Complete Waveform Inversion Approach To Seismic Surface Waves And Adjoint Active Surfaces

The idea to exploit the dispersive mechanism of surface waves as a probing tool for investigating subsurface structure was introduced about 30 years ago, and afterwards a very intense research field has developed. Currently many methods known generally as Surface Wave Methods exist, and are well established, most of them assuming layered or depth dependent ground models. In most cases the parallel layer assumption is correct because the soil structure is expected to negligibly depart from a layered structure at a typical surface testing scale for engineering and geotechnical purposes however to exploit the amount of information achievable, it is necessary to extend the research, relaxing at least one of the underlying model assumptions. Indeed in classical SWM’s, surface waves are assumed to be Rayleigh waves, this means that a parallel layered model has been implicitly assumed. As a consequence search for a soil model geometry other than the assumed one can only result in slight perturbations. The only possible deduction is that overcoming limitations of layered models requires to exploit P and S waves which are indeed general solutions of the elastodynamic problem. Geometry can then be retrived by a complete waveform inversion based on a forward model capable of successfully reproducing all of the features of the displacement field in presence of complex scattering phenomena. In this research effort an inversion approach has been introduced which exploits the Boundary Element Method as forward model. Such approach is appealing from a theoretical point of view and is computationally efficient. Although in the present work a monochromatic signal traveling in a system constituted by a layer over an half space was investigated, this method is suitable for any number of layers, and multi-frequency environments. The boundary element approach can be easily generalized to three-dimensional modeling; moreover viscoelasticity can be introduced by the elasticviscoelastic principle of correspondence. Finally BEM can be easily implemented for parallel computing architecture. Synthetic cases of high and low impedance Jump were investigated for typical SWM setups and a first example of application on real data was performed. Finally an elegant analytic form of the minimization flow named Adjoint Active Surfaces was obtained combining Computer Vision technique of Active surfaces and the Adjoint Field method

Book of Abstracts

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Full-waveform inversion in three-dimensional PML-truncated elastic media : theory, computations, and field experiments

We are concerned with the high-fidelity subsurface imaging of the soil, which commonly arises in geotechnical site characterization and geophysical explorations. Specifically, we attempt to image the spatial distribution of the Lame parameters in semi-infinite, three-dimensional, arbitrarily heterogeneous formations, using surficial measurements of the soil's response to probing elastic waves. We use the complete waveforms of the medium's response to drive the inverse problem. Specifically, we use a partial-differential-equation (PDE)-constrained optimization approach, directly in the time-domain, to minimize the misfit between the observed response of the medium at select measurement locations, and a computed response corresponding to a trial distribution of the Lame parameters. We discuss strategies that lend algorithmic robustness to the proposed inversion schemes. To limit the computational domain to the size of interest, we employ perfectly-matched-layers (PMLs). The PML is a buffer zone that surrounds the domain of interest, and enforces the decay of outgoing waves. In order to resolve the forward problem, we present a hybrid finite element approach, where a displacement-stress formulation for the PML is coupled to a standard displacement-only formulation for the interior domain, thus leading to a computationally cost-efficient scheme. We discuss several time-integration schemes, including an explicit Runge-Kutta scheme, which is well-suited for large-scale problems on parallel computers. We report numerical results demonstrating stability and efficacy of the forward wave solver, and also provide examples attesting to the successful reconstruction of the two Lame parameters for both smooth and sharp profiles, using synthetic records. We also report the details of two field experiments, whose records we subsequently used to drive the developed inversion algorithms in order to characterize the sites where the field experiments took place. We contrast the full-waveform-based inverted site profile against a profile obtained using the Spectral-Analysis-of-Surface-Waves (SASW) method, in an attempt to compare our methodology against a widely used concurrent inversion approach. We also compare the inverted profiles, at select locations, with the results of independently performed, invasive, Cone Penetrometer Tests (CPTs). Overall, whether exercised by synthetic or by physical data, the full-waveform inversion method we discuss herein appears quite promising for the robust subsurface imaging of near-surface deposits in support of geotechnical site characterization investigations.Civil, Architectural, and Environmental Engineerin

GFZ Wireless Seismic Array (GFZ-WISE), a Wireless Mesh Network of Seismic Sensors: New Perspectives for Seismic Noise Array Investigations and Site Monitoring

Over the last few years, the analysis of seismic noise recorded by two dimensional arrays has been confirmed to be capable of deriving the subsoil shear-wave velocity structure down to several hundred meters depth. In fact, using just a few minutes of seismic noise recordings and combining this with the well known horizontal-to-vertical method, it has also been shown that it is possible to investigate the average one dimensional velocity structure below an array of stations in urban areas with a sufficient resolution to depths that would be prohibitive with active source array surveys, while in addition reducing the number of boreholes required to be drilled for site-effect analysis. However, the high cost of standard seismological instrumentation limits the number of sensors generally available for two-dimensional array measurements (i.e., of the order of 10), limiting the resolution in the estimated shear-wave velocity profiles. Therefore, new themes in site-effect estimation research by two-dimensional arrays involve the development and application of low-cost instrumentation, which potentially allows the performance of dense-array measurements, and the development of dedicated signal-analysis procedures for rapid and robust estimation of shear-wave velocity profiles. In this work, we present novel low-cost wireless instrumentation for dense two-dimensional ambient seismic noise array measurements that allows the real–time analysis of the surface-wavefield and the rapid estimation of the local shear-wave velocity structure for site response studies. We first introduce the general philosophy of the new system, as well as the hardware and software that forms the novel instrument, which we have tested in laboratory and field studies

Generative adversarial networks review in earthquake-related engineering fields

Within seismology, geology, civil and structural engineering, deep learning (DL), especially via generative adversarial networks (GANs), represents an innovative, engaging, and advantageous way to generate reliable synthetic data that represent actual samples' characteristics, providing a handy data augmentation tool. Indeed, in many practical applications, obtaining a significant number of high-quality information is demanding. Data augmentation is generally based on artificial intelligence (AI) and machine learning data-driven models. The DL GAN-based data augmentation approach for generating synthetic seismic signals revolutionized the current data augmentation paradigm. This study delivers a critical state-of-art review, explaining recent research into AI-based GAN synthetic generation of ground motion signals or seismic events, and also with a comprehensive insight into seismic-related geophysical studies. This study may be relevant, especially for the earth and planetary science, geology and seismology, oil and gas exploration, and on the other hand for assessing the seismic response of buildings and infrastructures, seismic detection tasks, and general structural and civil engineering applications. Furthermore, highlighting the strengths and limitations of the current studies on adversarial learning applied to seismology may help to guide research efforts in the next future toward the most promising directions

Seismic Waves

The importance of seismic wave research lies not only in our ability to understand and predict earthquakes and tsunamis, it also reveals information on the Earth's composition and features in much the same way as it led to the discovery of Mohorovicic's discontinuity. As our theoretical understanding of the physics behind seismic waves has grown, physical and numerical modeling have greatly advanced and now augment applied seismology for better prediction and engineering practices. This has led to some novel applications such as using artificially-induced shocks for exploration of the Earth's subsurface and seismic stimulation for increasing the productivity of oil wells. This book demonstrates the latest techniques and advances in seismic wave analysis from theoretical approach, data acquisition and interpretation, to analyses and numerical simulations, as well as research applications. A review process was conducted in cooperation with sincere support by Drs. Hiroshi Takenaka, Yoshio Murai, Jun Matsushima, and Genti Toyokuni

Modeling the morphodynamics of coastal responses to extreme events: what shape are we in?

This paper is not subject to U.S. copyright. The definitive version was published in Sherwood, C. R., van Dongeren, A., Doyle, J., Hegermiller, C. A., Hsu, T.-J., Kalra, T. S., Olabarrieta, M., Penko, A. M., Rafati, Y., Roelvink, D., van der Lugt, M., Veeramony, J., & Warner, J. C. Modeling the morphodynamics of coastal responses to extreme events: what shape are we in? Annual Review of Marine Science, 14, (2022): 457–492, https://doi.org/10.1146/annurev-marine-032221-090215.This review focuses on recent advances in process-based numerical models of the impact of extreme storms on sandy coasts. Driven by larger-scale models of meteorology and hydrodynamics, these models simulate morphodynamics across the Sallenger storm-impact scale, including swash,collision, overwash, and inundation. Models are becoming both wider (as more processes are added) and deeper (as detailed physics replaces earlier parameterizations). Algorithms for wave-induced flows and sediment transport under shoaling waves are among the recent developments. Community and open-source models have become the norm. Observations of initial conditions (topography, land cover, and sediment characteristics) have become more detailed, and improvements in tropical cyclone and wave models provide forcing (winds, waves, surge, and upland flow) that is better resolved and more accurate, yielding commensurate improvements in model skill. We foresee that future storm-impact models will increasingly resolve individual waves, apply data assimilation, and be used in ensemble modeling modes to predict uncertainties.All authors except D.R. were partially supported by the IFMSIP project, funded by US Office of Naval Research grant PE 0601153N under contracts N00014-17-1-2459 (Deltares), N00014-18-1-2785 (University of Delaware), N0001419WX00733 (US Naval Research Laboratory, Monterey), N0001418WX01447 (US Naval Research Laboratory, Stennis Space Center), and N0001418IP00016 (US Geological Survey). C.R.S., C.A.H., T.S.K., and J.C.W. were supported by the US Geological Survey Coastal/Marine Hazards and Resources Program. A.v.D. and M.v.d.L. were supported by the Deltares Strategic Research project Quantifying Flood Hazards and Impacts. M.O. acknowledges support from National Science Foundation project OCE-1554892

Microwave Sensing and Imaging

In recent years, microwave sensing and imaging have acquired an ever-growing importance in several applicative fields, such as non-destructive evaluations in industry and civil engineering, subsurface prospection, security, and biomedical imaging. Indeed, microwave techniques allow, in principle, for information to be obtained directly regarding the physical parameters of the inspected targets (dielectric properties, shape, etc.) by using safe electromagnetic radiations and cost-effective systems. Consequently, a great deal of research activity has recently been devoted to the development of efficient/reliable measurement systems, which are effective data processing algorithms that can be used to solve the underlying electromagnetic inverse scattering problem, and efficient forward solvers to model electromagnetic interactions. Within this framework, this Special Issue aims to provide some insights into recent microwave sensing and imaging systems and techniques

Source-independent full wavefield converted-phase elastic migration velocity analysis

Converted phase (CP) elastic seismic signals are comparable in amplitude to the primary signals recorded at large offsets and have the potential to be used in seismic imaging and velocity analysis. We present an approach for CP elastic wave equation velocity analysis that does not use source information and is applicable to surface-seismic, microseismic, teleseismic and vertical seismic profile (VSP) studies. Our approach is based on the cross-correlation between reflected or transmitted PP and CP PS (and/or SS and CP SP) waves propagated backward in time, and is formulated as an optimization problem with a differential semblance criterion objective function for the simultaneous update of both P- and S-wave velocity models. The merit of this approach is that it is fully data-driven, uses full waveform information, and requires only one elastic backward propagation to form an image rather than the two (one forward and one backward) propagations needed for standard reverse-time migration. Moreover, as the method does not require forward propagation, it does not suffer from migration operator source aliasing when a small number of shots are used. We present a derivation of the method and test it with a synthetic model and field micro-seismic data