Characterizing near-surface structures at the Ostia archaeological site based on instantaneous-phase coherency inversion

Liu, Jianhuan; Ghose, Ranajit; Draganov, Deyan

doi:10.1190/geo2021-0467.1

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…Liu et al, 2022 evaluate

\delta ( {\frac{{s( t )}}{{{A}_{{\rm{syn}}}( t )}}} )

and

\delta ( {\frac{{H\{ {s( t )} \}}}{{{A}_{{\rm{syn}}}( t )}}} )

as:

\begin{matrix} δ (\frac{s ((), t)}{A_{syn} ((), t)}) & = & δ (\frac{s ((), t)}{\sqrt{{normals}^{2} (t) + H^{2} \{s (t)\}}}) \\ newline= & \frac{δ s ((), t) \sqrt{s^{2} ((), t) + H^{2} ({}, s ((), t))}}{s^{2} ((), t) + H^{2} ({}, s ((), t))} \\ - \frac{δ s (t) {normals}^{2} (t) + s (t) H \{s (t)\} δ H \{s (t)\}}{{[{normals}^{2} (t) + H^{2} \{s (t)\}]}^{\frac{3}{2}}} \\ newline= & δ s ((), t) H^{2} ({}, s ((), t)) - s ((), t) H ({}, s ((), t)) δ<... \end{matrix}

…”

Section: Theory and Methodologymentioning

confidence: 99%

“…To make the gradients of our objective function update towards the minimum of the objective, a minus sign has been added in equation ( 9). Based on previous work (Yuan et al, 2015(Yuan et al, , 2020Luo et al, 2018;Liu et al, 2022), we present the details on how to derive the gradient of the misfit defined in equation ( 9) with respect to model parameters m.…”

Section: Gradient For Misfit Function Based On Instantaneous-phase Co...mentioning

confidence: 99%

“…Yuan et al (2020) discussed the advantages and challenges of using phase information in adjoint waveform tomography. Liu et al (2022) proposed an amplitude-unbiased coherency measure as a misfit function and applied their FWI approach for characterizing near-surface structures at the Ostia archaeological site based on instantaneous-phase coherency.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Full‐waveform inversion of surface waves based on instantaneous‐phase coherency

Tohti

Liu

Xiao

et al. 2022

Near Surface Geophysics

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Full-waveform inversion of surface waves can provide high-resolution S-wave velocity (Vs) of the shallow subsurface and is becoming a popular shallowseismic method. We propose a misfit function based on instantaneous-phase coherency, which can measure the amplitude-unbiased coherency between measured and synthetic data. The instantaneous-phase coherency was once the key component that was used in the phase-weight stacking technology to enhance the weak but coherent signals. Using synthetic data, we show that our full-waveform inversion approach based on the proposed misfit function is robust in reconstructing subsurface anomalies from data contaminated by random noise. We also show that our misfit function is robust against the errors in the estimated source wavelets. We then choose to use published field data acquired at an archaeological site as a benchmark dataset to test the performance of our full-waveform inversion in a real environment. Subsurface structures identified in our inversion results are verified by an independent archaeological excavation, while the results from conventional full-waveform inversion are dominated by artefacts. The results of synthetic tests and field data experiments demonstrate the robustness of our full-waveform inversion approach in reconstructing the shallow subsurface structure from field data, where amplitude information of recorded wavefield may not be correctly recorded.

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“…Liu et al, 2022 evaluate

\delta ( {\frac{{s( t )}}{{{A}_{{\rm{syn}}}( t )}}} )

and

\delta ( {\frac{{H\{ {s( t )} \}}}{{{A}_{{\rm{syn}}}( t )}}} )

as:

\begin{matrix} δ (\frac{s ((), t)}{A_{syn} ((), t)}) & = & δ (\frac{s ((), t)}{\sqrt{{normals}^{2} (t) + H^{2} \{s (t)\}}}) \\ newline= & \frac{δ s ((), t) \sqrt{s^{2} ((), t) + H^{2} ({}, s ((), t))}}{s^{2} ((), t) + H^{2} ({}, s ((), t))} \\ - \frac{δ s (t) {normals}^{2} (t) + s (t) H \{s (t)\} δ H \{s (t)\}}{{[{normals}^{2} (t) + H^{2} \{s (t)\}]}^{\frac{3}{2}}} \\ newline= & δ s ((), t) H^{2} ({}, s ((), t)) - s ((), t) H ({}, s ((), t)) δ<... \end{matrix}

…”

Section: Theory and Methodologymentioning

confidence: 99%

Section: Gradient For Misfit Function Based On Instantaneous-phase Co...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Full‐waveform inversion of surface waves based on instantaneous‐phase coherency

Tohti

Liu

Xiao

et al. 2022

Near Surface Geophysics

Self Cite

View full text Add to dashboard Cite

show abstract

Subsoil density field reconstruction through 3-D FWI: a systematic comparison between vertical- and horizontal-force seismic sources

Kawasaki,

Minato,

Ghose

2023

Geophysical Journal International

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Summary Bulk-density (ρ) of soil is an important indicator of soil compaction and type. A knowledge of the spatial variability of in-situ soil density is important in geotechnical engineering, hydrology and agriculture. Surface geophysical methods have so far shown limited success in providing an accurate and high-resolution image of 3D soil-density distribution. In this pursuit, 3D seismic full-waveform inversion (FWI) is promising, provided the robustness and accuracy of density inversion via this approach can be established in the near-surface scale. However, simultaneous reconstruction of ρ and seismic wave velocities through multi-parameter FWI remains a challenging task. Near-surface seismic data are commonly dominated by dispersive surface waves whose velocities are controlled by the value and distribution of shear-wave velocity (VS). One major difficulty in estimating reliably ρ from near-surface seismic data is due to the relatively low sensitivity of the seismic wavefield to ρ compared to seismic velocities. Additionally, the accuracy of the estimated ρ decreases due to error in VS – an issue known as parameter coupling. Parameter coupling makes it difficult to estimate accurately ρ within the framework of conventional gradient-based FWI. More sophisticated optimization approaches (e.g., truncated Newton) can reduce the effect of parameter coupling, but these approaches are commonly not affordable in near-surface applications due to heavy computational burden. In this research, we have investigated how choosing correctly the force direction of the seismic source can contribute to a higher accuracy of ρ estimates through 3D FWI. Using scattered wavefields, the Hessian, and inversion tests, an in-depth and systematic investigation of datasets corresponding to different force directions has been carried out. A comparison of the scattered wavefields due to a point-localized ρ perturbation for different force directions shows the robustness of the horizontal-force dataset to noise compared to the vertical-force dataset. Furthermore, for a point-scatterer model, an analysis of the gradients of the misfit function using the Hessian shows that utilizing a horizontal-force source enables one to reconstruct the high-resolution gradient with relatively small parameter coupling. Finally, inversion tests for two different subsoil models demonstrate that 3D FWI on a horizontal-force-source seismic dataset is capable of providing a more accurate 3D ρ distribution in soil compared to a vertical-force-source dataset. Our results show that the use of a horizontal-force source might allow avoiding computationally demanding, costly optimization approaches in 3D FWI.

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Multiparameter shallow-seismic waveform inversion based on the Jensen–Shannon divergence

Yan,

Chen,

et al. 2024

Geophysical Journal International

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Summary Seismic full-waveform inversion (FWI) or waveform inversion (WI) has gained extensive attention as a cutting-edge imaging method, which is expected to reveal the high-resolution images of complex geological structures. In this paper, we regard each 1-D signal in the inversion system as a 1-D probability distribution, then use the Jensen-Shannon divergence (JSD) from information theory to measure the discrepancy between the predicted and observed signals, and finally implement a novel 2-D multiparameter shallow-seismic waveform inversion (MSWI). Essentially, the novel approach achieves an implicit weighting along the time-axis for each 1-D adjoint source defined by the classical waveform inversion (CWI), thus enhancing the extra illumination for a deeper medium compared with the CWI. By evaluating the inversion results of the two-layer model and fault model, the reconstruction accuracy for S-wave velocity and density of the new method is increased by about 30% and 20% compared with that of the CWI under the same conditions, respectively. The reconstruction performance for P-wave velocity of these two methods is almost equal. In addition, the new 2-D MSWI is also resilient to white Gaussian noise in the data. Numerically, the inversion system has almost the strongest sensitivities to the S-wave velocity and density, performing the poorest sensitivity to the P-wave velocity. Finally, we test the novel method with a detection case for a power tunnel.

show abstract

Characterizing near-surface structures at the Ostia archaeological site based on instantaneous-phase coherency inversion

Cited by 4 publications

References 32 publications

Full‐waveform inversion of surface waves based on instantaneous‐phase coherency

Full‐waveform inversion of surface waves based on instantaneous‐phase coherency

Subsoil density field reconstruction through 3-D FWI: a systematic comparison between vertical- and horizontal-force seismic sources

Multiparameter shallow-seismic waveform inversion based on the Jensen–Shannon divergence

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