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Artykuły w czasopismach na temat „Inversion full wave”

Autor: Grafiati

Data publikacji: 8 czerwca 2024

Data aktualizacji: 19 lipca 2025

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1

Luo, Yi, Yue Ma, Yan Wu, Hongwei Liu, and Lei Cao. "Full-traveltime inversion." GEOPHYSICS 81, no. 5 (2016): R261—R274. http://dx.doi.org/10.1190/geo2015-0353.1.

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Many previously published wave-equation-based methods, which attempt to automatically invert traveltime or kinematic information in seismic data or migrated gathers for smooth velocities, suffer a common and severe problem — the inversions are involuntarily and unconsciously hijacked by amplitude information. To overcome this problem, we have developed a new wave-equation-based traveltime inversion methodology, referred to as full-traveltime (i.e., fully dependent on traveltime) inversion (FTI), to automatically estimate a kinematically accurate velocity model from seismic data. The key idea o

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2

Brossier, Romain, Stéphane Operto, and Jean Virieux. "Seismic imaging of complex onshore structures by 2D elastic frequency-domain full-waveform inversion." GEOPHYSICS 74, no. 6 (2009): WCC105—WCC118. http://dx.doi.org/10.1190/1.3215771.

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Quantitative imaging of the elastic properties of the subsurface at depth is essential for civil engineering applications and oil- and gas-reservoir characterization. A realistic synthetic example provides for an assessment of the potential and limits of 2D elastic full-waveform inversion (FWI) of wide-aperture seismic data for recovering high-resolution P- and S-wave velocity models of complex onshore structures. FWI of land data is challenging because of the increased nonlinearity introduced by free-surface effects such as the propagation of surface waves in the heterogeneous near-surface. M

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Zhang, Chao, Ting Lei, and Yi Wang. "Two-Dimensional Full-Waveform Joint Inversion of Surface Waves Using Phases and Z/H Ratios." Applied Sciences 11, no. 15 (2021): 6712. http://dx.doi.org/10.3390/app11156712.

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Surface-wave dispersion and the Z/H ratio are important parameters used to resolve the Earth’s structure, especially for S-wave velocity. Several previous studies have explored using joint inversion of these two datasets. However, all of these studies used a 1-D depth-sensitivity kernel, which lacks precision when the structure is laterally heterogeneous. Adjoint tomography (i.e., full-waveform inversion) is a state-of-the-art imaging method with a high resolution. It can obtain better-resolved lithospheric structures beyond the resolving ability of traditional ray-based travel-time tomography

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4

Yilmaz, Öz, Kai Gao, Milos Delic, et al. "A reality check on full-wave inversion applied to land seismic data for near-surface modeling." Leading Edge 41, no. 1 (2022): 40–46. http://dx.doi.org/10.1190/tle41010040.1.

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We evaluate the performance of traveltime tomography and full-wave inversion (FWI) for near-surface modeling using the data from a shallow seismic field experiment. Eight boreholes up to 20-m depth have been drilled along the seismic line traverse to verify the accuracy of the P-wave velocity-depth model estimated by seismic inversion. The velocity-depth model of the soil column estimated by traveltime tomography is in good agreement with the borehole data. We used the traveltime tomography model as an initial model and performed FWI. Full-wave acoustic and elastic inversions, however, have fa

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Tran, Khiem T., Michael McVay, Michael Faraone, and David Horhota. "Sinkhole detection using 2D full seismic waveform tomography." GEOPHYSICS 78, no. 5 (2013): R175—R183. http://dx.doi.org/10.1190/geo2013-0063.1.

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We have developed an application of 2D time-domain waveform tomography for detection of embedded sinkholes and anomalies. The measured seismic surface wavefields were inverted using a full-waveform inversion (FWI) technique, based on a finite-difference solution of 2D elastic wave equations and the Gauss-Newton inversion method. The key advantage of this approach is the ability to generate all possible wave propagation modes of seismic wavefields (body waves and Rayleigh waves) that are then compared with measured data to infer complex subsurface properties.The pressure-wave (P-wave) and shear

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6

Barnes, Christophe, and Marwan Charara. "The domain of applicability of acoustic full-waveform inversion for marine seismic data." GEOPHYSICS 74, no. 6 (2009): WCC91—WCC103. http://dx.doi.org/10.1190/1.3250269.

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Marine reflection seismic data inversion is a compute-intensive process, especially in three dimensions. Approximations often are made to limit the number of physical parameters we invert for, or to speed up the forward modeling. Because the data often are dominated by unconverted P-waves, one popular approximation is to consider the earth as purely acoustic, i.e., no shear modulus. The material density sometimes is taken as a constant. Nonlinear waveform seismic inversion consists of iteratively minimizing the misfit between the amplitudes of the measured and the modeled data. Approximations,

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7

Zhang, Da-zhou, Ming-cai Zhang, Guang-Hong Ju, Zhang-qiang Xiong, and Wu-jun Xue. "Full waveform inversion of surface wave based on instantaneous frequency." Journal of Physics: Conference Series 2895, no. 1 (2024): 012045. https://doi.org/10.1088/1742-6596/2895/1/012045.

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Abstract Surface wave has many advantages, such as low attenuation, high signal-to-noise ratio, strong anti-interference ability and dispersion characteristics in layered media. It is widely used in engineering measurement and nondestructive testing. However, the applicability and reliability of surface wave processing methods are severely restricted by velocity inversion or strong heterogeneity of the medium. To overcome these shortcomings, in recent years, scholars have studied full-wave inversion methods including data preprocessing, wave field forward, gradient calculation, and inversion o

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8

Biondi, Biondo, and Ali Almomin. "Simultaneous inversion of full data bandwidth by tomographic full-waveform inversion." GEOPHYSICS 79, no. 3 (2014): WA129—WA140. http://dx.doi.org/10.1190/geo2013-0340.1.

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The convergence of full-waveform inversion can be improved by extending the velocity model along either the subsurface-offset axis or the time-lag axis. The extension of the velocity model along the time-lag axis enables us to linearly model large time shifts caused by velocity perturbations. This linear modeling was based on a new linearization of the scalar wave equation in which perturbation of the extended slowness squared was convolved in time with the second time derivative of the background wavefield. The linearization was accurate for reflected events and transmitted events. We determi

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9

da Silva, Nuno V., Gang Yao, and Michael Warner. "Semiglobal viscoacoustic full-waveform inversion." GEOPHYSICS 84, no. 2 (2019): R271—R293. http://dx.doi.org/10.1190/geo2017-0773.1.

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Full-waveform inversion deals with estimating physical properties of the earth’s subsurface by matching simulated to recorded seismic data. Intrinsic attenuation in the medium leads to the dispersion of propagating waves and the absorption of energy — media with this type of rheology are not perfectly elastic. Accounting for that effect is necessary to simulate wave propagation in realistic geologic media, leading to the need to estimate intrinsic attenuation from the seismic data. That increases the complexity of the constitutive laws leading to additional issues related to the ill-posed natu

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10

Luo, Y., and G. T. Schuster. "Wave‐equation traveltime inversion." GEOPHYSICS 56, no. 5 (1991): 645–53. http://dx.doi.org/10.1190/1.1443081.

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This paper presents a new traveltime inversion method based on the wave equation. In this new method, designated as wave‐equation traveltime inversion (WT), seismograms are computed by any full‐wave forward modeling method (we use a finite‐difference method). The velocity model is perturbed until the traveltimes from the synthetic seismograms are best fitted to the observed traveltimes in a least squares sense. A gradient optimization method is used and the formula for the Frechét derivative (perturbation of traveltimes with respect to velocity) is derived directly from the wave equation. No t

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11

Bleibinhaus, Florian, and Stéphane Rondenay. "Effects of surface scattering in full-waveform inversion." GEOPHYSICS 74, no. 6 (2009): WCC69—WCC77. http://dx.doi.org/10.1190/1.3223315.

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In full-waveform inversion of seismic body waves, often the free surface is ignored on grounds of computational efficiency. A synthetic study was performed to investigate the effects of this simplification. In terms of size and frequency, the test model and data conform to a real long-offset survey of the upper crust across the San Andreas fault. Random fractal variations are superimposed on a background model with strong lateral and vertical velocity variations ranging from 1200 to 6800 m/s. Synthetic data were computed and inverted for this model and different topographies. A fully viscoelas

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12

Xue, Zhiguang, Junzhe Sun, Sergey Fomel, and Tieyuan Zhu. "Accelerating full-waveform inversion with attenuation compensation." GEOPHYSICS 83, no. 1 (2018): A13—A20. http://dx.doi.org/10.1190/geo2017-0469.1.

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The calculation of the gradient in full-waveform inversion (FWI) usually involves crosscorrelating the forward-propagated source wavefield and the back-propagated data residual wavefield at each time step. In the real earth, propagating waves are typically attenuated due to the viscoelasticity, which results in an attenuated gradient for FWI. Replacing the attenuated true gradient with a [Formula: see text]-compensated gradient can accelerate the convergence rate of the inversion process. We have used a phase-dispersion and an amplitude-loss decoupled constant-[Formula: see text] wave equation

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13

Guddati, Murthy, Tuhin Roy, Abdelrahman M. Elmeliegy, and Matthew W. Urban. "Shear wave elastography: From dispersion matching to full waveform inversion." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A265. http://dx.doi.org/10.1121/10.0018796.

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Shear Wave Elastography (SWE) involves estimating mechanical properties through inversion, i.e., matching measured and simulated propagation characteristics of shear waves in the tissue. The accuracy of the estimated properties depends significantly on the specific characteristics/responses that are being matched. These could range from simple group velocity to dispersion curves and to full-wave response (particle velocity measurements). Using specific applications of arterial, liver, and tumor elstography, we illustrate that effective SWE is performed by resorting to an inversion approach, or

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14

Dettmer, Jan, Stan E. Dosso, and Charles W. Holland. "Full wave-field reflection coefficient inversion." Journal of the Acoustical Society of America 122, no. 6 (2007): 3327–37. http://dx.doi.org/10.1121/1.2793609.

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15

Sears, Timothy J., Penny J. Barton, and Satish C. Singh. "Elastic full waveform inversion of multicomponent ocean-bottom cable seismic data: Application to Alba Field, U. K. North Sea." GEOPHYSICS 75, no. 6 (2010): R109—R119. http://dx.doi.org/10.1190/1.3484097.

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Elastic full waveform inversion of multichannel seismic data represents a data-driven form of analysis leading to direct quantification of the subsurface elastic parameters in the depth domain. Previous studies have focused on marine streamer data using acoustic or elastic inversion schemes for the inversion of P-wave data. In this paper, P- and S-wave velocities are inverted for using wide-angle multicomponent ocean-bottom cable (OBC) seismic data. Inversion is undertaken using a two-dimensional elastic algorithm operating in the time domain, which allows accurate modeling and inversion of th

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16

Vigh, Denes, and E. William Starr. "3D prestack plane-wave, full-waveform inversion." GEOPHYSICS 73, no. 5 (2008): VE135—VE144. http://dx.doi.org/10.1190/1.2952623.

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Prestack depth migration has been used for decades to derive velocity distributions in depth. Numerous tools and methodologies have been developed to reach this goal. Exploration in geologically more complex areas exceeds the abilities of existing methods. New data-acquisition and data-processing methods are required to answer these new challenges effectively. The recently introduced wide-azimuth data acquisition method offers better illumination and noise attenuation as well as an opportunity to more accurately determine velocities for imaging. One of the most advanced tools for depth imaging

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17

Lu, Cai, Jijun Liu, Liyuan Qu, Jianbo Gao, Hanpeng Cai, and Jiandong Liang. "Resource-Efficient Acoustic Full-Waveform Inversion via Dual-Branch Physics-Informed RNN with Scale Decomposition." Applied Sciences 15, no. 2 (2025): 941. https://doi.org/10.3390/app15020941.

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Full-waveform velocity inversion has long been a primary focus in seismic exploration. Full-waveform inversion techniques employing physics-informed recurrent neural networks (PIRNNs) have recently gained significant scholarly attention. However, these approaches demand considerable storage to capture spatiotemporal seismic wave propagation fields and their gradient information, often exceeding the memory capabilities of current GPU resources during field data processing. This study proposes a full-waveform inversion method utilizing a dual-branch PIRNN architecture to effectively minimize GPU

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18

Wen, Jiawei, Can Jiang, and Hao Chen. "High-Precision Corrosion Detection via SH1 Guided Wave Based on Full Waveform Inversion." Sensors 23, no. 24 (2023): 9902. http://dx.doi.org/10.3390/s23249902.

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Corrosion detection for industrial settings is crucial for safe and efficient operations. Due to its high imaging resolution, the guided–wave full–waveform inversion tomography technique has significant potential for corrosion detection of plate metals. Limited by the long wavelengths of A0 and S0 mode waves, this method exhibits inadequate detection resolution for the earlier shallow and small corrosion defects. Based on the relatively short wavelength characteristics of the SH1 mode wave, we propose a high–precision corrosion detection method via SH1 guided wave using the full waveform inver

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19

Witte, Philipp, Mathias Louboutin, Keegan Lensink, et al. "Full-waveform inversion, Part 3: Optimization." Leading Edge 37, no. 2 (2018): 142–45. http://dx.doi.org/10.1190/tle37020142.1.

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This tutorial is the third part of a full-waveform inversion (FWI) tutorial series with a step-by-step walkthrough of setting up forward and adjoint wave equations and building a basic FWI inversion framework. For discretizing and solving wave equations, we use Devito ( http://www.opesci.org/devito-public ), a Python-based domain-specific language for automated generation of finite-difference code ( Lange et al., 2016 ). The first two parts of this tutorial ( Louboutin et al., 2017 , 2018 ) demonstrated how to solve the acoustic wave equation for modeling seismic shot records and how to comput

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20

Agudo, Òscar Calderón, Nuno Vieira da Silva, George Stronge, and Michael Warner. "Mitigating elastic effects in marine 3-D full-waveform inversion." Geophysical Journal International 220, no. 3 (2019): 2089–104. http://dx.doi.org/10.1093/gji/ggz569.

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SUMMARY The potential of full-waveform inversion (FWI) to recover high-resolution velocity models of the subsurface has been demonstrated in the last decades with its application to field data. But in certain geological scenarios, conventional FWI using the acoustic wave equation fails in recovering accurate models due to the presence of strong elastic effects, as the acoustic wave equation only accounts for compressional waves. This becomes more critical when dealing with land data sets, in which elastic effects are generated at the source and recorded directly by the receivers. In marine set

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21

Ma, Yong, and Dave Hale. "Wave-equation reflection traveltime inversion with dynamic warping and full-waveform inversion." GEOPHYSICS 78, no. 6 (2013): R223—R233. http://dx.doi.org/10.1190/geo2013-0004.1.

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In reflection seismology, full-waveform inversion (FWI) can generate high-wavenumber subsurface velocity models but often suffers from an objective function with local minima caused mainly by the absence of low frequencies in seismograms. These local minima cause cycle skipping when the low-wavenumber component in the initial velocity model for FWI is far from the true model. To avoid cycle skipping, we discovered a new wave-equation reflection traveltime inversion (WERTI) to update the low-wavenumber component of the velocity model, while using FWI to only update high-wavenumber details of th

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22

Oh, Ju-Won, Youngjae Shin, Tariq Alkhalifah, and Dong-Joo Min. "Multistage elastic full-waveform inversion for tilted transverse isotropic media." Geophysical Journal International 223, no. 1 (2020): 57–76. http://dx.doi.org/10.1093/gji/ggaa295.

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SUMMARY Seismic anisotropy is an important physical phenomenon that significantly affects wave propagation in complex sedimentary basins. When geological structures exhibit steep dips or severe folding, the symmetry axis of the transversely isotropic (TI) representation of the region can be rotated, leading to tilted transversely isotropic (TTI) media. We seek to find the optimal full-waveform inversion (FWI) strategy to estimate both the seismic velocities and the anisotropic parameters, including the tilt angle, in the presence of elastic TTI media. We first formulate the forward and inverse

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23

Borisov, Dmitry, Ryan Modrak, Fuchun Gao, and Jeroen Tromp. "3D elastic full-waveform inversion of surface waves in the presence of irregular topography using an envelope-based misfit function." GEOPHYSICS 83, no. 1 (2018): R1—R11. http://dx.doi.org/10.1190/geo2017-0081.1.

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Full-waveform inversion (FWI) is a powerful method for estimating the earth’s material properties. We demonstrate that surface-wave-driven FWI is well-suited to recovering near-surface structures and effective at providing S-wave speed starting models for use in conventional body-wave FWI. Using a synthetic example based on the SEG Advanced Modeling phase II foothills model, we started with an envelope-based objective function to invert for shallow large-scale heterogeneities. Then we used a waveform-difference objective function to obtain a higher-resolution model. To accurately model surface

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24

Li, Jing, Sherif Hanafy, Zhaolun Liu, and Gerard T. Schuster. "Wave-equation dispersion inversion of Love waves." GEOPHYSICS 84, no. 5 (2019): R693—R705. http://dx.doi.org/10.1190/geo2018-0039.1.

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We present a theory for wave-equation inversion of Love-wave dispersion curves, in which the misfit function is the sum of the squared differences between the wavenumbers along the predicted and observed dispersion curves. Similar to inversion of Rayleigh-wave dispersion curves, the complicated Love-wave arrivals in traces are skeletonized as simpler data, namely, the picked dispersion curves in the [Formula: see text] domain. Numerical solutions to the SH-wave equation and an iterative optimization method are then used to invert these dispersion curves for the S-wave velocity model. This proc

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25

Kwon, Taekhyun, Joongmoo Byun, Byoung Yeop Kim, and Sik Huh. "Elastic full waveform inversion using plane-wave." Journal of Applied Geophysics 170 (November 2019): 103826. http://dx.doi.org/10.1016/j.jappgeo.2019.103826.

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Sjögreen, Björn, and N. Anders Petersson. "Source Estimation by Full Wave Form Inversion." Journal of Scientific Computing 59, no. 1 (2013): 247–76. http://dx.doi.org/10.1007/s10915-013-9760-6.

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Shen, Xukai, Simon Luo, Mike O'Brien, Esteban Diaz, and Imtiaz Ahmed. "Practical elastic full-waveform inversion in the Gulf of Mexico." Leading Edge 44, no. 5 (2025): 344–51. https://doi.org/10.1190/tle44050344.1.

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Elastic full-waveform inversion (EFWI) improves velocity model building accuracy through its utilization of a more accurate representation of wave propagation in the subsurface. Such accuracy is desirable in areas with high-impedance contrasts (e.g., at interfaces separating salt bodies from the surrounding sediments), where acoustic wave propagation is inadequate to describe and model the full wavefield. On the other hand, elastic modeling and inversion incur extra geophysical and computational challenges with the introduction of the shear wave and the corresponding velocity model. Although l

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Louboutin, Mathias, Philipp Witte, Michael Lange, et al. "Full-waveform inversion, Part 2: Adjoint modeling." Leading Edge 37, no. 1 (2018): 69–72. http://dx.doi.org/10.1190/tle37010069.1.

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This is the second part of a three-part tutorial series on full-waveform inversion (FWI) in which we provide a step-by-step walk through of setting up forward and adjoint wave equation solvers and an optimization framework for inversion. In Part 1 ( Louboutin et al., 2017 ), we showed how to use Devito ( http://www.opesci.org/devito-public ) to set up and solve acoustic wave equations with (impulsive) seismic sources and sample wavefields at the receiver locations to forward model shot records. Here in Part 2, we will discuss how to set up and solve adjoint wave equations with Devito and, from

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Cheng, Guangsen, Xingyao Yin, Zhaoyun Zong, Tongxing Xia, Jianli Wang, and Haojie Liu. "Seismic inversion using complex spherical-wave reflection coefficient at different offsets and frequencies." GEOPHYSICS 87, no. 2 (2022): R183—R192. http://dx.doi.org/10.1190/geo2020-0787.1.

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Compared with the plane-wave reflection coefficient, the spherical-wave reflection coefficient (SRC) can more accurately describe the reflected wavefield excited by a point source, especially in the case of low seismic frequency and short travel distance. However, unlike the widely used plane-wave amplitude-variation-with-offset/frequency (AVO/AVF) inversion, the practical application of spherical-wave AVO/AVF inversion in multilayer elastic media is still in the exploratory stage. One of the difficulties is how to fully use the amplitude and phase information of the complex-valued SRC and the

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Qi, Qiyuan, Wensha Huang, Donghao Zhang, and Liguo Han. "Robust Elastic Full-Waveform Inversion Based on Normalized Cross-Correlation Source Wavelet Inversion." Applied Sciences 13, no. 24 (2023): 13014. http://dx.doi.org/10.3390/app132413014.

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The elastic full-waveform inversion (EFWI) method efficiently utilizes the amplitude, phase, and travel time information present in multi-component seismic recordings to create detailed parameter models of subsurface structures. Within full-waveform inversion (FWI), accurate source wavelet estimation significantly impacts both the convergence and final result quality. The source wavelet, serving as the initial condition for the wave equation’s forward modeling algorithm, directly influences the matching degree between observed and synthetic data. This study introduces a novel method for estima

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Zhang, Zhendong, Tariq Alkhalifah, Zedong Wu, Yike Liu, Bin He, and Juwon Oh. "Normalized nonzero-lag crosscorrelation elastic full-waveform inversion." GEOPHYSICS 84, no. 1 (2019): R1—R10. http://dx.doi.org/10.1190/geo2018-0082.1.

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Full-waveform inversion (FWI) is an attractive technique due to its ability to build high-resolution velocity models. Conventional amplitude-matching FWI approaches remain challenging because the simplified computational physics used does not fully represent all wave phenomena in the earth. Because the earth is attenuating, a sample-by-sample fitting of the amplitude may not be feasible in practice. We have developed a normalized nonzero-lag crosscorrelataion-based elastic FWI algorithm to maximize the similarity of the calculated and observed data. We use the first-order elastic-wave equation

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Wang, Haiyang, Satish C. Singh, and Henri Calandra. "Integrated inversion using combined wave-equation tomography and full waveform inversion." Geophysical Journal International 198, no. 1 (2014): 430–46. http://dx.doi.org/10.1093/gji/ggu138.

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Espindola-Carmona, Armando, Jürgen Hoffmann, Frederik J. Simons, and Jeroen Tromp. "On the importance of horizontal components in source-encoded elastic full-waveform inversion: Multicomponent ocean-bottom-node data." Leading Edge 44, no. 5 (2025): 417a1–417a7. https://doi.org/10.1190/tle44050417a1.1.

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Elastic full-waveform inversion (EFWI) is a state-of-the-art seismic tomographic method. Recent advances in technology and instrumentation, combining crosstalk-free source-encoded FWI (SE-FWI) with multicomponent marine data acquisition using ocean-bottom nodes (OBNs), enable full-physics wave propagation and parameter inversion without the computational burden of traditional FWI. With OBN acquisition, P waves, S waves, and P-to-S conversions are recorded. It is not well understood to what extent adding horizontal components to SE-FWI improves the resolution of subsurface modeling. We assess t

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Groos, Lisa, Martin Schäfer, Thomas Forbriger, and Thomas Bohlen. "Application of a complete workflow for 2D elastic full-waveform inversion to recorded shallow-seismic Rayleigh waves." GEOPHYSICS 82, no. 2 (2017): R109—R117. http://dx.doi.org/10.1190/geo2016-0284.1.

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The S-wave velocity of the shallow subsurface can be inferred from shallow-seismic Rayleigh waves. Traditionally, the dispersion curves of the Rayleigh waves are inverted to obtain the (local) S-wave velocity as a function of depth. Two-dimensional elastic full-waveform inversion (FWI) has the potential to also infer lateral variations. We have developed a novel workflow for the application of 2D elastic FWI to recorded surface waves. During the preprocessing, we apply a line-source simulation (spreading correction) and perform an a priori estimation of the attenuation of waves. The iterative

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Xu, Tong, George A. McMechan, and Robert Sun. "3-D prestack full‐wavefield inversion." GEOPHYSICS 60, no. 6 (1995): 1805–18. http://dx.doi.org/10.1190/1.1443913.

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A full‐wavefield inversion algorithm for direct imaging of a 3-D compressional wave velocity distribution is based on the full 3-D scalar wave equation and operates on common‐source data recorded by areal arrays. For each source, the method involves reverse‐time extrapolation of the residual wavefield. Application of the image condition by crosscorrelation with the source wavefield at each time step produces a 3-D image whose amplitude at each point is proportional to the required velocity update at that point. Convergence to local minima is mitigated against by gradually increasing the wavenu

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Borisov, Dmitry, Fuchun Gao, Paul Williamson, and Jeroen Tromp. "Application of 2D full-waveform inversion on exploration land data." GEOPHYSICS 85, no. 2 (2020): R75—R86. http://dx.doi.org/10.1190/geo2019-0082.1.

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Estimating subsurface seismic properties is an important topic in civil engineering, oil and gas exploration, and global seismology. We have developed an application of 2D elastic waveform inversion with an active-source on-shore data set, as is typically acquired in exploration seismology on land. The maximum offset is limited to 12 km, and the lowest available frequency is 5 Hz. In such a context, surface waves are generally treated as noise and are removed as a part of data processing. In contrast to the conventional approach, our workflow starts by inverting surface waves to constrain shal

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Métivier, Ludovic, Grégory Bièvre, Romain Brossier, et al. "Elastic full-waveform inversion of seismic ambient noise." Leading Edge 44, no. 5 (2025): 373a1–373a12. https://doi.org/10.1190/tle44050373a1.1.

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Elastic full-waveform inversion (FWI) is appealing for an enhanced integration of wave physics propagation and the resulting improved characterization of the subsurface due to the reconstruction of P- and S-wave velocity models. While the high computational cost of elastic FWI can be controlled using adequate numerical methods, the increase in the nonlinearity of elastic FWI calls for dedicated strategies to design initial P- and S-wave velocity models and access low-frequency data. We believe that the recent surge in ocean-bottom sensor acquisition is an opportunity to develop such strategies

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Minkoff, Susan E., and William W. Symes. "Full waveform inversion of marine reflection data in the plane‐wave domain." GEOPHYSICS 62, no. 2 (1997): 540–53. http://dx.doi.org/10.1190/1.1444164.

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Full waveform inversion of a p‐τ marine data set from the Gulf of Mexico provides estimates of the long‐wavelength P‐wave background velocity, anisotropic seismic source, and three high‐frequency elastic parameter reflectivities that explain 70% of the total seismic data and 90% of the data in an interval around the gas sand target. The forward simulator is based on a plane‐wave viscoelastic model for P‐wave propagation and primary reflections in a layered earth. Differential semblance optimization, a variant of output least‐squares inversion, successfully estimates the nonlinear P‐wave backgr

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Haffinger, P., P. Doulgeris, and A. Gisolf. "Wave-equation-based AVO inversion: A 1.5D elastic full-waveform inversion technique for improved reservoir characterization." Leading Edge 44, no. 5 (2025): 415a1–415a9. https://doi.org/10.1190/tle44050415a1.1.

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Accurate subsurface characterization is vital for hydrocarbon exploration and the energy transition. Full-waveform inversion (FWI) potentially provides a complete data model by fully simulating elastic wave propagation in 3D, but it is computationally demanding. Linear amplitude variation with offset (AVO) inversion is computationally efficient by deploying a 1.5D data model but is limited by simplifying assumptions like primary reflections only. This study introduces elastic wave-equation-based AVO (WEB-AVO), which combines the efficiency of AVO inversion with the physical accuracy of FWI. Ad

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Agudo, Òscar Calderón, Nuno Vieira da Silva, Michael Warner, and Joanna Morgan. "Acoustic full-waveform inversion in an elastic world." GEOPHYSICS 83, no. 3 (2018): R257—R271. http://dx.doi.org/10.1190/geo2017-0063.1.

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Full-waveform inversion (FWI) is a technique used to obtain high-quality velocity models of the subsurface. Despite the elastic nature of the earth, the anisotropic acoustic wave equation is typically used to model wave propagation in FWI. In part, this simplification is essential for being efficient when inverting large 3D data sets, but it has the adverse effect of reducing the accuracy and resolution of the recovered P-wave velocity models, as well as a loss in potential to constrain other physical properties, such as the S-wave velocity given that amplitude information in the observed data

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Groos, Lisa, Martin Schäfer, Thomas Forbriger, and Thomas Bohlen. "The role of attenuation in 2D full-waveform inversion of shallow-seismic body and Rayleigh waves." GEOPHYSICS 79, no. 6 (2014): R247—R261. http://dx.doi.org/10.1190/geo2013-0462.1.

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Full-waveform inversion (FWI) of Rayleigh waves is attractive for shallow geotechnical investigations due to the high sensitivity of Rayleigh waves to the S-wave velocity structure of the subsurface. In shallow-seismic field data, the effects of anelastic damping are significant. Dissipation results in a low-pass effect as well as frequency-dependent decay with offset. We found this by comparing recorded waveforms with elastic and viscoelastic wave simulation. The effects of anelastic damping must be considered in FWI of shallow-seismic Rayleigh waves. FWI using elastic simulation of wave prop

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Um, Evan Schankee, Michael Commer, and Gregory A. Newman. "A strategy for coupled 3D imaging of large-scale seismic and electromagnetic data sets: Application to subsalt imaging." GEOPHYSICS 79, no. 3 (2014): ID1—ID13. http://dx.doi.org/10.1190/geo2013-0053.1.

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Offshore seismic and electromagnetic (EM) imaging for hydrocarbons can require up to tens of millions of parameters to describe the 3D distribution of complex seabed geology and relevant geophysical attributes. The imaging and data volumes for such problems are enormous. Descent-based methods are the only viable imaging approach, where it is often challenging to manage the convergence of stand-alone seismic and EM inversion experiments. When a joint seismic-EM inversion is implemented, convergence problems with descent-based methods are further aggravated. Moreover, resolution mismatches betwe

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Nguyen, Trung Dung, and Khiem T. Tran. "Site characterization with 3D elastic full-waveform tomography." GEOPHYSICS 83, no. 5 (2018): R389—R400. http://dx.doi.org/10.1190/geo2017-0571.1.

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We have developed a 3D elastic full-waveform inversion (FWI) method for geotechnical site characterization. The method is based on a solution of 3D elastic-wave equations for forward modeling to simulate wave propagation and a local optimization approach based on the adjoint-state method to update the model parameters. The staggered-grid finite-difference technique is used to solve the wave equations together with implementation of the perfectly matched layer condition for boundary truncation. Seismic wavefields are acquired from geophysical testing using sensors and sources located in uniform

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Athanasopoulos, Nikolaos, Edgar Manukyan, Thomas Bohlen, and Hansruedi Maurer. "Time–frequency windowing in multiparameter elastic FWI of shallow seismic wavefield." Geophysical Journal International 222, no. 2 (2020): 1164–77. http://dx.doi.org/10.1093/gji/ggaa242.

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SUMMARY Full-waveform inversion of shallow seismic wavefields is a promising method to infer multiparameter models of elastic material properties (S-wave velocity, P-wave velocity and mass density) of the shallow subsurface with high resolution. Previous studies used either the refracted Pwaves to reconstructed models of P-wave velocity or the high-amplitude Rayleigh waves to infer the S-wave velocity structure. In this work, we propose a combination of both wavefields using continuous time–frequency windowing. We start with the contribution of refracted P waves and gradually increase the time

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Rao, Jing, Madis Ratassepp, and Zheng Fan. "Guided Wave Tomography Based on Full Waveform Inversion." IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 63, no. 5 (2016): 737–45. http://dx.doi.org/10.1109/tuffc.2016.2536144.

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Wang, Kai, Meiyan Guo, Qingxia Xiao, et al. "Frequency Domain Full Waveform Inversion Method of Acquiring Rock Wave Velocity in Front of Tunnels." Applied Sciences 11, no. 14 (2021): 6330. http://dx.doi.org/10.3390/app11146330.

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Ahead geological prospecting, which can estimate adverse geology ahead of the tunnel face, is necessary in the process of tunnel construction. Due to its long detection range and good recognition effect on the interface, the seismic method is widely used in tunnel ahead prospecting. However, the observation space in tunnels is quite narrow compared to ground seismic prospecting, which leads to some problems in the acquisition of wave velocity, including: the velocity of the direct wave is used to replace the wave velocity of the forward rock approximately; the arrival time information of seism

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Zhang, Wensheng. "Frequency-domain elastic full-waveform inversion based on Green functions." Journal of Physics: Conference Series 2444, no. 1 (2023): 012003. http://dx.doi.org/10.1088/1742-6596/2444/1/012003.

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Abstract In this paper, the elastic full-waveform inversion in the frequency domain based on Green functions is investigated. The method allows to image media velocities of compressional wave and shear wave by using vertical and horizontal components. The forward problem is solved by the finite difference scheme with the perfectly matched layer in the frequency domain. The inversion is an optimization iterative process to minimize the residual between the synthetic data and the observed data on the surface. A gradient method is used to find the optimization direction, preconditioned with the d

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Feng, Zongcai, and Lianjie Huang. "Shear reflectivity compensation in full-waveform inversion using least-squares reverse-time migration." Geophysical Journal International 227, no. 1 (2021): 1–15. http://dx.doi.org/10.1093/gji/ggab193.

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SUMMARY The computational cost of elastic-waveform inversion is too high for inverting PP reflections, while using acoustic full-waveform inversion (FWI) is inaccurate because it does not depend on the shear modulus/velocity/impedance that affects elastic PP wavefield amplitudes. To solve this problem, we develop a waveform inversion method that uses acoustic least-squares reverse-time migration (LSRTM) to compensate the shear reflectivity for acoustic FWI. Our method is based on the quasi-elastic-wave equation developed by Chapman et al. (2014). The quasi-elastic-wave equation uses a lineariz

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Tang, Zhiyuan. "Frequency Domain Wave Equation Inversion and Its Application on the Heterogeneous Reservoir Model Data." Earth Science Research 6, no. 1 (2016): 55. http://dx.doi.org/10.5539/esr.v6n1p55.

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Seismic full waveform inversion seeks to make use of the full information based on full wave field modeling to extract quantitative information from seismograms. Its serious nonlinearity and high dependence on initial velocity model often results in unsatisfactory inversion results in paleo-karsts carbonate reservoir characterized by strong heterogeneity. The paper presents an improved strategy of multi-scale inversion to establish velocity field model of waveform tomography. the forward wave equation algorithm was derived in frequency domain, and then the Matrix formalism for the iterative in

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Zhang, Zhen-Dong, and Tariq Alkhalifah. "Wave-equation Rayleigh-wave dispersion inversion using fundamental and higher modes." GEOPHYSICS 84, no. 4 (2019): EN57—EN65. http://dx.doi.org/10.1190/geo2018-0506.1.

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Recorded surface waves often provide reasonable estimates of the S-wave velocity in the near surface. However, existing algorithms are mainly based on the 1D layered-model assumption and require picking the dispersion curves either automatically or manually. We have developed a wave-equation-based inversion algorithm that inverts for S-wave velocities using fundamental and higher mode Rayleigh waves without picking an explicit dispersion curve. Our method aims to maximize the similarity of the phase velocity spectrum ([Formula: see text]) of the observed and predicted surface waves with all Ra

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