Phase only reflection full-waveform inversion for high resolution model update

Mao, Jian; Sheng, James J.; Hilburn, Guy

doi:10.1190/segam2019-3214447.1

Cited by 7 publications

(2 citation statements)

References 14 publications

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“…; Luo, Wu and Gao ; Warner and Guasch ; Maharramov et al . ; Tang and McMechan ; Mao, Sheng and Hilburn ).…”

Section: D Multiscale Phase Inversionmentioning

confidence: 99%

“…Magnified views for different cross sections in Figure 5.observed traces d obs and d pre are superscripted by their abbreviations, and their arguments are for a point source at the source coordinate x s and the geophone is at the geophone coordinate x g Fu et al (2018). state that the MPI objective function is related to the classical traveltime-inversion(Luo and Schuster 1991a, b;Schuster and Quintus-Bosz 1993;Ma and Hale 2013;Luo et al 2016b) and phase-inversion methods(Bednar et al 2007;Luo, Wu and Gao 2016a;Warner and Guasch 2016;Maharramov et al 2017;Tang and McMechan 2017;Mao, Sheng and Hilburn 2019).The time integration in equation(2)acts as a simple and natural frequency shaping to improve the convergence of full Velocity profile comparisons for (a) x = 2, y = 2 km, (b) x = 2, z = 0.3 km and (c) y = 2, z = 0.3 km. The black, blue, green and red curves represent the true, initial, 3D-FWI and 3D-MPI velocity values, respectively.…”

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Multiscale phase inversion for 3D ocean‐bottom cable data

Feng

Schuster

2019

Geophysical Prospecting

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We invert three‐dimensional seismic data by a multiscale phase inversion scheme, a modified version of full waveform inversion, which applies higher order integrations to the input signal to produce low‐boost signals. These low‐boost signals are used as the input data for the early iterations, and lower order integrations are computed at the later iterations. The advantages of multiscale phase inversion are that it (1) is less dependent on the initial model compared to full waveform inversion, (2) is less sensitive to incorrectly modelled magnitudes and (3) employs a simple and natural frequency shaping filtering. For a layered model with a three‐dimensional velocity anomaly, results with synthetic data show that multiscale phase inversion can sometimes provide a noticeably more accurate velocity profile than full waveform inversion. Results with the Society of Exploration Geophysicists/European Association of Geoscientists and Engineers overthrust model shows that multiscale phase inversion more clearly resolves meandering channels in the depth slices. However, the data and model misfit functions achieve about the same values after 50 iterations. The results with three‐dimensional ocean‐bottom cable data show that, compared to the full waveform inversion tomogram, the three‐dimensional multiscale phase inversion tomogram provides a better match to the well log, and better flattens angle‐domain common image gathers. The problem is that the tomograms at the well log provide an incomplete low‐wavenumber estimate of the log's velocity profile. Therefore, a good low‐wavenumber estimate of the velocity model is still needed for an accurate multiscale phase inversion tomogram.

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“…; Luo, Wu and Gao ; Warner and Guasch ; Maharramov et al . ; Tang and McMechan ; Mao, Sheng and Hilburn ).…”

Section: D Multiscale Phase Inversionmentioning

confidence: 99%

mentioning

confidence: 99%

Multiscale phase inversion for 3D ocean‐bottom cable data

Feng

Schuster

2019

Geophysical Prospecting

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

2022

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Traditional least-squares full-waveform inversion (FWI) suffers from severe local minima problems in case of the presence of strongly dispersive surface waves. Additionally, recorded wavefields are often characterized by amplitude errors due to varying source coupling and incorrect 3D-to-2D geometrical-spreading correction. Thus, least-squares FWI is considered less than suitable for near-surface applications. In this paper, we introduce an amplitude-unbiased coherency measure as a misfit function that can be incorporated into FWI. Such coherency was earlier used in phase-weighted stacking (PWS) to enhance weak but coherent signals. The benefit of this amplitude-unbiased misfit function is that it can extract information uniformly for all seismic signals (surface waves, reflections, and scattered waves). Using the adjoint-state method, we show how to calculate the gradient of this new misfit function. We validate the robustness of the new approach using checkerboard tests and synthetic data contaminated by random noise. We then apply the new FWI approach to a field dataset acquired at an archaeological site located in Ostia, Italy. The goal of this survey was to map the unexcavated archaeological remains with high-resolution. We identify a known tumulus in the FWI results. The instantaneous-phase coherency FWI results also establish that the shallow subsurface under the survey lines is quite heterogeneous. The instantaneous-phase coherency FWI of near-surface data can be a promising tool to image shallow small-scale objects buried under shallow soil covers, as found at archaeological sites.

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