Application of active-source surface waves in urban underground space detection: a case study of Rongcheng County, Hebei, China

Wang, GuangWen; Wang, Haiyan; Li, HongQiang; Lu, ZhanWu; Li, Wenhui; Xu, and TaiRan

doi:10.26464/epp2022039

Cited by 3 publications

(3 citation statements)

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“…In recent years, with the continuous progress and improvement of seismic methods, surface waves have been considered signals rather than noise (Socco et al, 2010;Boiero et al, 2011;Strobbia et al, 2011). Reasonable use of surface wave information from 3D seismic exploration data can help analyse near-surface formation structures (Wang et al, 2021;Jusoh et al, 2022;Wang et al, 2022) and can also be used for static computation (Socco et al, 2015) and surface wave simulation suppression (H. Qi, 2022;Yang & Wang, 2022) of later seismic data.…”

Section: Introductionmentioning

confidence: 99%

“…Geotechnical and environmental engineering studies have focused on characterizing the properties of shallow subsurface layers (Schuler, 2008; Cui et al., 2019; Da Col et al., 2022). Among them, the most important seismological parameter of the near surface is the shear wave velocity (Wang et al., 2022). The inherent characteristics of surface waves determine their ability to characterize the velocity of near‐surface shear waves (Socco & Strobbia, 2004; Xia et al., 2009).…”

Section: Introductionmentioning

confidence: 99%

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Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method

He,

Peng,

Geng

2024

Near Surface Geophysics

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Surface‐wave information from seismic data can be used for near‐surface analysis, static computation and noise suppression. The multichannel analysis of surface waves method is a useful approach for obtaining the shear wave velocity of the near surface; however, rapidly generating an image of dispersive energy in the presence of coherent noise is a challenge. In this study, we propose the imaging of the dispersive energy of the Rayleigh wave using a spatial smoothing propagation method. In this method, forward and backward spatial smoothing algorithms were used to restore the rank of the covariance matrix in strong coherent noise. Subsequently, an image of the dispersive energy was rapidly generated by the propagation method using a linear operation equivalent to the eigenvalue decomposition. The proposed method was evaluated using both synthetic and field data. The results showed that the method was easy to use and has higher resolution representation, efficiency and noise robustness compared with conventional methods.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method

He,

Peng,

Geng

2024

Near Surface Geophysics

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“…On this regards, multichannel analysis of surface waves (MASW) are widely used to measure the shear wave velocity (Vs) of near-surface materials as these methods are reliable, noninvasive, and low-cost procedures in engineering applications to identify potentially unsuitable geological conditions, determine small-strain stiffness of soil and rock, foundation instability analysis, and know site classes [14][15][16]. Rayleigh waves that propagate from the ground surface to subsurface are used to estimate Vs from the dispersion curve and thus the average shear wave velocity (Vs30) is estimated from the measured Vs to determine the site class for site response analysis, earthquake resistant design and safe building provision [17,18]. It is also an important geotechnical parameter to obtain the nearsurface dynamic properties of a soil which in turn is essential for the engineering design of a small to large projects such as roads, buildings, and highways.…”

Section: Introductionmentioning

confidence: 99%

Multichannel Analysis of Surface Waves (MASW) to Estimate the Shear Wave Velocity for Engineering Characterization of Soils at Hawassa Town, Southern Ethiopia

Ayele

Woldearegay

Meten

2022

International Journal of Geophysics

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Site characterization is a prerequisite for the successful and economic design of engineering structures and earthworks by providing geological information for any proposed project. Until now, no detail study has been carried out on the site characterization and classification using shear wave velocity (Vs) up to the top 30 m depth in Hawassa town. For this study, multichannel analysis of surface waves (MASW) was used to determine the variation of Vs for a proper civil engineering design in the town. In addition, vertical electrical sounding (VES) and standard penetration test (SPT) were employed to characterize the near-surface materials. The Vs30 map was prepared for Hawassa town using the estimated Vs30 values which ranges from 248.9 m/s to 371.3 m/s while the SPT-N values were ranges from 5bpf to 50bpf. The correlation of Vs and SPT-N values has been done by considering both corrected and uncorrected SPT-N values. The VES result showed that groundwater is found at a shallow depth. The correlation of Vs and SPT-N value was validated using regression model. The 1D Vs profile and 2D cross-section showed low Vs at a shallow depth. The near-surface soils of the town are classified based on the Vs30 as site class C (stiff soil and soft rock) and D class (stiff soils) according to the NEHRP (Natural Earthquake hazards Reduction Program) and as subsoil classes B and C according to the Eurocode 8. The geotechnical tests also showed that the soils in the study area are silty sand, sand and silty sand with some gravel. The low Vs values observed at a shallow depth should be given much attention during foundation design for the stability of civil engineering structures.

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Multimodal surface wave inversion with automatic differentiation

Liu,

Li,

et al. 2024

Geophysical Journal International

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Summary Investigating subsurface shear-wave velocity (vs) structures using surface wave dispersion data involves minimizing a misfit function that is commonly solved through gradient-based optimization. Sensitivity kernels for model updates are commonly estimated using numerical differentiation, variational methods or implicit functions which however, may involve numerical instability and computational challenges when dealing with complex velocity models and large datasets. In this study, we propose a novel surface wave inversion framework in which error-free gradients are calculated by automatic differentiation (AD) and forward modeling is implemented by convenient computational graphs in the state-of-the-art deep learning framework. The AD-based inversion approach is first validated using two synthetic datasets. Then the subsurface structures at three distinct locations, namely the Great Plains and the Long Beach in the US and Tong Zhou in China, are also derived using this method with seismic ambient noise data, which show nice consistency with those obtained using traditional methods. With the significantly improved computational efficiency, a great number of initial models can be inverted simultaneously to mitigate the impact of local minima and to estimate the uncertainty in the invert models. We have developed a new surface wave inversion package named ADsurf based on automatic differentiation and computational graphs in the deep learning framework, and its computational efficiency is also compared with the traditional finite-difference based gradient estimation approach. While a great number of intriguing studies on the geophysical inverse problems have been conducted recently using deep learning for end-to-end mapping, the use of AD provided in the in the deep learning frameworks to assist and expedite the gradient computations are still underexploited in geophysics. Thus, it is expected that various geophysical inverse problems in many different areas beyond the surface wave inversion can also be tackled with this new paradigm in the future.

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Application of active-source surface waves in urban underground space detection: a case study of Rongcheng County, Hebei, China

Cited by 3 publications

References 0 publications

Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method

Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method

Multichannel Analysis of Surface Waves (MASW) to Estimate the Shear Wave Velocity for Engineering Characterization of Soils at Hawassa Town, Southern Ethiopia

Multimodal surface wave inversion with automatic differentiation

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