accordingly lowering costs.

Critical speed of ballasted railway tracks: Influence of ballast and subgrade degradation

Track substructure layers such as ballast and subgrade involve progressive degradation with time in relation to the loading history. Degradation of track components directly influences the dynamic track response including the displacements and stresses. Determining the influence of real-world substructure degradation problems such as particle breakage, ballast fouling and mud pumping on the critical speed of a given track is essential to design ballasted tracks for high-speed passenger and freight trains. In this paper, a coupled rheological-continuum model is developed to predict the track dynamic response for different train speeds and axle loads. In this novel approach, field dispersion curves obtained from MASW (Multichannel Analysis of Surface Waves) testing can be adopted along with the proposed analytical model to predict the critical speed of track as well as the corresponding dynamic stress state in the substructure layers. Analytical modelling shows that problems such as ballast fouling and mud pumping lead to reduction in the computed critical speed, while also amplifying the dynamic stress response at lower train speeds. The influence of substructure degradation is found to be more prominent for heavy-haul (freight) trains imparting higher axle loads, when compared to passenger trains. Practical insights highlighting the influence of track improvements such as placing a thicker ballast layer and the addition of a capping layer on the critical speed are presented in this study with the objective of rejuvenating future track design.

DAS for 2-D MASW imaging: a case study on the benefits of flexible subarray processing

SUMMARY Distributed acoustic sensing (DAS) is a relatively new technology for recording the propagation of seismic waves, with promising applications in both engineering and geophysics. DAS's ability to simultaneously collect high spatial resolution waveforms over long arrays suggests that it is well-suited for near-surface imaging applications such as 2-D multichannel analysis of surface waves (MASWs), which require, at a minimum, long, linear arrays of single-component receivers. The 2-D MASW method uses a large number of sensor subarrays deployed along a linear alignment to produce 1-D shear-wave velocity (VS) profiles beneath each subarray. The 1-D VS profiles are then combined to form a pseudo-2-D VS image beneath the entire linear alignment that can be used for the purpose of identifying and characterizing lateral variations in subsurface layering. Traditionally, 2-D MASW is conducted using arrays consisting of either 24 or 48 geophones. While additional receivers could easily be incorporated into the testing configuration, it is rare for researchers and practitioners to have access to greater numbers of seismographs and geophones. When a limited number of geophones are available for deployment, there is a need to pre-determine the geophone spacing and subarray length prior to field data acquisition. Studies examining how the choice of subarray geometry impacts the resulting pseudo-2-D VS cross-sections have been largely limited to synthetic data. In response, this study utilizes DAS data to examine the effects of using various subarray lengths by comparing pseudo-2-D VS cross-sections derived from active-source waveforms collected at a well-characterized field site. DAS is particularly useful for 2-D MASW applications because the subarray geometry does not need to be determined prior to field data acquisition. We organize the DAS waveforms into multiple sets of overlapping MASW subarrays of differing lengths, ranging from 11 to 47 m, along the same alignment, allowing for direct comparison of the derived pseudo-2-D VS results at the site. We show that the length of the individual MASW subarrays has a significant effect on the resulting VS cross-sections, including the resolved location of a strong impedance contrasts at our study site, and evaluate the results relative to ground truth from invasive testing. Our results suggest that the choice of subarray length is important and should be carefully chosen to meet project-specific goals. Furthermore, analysts may consider using multiple subarray geometries during the data processing stage, as is made possible by DAS, to properly evaluate the uncertainty of 2-D MASW results. This study demonstrates the potential of using DAS to collect data for 2-D MASW in a manner that is efficient and flexible, and can be easily scaled up for use with very long arrays.

Multimode Rayleigh wave dispersion spectrum inversion using Wasserstein distance coupled with Bayesian optimization

We develop a new automatic framework for the nondestructive multichannel analysis of surface waves that combines multimode dispersion spectrum matching and a finite-element method (FEM)-based inversion to enhance the accuracy of subsurface profiling in site investigation activities. This framework eliminates the need for manual identification of the Rayleigh wave energy component and multimode assignment, reducing dependence on operator experience and judgment. The dispersion spectrum is generated through an FEM model that simulates 2D seismic wave propagation, taking into account the actual acquisition layout and lateral variations in the subsurface. We introduce the Wasserstein distance (WD) for evaluating the difference between the observed and simulated spectra and incorporate Bayesian optimization for efficiently inverting S-wave velocity profiles. The effectiveness of our framework is demonstrated through synthetic data examples, and the superiority of the WD-based objective function is illustrated by comparing it with the conventional mean square error-based objective function. Subsequently, we conduct a field test on a reclaimed landfill to validate our framework. This test confirms the ability of the framework to retrieve multimode Rayleigh waves and demonstrates its effectiveness in providing high-resolution S-wave profiles of the shallow subsurface.

The Combination of Hvsr and Masw Methods with Landsat 8 Imagery to Assess the Changing Shoreline along the Coastal Area of Central Bengkulu

The Central Bengkulu Regency possesses a coastline measuring 21.8 km, situated in direct proximity to the Indian Ocean. The heightened wave and ocean current dynamics possess the capacity to induce detrimental effects in the form of coastal abrasion along the coastline. This study conducted an examination of the rate of shoreline changes resulting from coastal abrasion in Central Bengkulu Regency, Bengkulu, Indonesia. Horizontal-to-vertical spectral ratio (HVSR) analysis, multichannel analysis of surface waves (MASW), and Landsat-8 remote sensing were all used in the current investigation. The project gets started with conducting field investigations and measurements of geophysical techniques, including the collection of Landsat-8 satellite imagery spanning the period from 1990 to 2020. Additionally, an examination was conducted on the rate at which the shoreline undergoes changes in velocity. In order to determine the increase in change that occurs along coastlines over a period of several decades, a study was carried out during which Landsat-8 satellite images were analyzed. This study investigates the application of the HVSR technique for assessing the seismic vulnerability of the ground and, additionally, the MASW technique for measuring the shear wave velocity of the coastline’s soil. Both of these methodologies are compared and contrasted with one another in this research. The findings indicated that the mean pace of coastline change in Central Bengkulu Regency was 1.5 m/yr, with the maximum velocity recorded at 4.1 m/yr. This high velocity of shoreline change is correlated with the Vs30 value of MASW measurement and Kg of HVSR measurement, where the subsurface soil structure along the coast of Central Bengkulu Regency from Vs30 measurement shows that it is dominated by stiff soil structure that is susceptible to erosion. Outcomes from the study can inform decision-making processes about safeguards and preventative measures to prevent further coastal degradation. HIGHLIGHTS In this paper, we present a framework using application passive and active seismic method with Landsat 8 for knowing the changing of shoreline coastal area in Central Bengkulu Indonesia This study demonstrated that the high velocity of the shifting shoreline is correlated with Vs30 and Kg values The subsurface soil structure is predominantly composed of stiff soil, and the changing shoreline starts at 1.5 mm/yr, which makes the coast of Central Bengkulu vulnerable to erosion GRAPHICAL ABSTRACT

Mapping Permafrost Variability and Degradation Using Seismic Surface Waves, Electrical Resistivity, and Temperature Sensing: A Case Study in Arctic Alaska

AbstractSubsurface processes significantly influence surface dynamics in permafrost regions, necessitating utilizing diverse geophysical methods to reliably constrain permafrost characteristics. This research uses multiple geophysical techniques to explore the spatial variability of permafrost in undisturbed tundra and its degradation in disturbed tundra in Utqiaġvik, Alaska. Here, we integrate multiple quantitative techniques, including multichannel analysis of surface waves (MASW), electrical resistivity tomography (ERT), and ground temperature sensing, to study heterogeneity in permafrost’s geophysical characteristics. MASW results reveal active layer shear wave velocities (Vs) between 240 and 370 m/s, and permafrost Vs between 450 and 1,700 m/s, typically showing a low‐high‐low velocity pattern. Additionally, we find an inverse relationship between in situ Vs and ground temperature measurements. The Vs profiles along with electrical resistivity profiles reveal cryostructures such as cryopeg and ice‐rich zones in the permafrost layer. The integrated results of MASW and ERT provide valuable information for characterizing permafrost heterogeneity and cryostructure. Corroboration of these geophysical observations with permafrost core samples’ stratigraphies and salinity measurements further validates these findings. This combination of geophysical and temperature sensing methods along with permafrost core sampling confirms a robust approach for assessing permafrost’s spatial variability in coastal environments. Our results also indicate that civil infrastructure systems such as gravel roads and pile foundations affect permafrost by thickening the active layer, lowering the Vs, and reducing heterogeneity. We show how the resulting Vs profiles can be used to estimate key parameters for designing buildings in permafrost regions and maintaining existing infrastructure in polar regions.

Physico-mechanical Properties Estimation of Upper Siwalik Sandstone using Field (MASW) and Laboratory Test, Himachal Himalaya, India

Abstract A study on the Upper Siwalik Sandstone was conducted to determine and compare the relationship between shear wave velocity and the petro-physical and petro-mechanical characteristics of the sandstone. Two localities in the Himachal Himalaya’s Bilaspur district were sampled for collection of sandstone of Upper Siwalik. The method of Multichannel Analysis of Surface Waves (MASW) was used to obtain average shear wave velocity at 30m depth (Vs30) in the field. The shear modulus of rocks is intimately correlated with the Vs30 parameter. The Vs30 value is 185 m/s for the Majher Khad (sandstone A) region and 366 m/s for the Dharot region (sandstone B). Based on obtained Vs30 values these two regions are classified under class D and class C respectively by the National Earthquake Hazards Reduction Program (NEHRP). Both the rocks belong to Upper Siwalik Sandstone, but diversity in Vs30 and shear modulus values can be ascribed to the composition of minerals, the size of the grains, and the cementing substances present in the rock.

MASW (Multichannel of Analysis of Surface Waves) Measurements on Very Dense Fill of Freeport Mining

The MASW (Multi-Channel Analysis of Surface Waves) was conducted on fill soil at Tembagapura Freeport Mining. The fill was very dense and is the landfills where people dumped waste disposal like car tire rubber etc. Several attempts were made to make boreholes to collect soil samples and to run SPT (Standard Penetration Test), but they failed. The fill was so dense that the employed drill bits were worn out when penetrating the soil. The MASW team was invited to carry out the measurements and to produce shear wave velocities of the layers, which correspond to SPT Number. The number of measured MASW points was 8 points. They were successfully carried out on the surface of the fill without borings. The offset distance between the hammer blows, and the first geophone was 18 m, and the interval distance between 4.5 Hz geophones was 3 m. The MASW measurements resulted in an average shear velocity of 400 m/s which confirmed the soil was very dense soil. The information regarding the shear wave velocities of the layers was adopted as input of earthquake engineering software to predict the amplification when the earthquake happens.

Method of automated extracting dispersion curves based on time-frequency distribution of seismic data

This paper discusses examples of testing a new implementation of the method of multi-channel surface wave analysis on synthetic data computed for elastic media with complex boundary geometry. The new implementation of the method includes developed algorithms for noise-resistant spectral analysis based on time-frequency domain filtering of seismograms and inversion of dispersion curves of phase velocities based on determination of ranges of possible transverse wave velocity models and application of artificial neural networks. Based on the results of synthetic data processing, the accuracy, lateral resolution limitations and applicability limits of the method under consideration are evaluated.

Novel techniques for in situ estimation of shear-wave velocity and damping ratio through MASW testing – I: a beamforming procedure for extracting Rayleigh-wave phase velocity and phase attenuation

SUMMARY A robust, in situ estimate of shear-wave velocity VS and the small-strain damping ratio DS (or equivalently, the quality factor QS) is crucial for the design of buildings and geotechnical systems subjected to vibrations or earthquake ground shaking. A promising technique for simultaneously obtaining both VS and DS relies on the Multichannel Analysis of Surface Waves (MASW) method. MASW can be used to extract the Rayleigh wave phase velocity and phase attenuation data from active-source seismic traces recorded along linear arrays. Then, these data can be inverted to obtain VS and DS profiles. This paper introduces two novel methodologies for extracting the phase velocity and attenuation data. These new approaches are based on an extension of the beamforming technique which can be combined with a modal filter to isolate different Rayleigh propagation modes. Thus, the techniques return reliable phase velocity and attenuation estimates even in the presence of a multimode wavefield, which is typical of complex stratigraphic conditions. The reliability and effectiveness of the proposed approaches are assessed on a suite of synthetic wavefields and on experimental data collected at the Garner Valley Downhole Array and Mirandola sites. The results reveal that, under proper modelling of wavefield conditions, accurate estimates of Rayleigh wave phase velocity and attenuation can be extracted from active-source MASW wavefields over a broad frequency range. Eventually, the estimation of soil mechanical parameters also requires a robust inversion procedure to map the experimental Rayleigh wave parameters into soil models describing VS and DS with depth. The simultaneous inversion of phase velocity and attenuation data is discussed in detail in the companion paper.

Novel techniques for in situ estimation of shear-wave velocity and damping ratio through MASW testing part II: a Monte Carlo algorithm for the joint inversion of phase velocity and phase attenuation

SUMMARY This paper deals with in situ characterization of the small-strain shear-wave velocity VS and damping ratio DS from an advanced interpretation of Multi-channel Analysis of Surface Waves (MASW) surveys. A new approach based on extracting Rayleigh wave data using the CFDBFa method has been discussed in the companion paper. This paper focuses on mapping the experimental Rayleigh wave phase velocity and attenuation into profiles of VS and DS versus depth, which is achieved through a joint inversion procedure. The joint inversion of phase velocity and attenuation data utilizes a newly developed Monte Carlo global search algorithm, which implements a smart sampling procedure. This scheme exploits the scaling properties of the solution of the Rayleigh eigenvalue problem to modify the trial earth models and improve the matching with the experimental data. Thus, a reliable result can be achieved with a limited number of trial ground models. The proposed algorithm is applied to the inversion of synthetic data and of experimental data collected at the Garner Valley Downhole Array site, as described in the companion paper. In general, inverted soil models exhibit well-defined VS profiles, whereas DS profiles are affected by larger uncertainties. Greater uncertainty in the inverted DS profiles is a direct result of higher variability in the experimental attenuation data, the limited wavelength range at which reliable values of attenuation parameters can be retrieved, and the sensitivity of attenuation data to both DS and VS. Nonetheless, the resulting inverted earth models agree well with alternative in situ estimates and geological data. The results stress the feasibility of retrieving both stiffness and attenuation parameters from active-source MASW testing and the effectiveness of extracting in situ damping ratio estimates from surface wave data.

Multi-parameters approach to assessment of soil liquefaction vulnerability in wetland areas of Lagos, Southwestern, Nigeria

With respect to geology, most coastal terrains are underlain by problematic soils, some of which are liquefiable in nature and may cause sudden failure of engineering infrastructures. Against this background, this study was carried out to investigate the subsurface geology of some Lagos coastal areas and their engineering implications using geophysical and geotechnical methods. To achieve this purpose, the Multichannel Analysis of Surface Waves, Cone Penetration Test, and Standard Penetration Test were deployed. Surface waves measurements were collected using a 24-channel seismograph to which 4.5 Hz twenty-four vertical geophones were connected via the takeouts of the two cable reels. CPT soundings were carried out with a 10-tons motorized cone penetrometer and boring with SPT were carried out as well. The results of the Multichannel Analysis of Surface Waves measurements showed that the shear waves velocity (Vs) ranges from 160 to 470 m/s. The very loose to loose sand delineated have Vs in the range from 170 to 250 m/s. The tip resistance and sleeve resistance values spanned between 4.0 and 72.0 kg/cm2 and 6.0–94 kg/cm2 respectively. The thickness of the liquefiable sands in the study area varied between 2.5 and 18.0 m. At Ikoyi site, owing to the prevalence of loose silty sand, corroborated by the available borehole data and the Liquefaction Potential Index, it is classified as having a high-risk liquefaction and could be responsible for the periodic damages to structural infrastructures such as roads and buildings. The sediments mapped at Okun-Ajah and Badore sites are mainly saturated loose sands with high likelihood to liquefaction with very-high to high risk severity. The study concludes that the presence of these sediments and other factors that could induce ground motion making the study sites potentially susceptible to liquefaction. Hence, an urgent attention must be given to early monitoring measures to address the trend.

An assessment of seismicity and near surface geophysical characteristics of potential solid waste landfill sites in the Eastern Black Sea Region of Türkiye.

This study aimed to assess the suitability of the potential solid waste landfill sites in seven provinces (Samsun, Ordu, Giresun, Trabzon, Gümüşhane, Bayburt and Artvin) in the Eastern Blacksea Region of Türkiye. The earthquake hazard analysis for two major earthquakes which occurred in the region was first carried out. Then, the geophysical methods including seismic refraction tomography (SRT), electrical resistivity tomography (ERT) and Multichannel Analysis of Surface Waves (MASW) were conducted to find out the structural and physical properties of the subsurface which include the layering, soil classification based on VS30 and the groundwater content at 25 locations of 13 in target provinces. The integrated interpretation of whole data sets demonstrates that Işıktepe, Esence, Çamburnu and Kazantaş which are characterized by VP > 1200m/s, VS30 ≥ 400m/s, ρ > 70 Ohm-m, low earthquake hazard and seismicity are more suitable among others. Vezirköprü, Şebinkarahisar, Yenice, Bayburt-Center, Balkaynak and Murgul will be suitable after a geotechnical reclamation due to moderate seismic velocities and electrical resistivity which are 900 < VP ≤ 1200m/s, 200 < VS30 < 400m/s and 10 < ρ ≤ 70 Ohm-m representing stiff and wet soils. In addition, Bafra, Ağalık and Ovacık were considered to be unsuitable due to the presence of thick, water-saturated soft soil and extremely weathered rocks. Finally, this study shows that the joint interpretation of seismicity and geophysical data in potential waste landfill sites, extremely important for the planning and development of a city, can provide the valuable information which will enable to prevent possible deformations, environmental problems and economic losses after waste landfill.

Some practical applications of shear wave velocity measurements in dense sand

Shear wave velocity (Vs) profiles were obtained using two techniques at a dense sand site in Blessington near Dublin, Ireland. It was shown that both the multichannel analysis of surface waves (MASW) and seismic CPT (SCPTU) techniques provided reliable data. Use was made of a novel approach involving a Monte Carlo inversion of the MASW output to assess the fit between the measured and theoretical surface wave data. Differences between the SCPTU and MASW data are likely to be due to a combination of natural anisotropy in the sand and to uncertainty in the two methods involved. Previous published correlations between CPTU data and Vs also work well for this site. The Vs data was also used to accurately predict (Class 3 prediction) measured settlement data from shallow footing tests at the site.

Automatic and adaptive picking of surface-wave dispersion curves for near-surface application

Multichannel analysis of surface waves (MASW) is a widely used non-invasive method to reveal the S-velocity structure in near-surface applications. Automatic and adaptive picking of surface wave dispersion curves is crucial for the later surface wave analysis. The traditional way to acquire the dispersion curves is to identify the local extremum energy in phase-velocity images and manually pick the dispersion curve by following peaks at different frequencies. However, the large number of interactive works in extensive surveys could be more efficient, time-consuming, and prone to human error. In this work, we developed an automatic adaptive picking of dispersion curves (AAPDC) strategy, which automatically searches the surface-wave dispersion curve based on the position of the local energy maxima in the dispersion spectrum. This method is straightforward and efficient and requires only a few or no additional parameters to obtain a stable result. The typical synthetic model tests show that the automatic picking agrees with the theoretical dispersion curves. In addition, the proposed AAPDC method is used to land geophone data and DAS data. The final S-velocity tomograms have a good agreement with the geological and other geophysics results, which demonstrate that the AAPDC method could accurately and adaptive extract fundamental dispersion curves from the complex dispersion spectrum.

A fused sampling method integrating geotechnical and geophysical data for assessing three-dimensional soil liquefaction-induced damage capacity

Combining intrusive geotechnical site investigations with non-intrusive geophysical surveys is a cost-effective approach to producing data with varying levels of accuracy, uncertainty, and different spatial scales to better characterize the site's liquefaction properties. Moreover, the demand for three-dimensional (3D) subsurface models in geotechnical engineering is increasing, but the models contain uncertainties and spatial variability associated with the use of relevant stochastic and geostatistical methods, and it remains a challenging task to obtain reliable liquefaction assessment results and the corresponding damage capacity. This study proposes a data-driven and non-parametric form of 3D multi-source fusion Bayesian compressive sampling (3D MSF-BCS) method for assessing 3D soil liquefaction-induced damage capacity. It consists of three main components: (i) 3D MSF-BCS fusing sparse geotechnical data (e.g., cone penetration test (CPT)) and geophysical data (e.g., multi-channel analysis of surface waves (MASW)) for 3D site modeling, (ii) quantifying the accuracy and uncertainty of 3D MSF-BCS, and (iii) Soil liquefaction-induced damage capacity analysis in 3D space. The method was applied to numerical examples and a real case study at the Cresselly Place site, and the results showed that the proposed method performs well.

Detection of Low-Velocity Layer Using Passive Surface-Wave Data and Deep Learning: An Application in The Urban Area of Hangzhou, China

Passive surface-wave methods using dense seismic arrays have gained growing attention in near-surface high-resolution imaging in urban environments. Deep learning (DL) can release a tremendous workload brought by dense seismic arrays. We presented a case study of shear-wave velocity (Vs) structure imaging in the Hangzhou urban area (eastern China) using DL inversion. Noise data were recorded by dense linear arrays with approximately 5 m spacing deployed along two crossing roads for investigating the top 80 m of the subsurface. Phase-velocity dispersion curves are extracted from virtual shot gathers using multichannel analysis of surface waves. We divided the area where the low-velocity layer (LVL) may exist into three layers with a thickness of 5 m. We gave the four layers weak constraints to generate training dataset and adopted a convolutional neural network to directly invert fundamental-mode Rayleigh-wave phase velocity for 1D Vs models. To improve the accuracy, we further applied the sensitivities to weight the loss function in DL inversion. The obtained pseudo-2D Vs profiles correspond to the velocities estimated from logging data and previous survey. The well-trained neural network successfully identified that the LVL is located at 50-60 m deep. And this network was also achieved accurately the inversion of a dense seismic network nearby. The results of this survey demonstrate the accuracy and efficiency of delineating near-surface structures from traffic-induced noise using the DL technique, which has great potential for monitoring subsurface changes in urban areas.

Prediction of S‐wave velocity models from surface waves using deep learning

AbstractSurface wave (SW) methods extract dispersion properties of wavefields propagating through a seismic array (1D or 2D). This is achieved by analysing the phase velocity versus frequency (or wavelength) data. Afterwards, an inversion process is performed to construct near‐surface S‐wave velocity models. Among the SW methods, multichannel analysis of SWs (MASW) is commonly used for engineering applications, analysing dispersion characteristics by generating a dispersion image. However, classical MASW depends on the manual picking of dispersion curves, which can lead to subjective outcomes and require time and effort to obtain precise results. To avoid these pitfalls, many studies, including deep‐learning techniques, have focused on automating the process. Similarly, we propose a deep‐learning‐based algorithm that estimates the S‐wave velocity directly from the dispersion image of SWs. This algorithm consists of a convolutional neural network (CNN) designed to directly yield S‐wave velocity profiles and a fully connected network (multi‐layer perceptron) added to regularize predictions. Unlike typical SW techniques, the proposed approach does not incorporate prior information such as layer count and thickness. To ensure successful training, we modified the loss function to exploit the normalized mean squared error. The training dataset was generated by modelling synthetic shot gathers and transforming them into dispersion images for various 1D stratified velocity structures. After a sample is fed to the CNN network for inversion, the inversion network's output subsequently goes through an additional simple neural network (NN) to regularize the predicted S‐wave velocity model (which is the post‐processing step). The combined usage of deep‐learning‐based SW inversion with NN‐based post‐processing was assessed using test data. The proposed algorithm achieved an average relative error of approximately 7.49% in predicting the S‐wave velocity and was successfully applied to the field data. Additionally, we discuss its performance on noisy data as well as its applicability to out‐of‐training data. Numerical examples demonstrated that the proposed method is robust to noise, whereas it requires additional training to handle data beyond the distribution of the training data.

Geophysical and Geochemical Pilot Study to Characterize the Dam Foundation Rock and Source of Seepage in Part of Pensacola Dam in Oklahoma

Pensacola Dam, operated by the Grand River Dam Authority (GRDA), is a multiple-arch buttress dam constructed in 1940. The dam has little or no existing geophysical reports on the integrity of the dam foundation rock and even less knowledge at depth. Visual inspection indicated evidence of seepage at some arches of the dam. As a pilot study, we conducted a suite of geophysical surveys inside two arches (Arch-16 and Arch-17) and a part of the downstream berm to characterize the dam foundation rock, delineate seepage zones, and identify the most appropriate geophysical methods for temporal monitoring of the dam’s conditions. The geophysical methods included electrical resistivity tomography (ERT), self-potential (SP), multichannel analysis of surface waves (MASW), compressional (P)-wave refraction, and shear (S)-wave reflection. Water samples were collected for geochemical analysis to investigate the source of the seepage flow inside Arch-16. The geophysical results characterized the dam foundation rock into an unsaturated limestone and chert overlying a water-saturated limestone and chert. The ERT profiles indicated that groundwater is rising inside the arches and significantly dropping under the downstream berm, which can be due to the uplift pressure beneath the dam base. Zones of high seepage potential were detected near the buttress walls of the two surveyed arches, which may be related to previous blasting, excavation of the dam foundation, concrete placement, or improper grouting. The geochemical analysis of water samples taken from the artesian wells inside Arch-16 and the Grand Lake revealed different chemical compositions, suggesting that the source of water could be a mixture of groundwater and lake water or lake water interacting with rock and reaching the surface through fractures; however, more sampling and further analysis are required to ascertain the source of the seeps. This study showed that the ERT, SP, and S-wave reflection methods have effectively characterized the dam foundation rock and seepage zones beneath the arches. The study provided a better understanding of the conditions of the dam foundation rock, evaluated the utilized geophysical methods, and determined the optimum geophysical methods that can be used for the characterization and monitoring of the subsurface conditions along the entire length of the dam. In this study, we have demonstrated that the integration of effective geophysical surveys and geochemical analysis yielded optimum results in solving a complex dam safety problem. This strategy promotes the best practice for dam safety investigation.