Detecting a known near-surface target through application of frequency-dependent traveltime tomography and full-waveform inversion to P- and SH-wave seismic refraction data

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. R1-R17 ◽  
Author(s):  
Jianxiong Chen ◽  
Colin A. Zelt ◽  
Priyank Jaiswal
Keyword(s):  
Waveform Inversion ◽  
P Wave ◽  
Sh Wave ◽  
Void Space ◽  
Near Surface ◽  
Traveltime Tomography ◽  
Velocity Anomaly ◽  
Velocity Models ◽  
Full Waveform ◽  
Wave Models

We have applied a combined workflow of frequency-dependent traveltime tomography (FDTT) and full-waveform inversion (FWI) to 2D near-surface P- and SH-wave seismic data to detect a known target consisting of a buried tunnel with concrete walls and a void space inside. FDTT inverted the P- and SH-wave picked traveltimes at 250 Hz to provide long-wavelength background velocity models as the starting models for FWI. FWI inverted 18–54 Hz P-wave data and 16–50 Hz SH-wave data to produce velocity models with subwavelength- and wavelength-scale features allowing for direct interpretation of the velocity models as is usually carried out in conventional imaging using seismic reflection data. The P- and SH-wave models image the top part of the tunnel at the correct location at a depth of 1.6 m as a high-velocity anomaly. The P-wave models also image the air in the void space of the tunnel as a low-velocity anomaly. The inverted models were assessed by synthetic tests, the consistency of the inverted sources, and the fit between the predicted and observed data. As a comparison, conventional ray-theory infinite-frequency traveltime tomography (IFTT) was also applied in a combined workflow with FWI. The comparisons of the inverted models favor the use of FDTT over IFTT because (1) The FDTT models better recover the magnitude of the velocity anomalies and (2) the FDTT model serves as a better starting model for FWI, which results in a more accurate FWI velocity estimation with better recovery of the magnitude and location of the key features. FDTT will not provide significant benefits over IFTT in all studies, particularly those in which ray theory is valid.

Challenges in shallow targets reconstruction by 3D elastic full-waveform inversion — Which initial model?

Geophysics ◽  
2021 ◽  
pp. 1-91
Author(s):  
Daniela Teodor ◽  
Cesare Cesare ◽  
Farbod Khosro Anjom ◽  
Romain Brossier ◽  
Valentina Socco Laura ◽  
...  
Keyword(s):  
Field Data ◽  
Weighting Function ◽  
Waveform Inversion ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Initial Model ◽  
Near Surface ◽  
Velocity Models ◽  
Full Waveform ◽  
3D Acquisition

Elastic full-waveform inversion (FWI) is a powerful tool for high-resolution subsurface multi-parameter characterization. However, 3D FWI applied to land data for near-surface applications is particularly challenging, since the seismograms are dominated by highly energetic, dispersive, and complex-scattered surface waves (SWs). In these conditions, a successful deterministic FWI scheme requires an accurate initial model. This study, primarily focused on field data analysis for 3D applications, aims at enhancing the resolution in the imaging of complex shallow targets, by integrating devoted SW analysis techniques with a 3D spectral-element-based elastic FWI. From dispersion curves (DCs), extracted from seismic data recorded over a sharp-interface shallow target, we built different initial S-wave (VS) and P-wave (VP) velocity models (laterally homogeneous and laterally variable), using a specific data-transform. Starting from these models, we carry out 3D FWI tests on synthetic and field data, using a relatively straightforward inversion scheme. The field data processing before FWI consists of bandpass filtering and muting of noisy traces. During FWI, a weighting function is applied to the far-offset traces. We test both 2D and 3D acquisition layouts, with different positions of the sources and variable offsets. The 3D FWI workflow enriched the overall content of the initial models, allowing a reliable reconstruction of the shallow target, especially when using laterally variable initial models. Moreover, a 3D acquisition layout guaranteed a better reconstruction of the target’s shape and lateral extension. In addition, the integration of model-oriented (preliminary monoparametric FWI) and data-oriented (time-windowing) strategies into the main optimization scheme has granted further improvement of the FWI results.

Introduction to this special section: Near-surface imaging and modeling

2020 ◽  
Vol 39 (5) ◽  
pp. 310-310
Author(s):  
Steve Sloan ◽  
Dan Feigenbaum
Keyword(s):  
Open Source Software ◽  
Special Section ◽  
Waveform Inversion ◽  
Radar Data ◽  
Surface Velocity ◽  
Surface Imaging ◽  
Near Surface ◽  
Velocity Models ◽  
Full Waveform ◽  
Ground Penetrating

This special section on near-surface imaging and modeling was intended originally to focus on improving deeper imaging for exploration purposes through more accurate representations of the near surface, the highly variable zone that energy must traverse through on the way down and back up again to be recorded at the surface. However, as proposed manuscript topics started coming in, it became clear that this section would cover a wider range, from kilometers down to meters. Papers in this section highlight a range of near-surface-related work that includes applying full-waveform inversion (FWI) to improve near-surface velocity models, identifying potential sinkhole hazards before they collapse, the potential of smartphones as geophysical sensors, and new open-source software for ground-penetrating radar data.

scholarly journals Full Waveform Inversion in generalized coordinates for zones of curved topography

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
César Augusto Arias- Chica ◽  
David Abreo ◽  
Sergio Abreo ◽  
Luis Fernando Duque- Gómez ◽  
Ana Beatríz Ramírez- Silva
Keyword(s):  
Computing Time ◽  
Waveform Inversion ◽  
Surface Velocity ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Velocity Models ◽  
Full Waveform ◽  
Wide Range ◽  
Rugged Topography ◽  
Uniform Rectangular Grid

Full waveform inversion (FWI) has been recently used to estimate subsurface parameters, such as velocity models. This method, however, has a number of drawbacks when applied to zones with rugged topography due to the forced application of a Cartesian mesh on a curved surface. In this work, we present a simple coordinate transformation that enables the construction of a curved mesh. The proposed transformation is more suitable for rugged surfaces and it allows mapping a physical curved domain into a uniform rectangular grid, where acoustic FWI can be applied in the traditional way by introducing a modified Laplacian. We prove that the proposed approximation can have a wide range of applications, producing precise near-surface velocity models without increasing the computing time of the FWI.

Reconstruction of the Near-Surface Velocities with Trap Bodies by the Full Waveform Inversion

2021 ◽  
Author(s):  
Kirill Gennadievich Gadylshin ◽  
Vladimir Albertovich Cheverda ◽  
Danila Nikolaevich Tverdokhlebov
Keyword(s):  
Free Surface ◽  
Surface Area ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Near Surface ◽  
Velocity Models ◽  
Full Waveform ◽  
Seismic Image ◽  
Geological Conditions ◽  
Velocity Anomalies

Abstract Seismic surveys in the vast territory of Eastern Siberia are carried out in seismic and geological conditions of varying complexity. Obtaining a high-quality dynamic seismic image for the work area is a priority task in the states of contrasting heterogeneities of the near-surface. For this, it is necessary to restore an effective depth-velocity model that provides compensation for velocity anomalies and calculates static corrections. However, for the most complex near-surface structure, for example, the presence of trap intrusions and tuffaceous formations, the information content of the velocity models of the near-surface area obtained based on tomographic refinement turns out to be insufficient, and a search for another solution is required. The paper considers an approach based on Full Waveform Inversion (FWI). As the authors showed earlier, multiples associated with the free surface reduce the resolution of this approach. But their use increases the stability of the solution in the presence of uncorrelated noise. Therefore, at the first stage of FWI, the full wavefield is used, including free surface-related multiples, but they are suppressed in the next steps of the data processing. The results obtained demonstrate the ability of the FWI to restore complex geological structures of the near-surface area, even in the presence of high-velocity anomalies (trap intrusions).

scholarly journals Estimation of acoustic macro models using a genetic full-waveform inversion: Applications to the Marmousi model

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. R173-R184 ◽  
Author(s):  
Angelo Sajeva ◽  
Mattia Aleardi ◽  
Eusebio Stucchi ◽  
Nicola Bienati ◽  
Alfredo Mazzotti
Keyword(s):  
Prior Information ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Forward Modeling ◽  
Coarse Grid ◽  
P Wave ◽  
Stochastic Methods ◽  
Full Waveform Inversion ◽  
Velocity Models ◽  
Full Waveform

We have developed a stochastic full-waveform inversion that uses genetic algorithms (GA FWI) to estimate acoustic macro models of the P-wave velocity field. Stochastic methods such as GA severely suffer the curse of dimensionality, meaning that they require unaffordable computer resources for inverse problems with many unknowns and expensive forward modeling. To mitigate this issue, we have proposed a two-grid technique with a coarse grid to represent the subsurface for the GA inversion and a finer grid for the forward modeling. We have applied this procedure to invert synthetic acoustic data of the Marmousi model, and we have developed three different tests. The first two tests use a velocity model derived from standard stacking velocity analysis as prior information and differ only for the parameterization of the coarse grid. Their comparison indicates that a smart parameterization of the coarse grid may significantly improve the final result. The third test uses a linearly increasing 1D velocity model as prior information, a layer-stripping procedure, and a large number of model evaluations. All three tests return velocity models that fairly reproduce the long-wavelength structures of the Marmousi. First-break cycle skipping related to the seismograms of the final GA-FWI models is significantly reduced compared with that computed on the models used as prior information. Descent-based FWIs starting from final GA-FWI models yield velocity models with low and comparable model misfits and with an improved reconstruction of the structural details. The quality of the models obtained by GA FWI plus descent-based FWI is benchmarked against the models obtained by descent-based FWI started from a smoothed version of the Marmousi and started directly from the prior information models. Our results are promising and demonstrate the ability of the two-grid GA FWI to yield velocity models suitable as input to descent-based FWI.

scholarly journals 2-D multiparameter viscoelastic shallow-seismic full-waveform inversion: reconstruction tests and first field-data application

2020 ◽  
Vol 222 (1) ◽  
pp. 560-571
Author(s):  
Lingli Gao ◽  
Yudi Pan ◽  
Thomas Bohlen
Keyword(s):  
Wave Velocity ◽  
Wave Attenuation ◽  
Waveform Inversion ◽  
P Wave ◽  
S Wave ◽  
Velocity Models ◽  
Full Waveform ◽  
Shallow Seismic ◽  
P Wave Velocity ◽  
Data Application

SUMMARY 2-D full-waveform inversion (FWI) of shallow-seismic wavefields has recently become a novel way to reconstruct S-wave velocity models of the shallow subsurface with high vertical and lateral resolution. In most applications, seismic wave attenuation is ignored or considered as a passive modelling parameter only. In this study, we explore the feasibility and performance of multiparameter viscoelastic 2-D FWI in which seismic velocities and attenuation of P and S waves, respectively, and mass density are inverted simultaneously. Synthetic reconstruction experiments reveal that multiple crosstalks between all viscoelastic material parameters may occur. The reconstruction of S-wave velocity is always robust and of high quality. The parameters P-wave velocity and density exhibit weaker sensitivity and can be reconstructed more reliably by multiparameter viscoelastic FWI. Anomalies in S-wave attenuation can be recovered but with limited resolution. In a field-data application, a small-scale refilled trench is nicely delineated as a low P- and S-wave velocity anomaly. The reconstruction of P-wave velocity is improved by the simultaneous inversion of attenuation. The reconstructed S-wave attenuation reveals higher attenuation in the shallow weathering zone and weaker attenuation below. The variations in the reconstructed P- and S-wave velocity models are consistent with the reflectivity observed in a ground penetrating radar (GPR) profile.

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