scholarly journals On cycle-skipping and misfit functions modification for full-wave inversion: comparison of five recent approaches

Geophysics ◽  
2021 ◽  
pp. 1-85
Author(s):  
Arnaud Pladys ◽  
Romain Brossier ◽  
Yubing Li ◽  
Ludovic Métivier
Keyword(s):  
Least Squares ◽  
Field Data ◽  
Optimal Transport ◽  
Waveform Inversion ◽  
Imaging Method ◽  
Full Waveform Inversion ◽  
Wave Inversion ◽  
Full Waveform ◽  
Full Wave ◽  
Definition Of

Full waveform inversion, a high-resolution seismic imaging method, is known to require sufficiently accurate initial models to converge toward meaningful estimations of the subsurface mechanical properties. This limitation is due to the non-convexity of the least-squares distance with respect to kinematic mismatch. We propose a comparison of five misfit functions promoted recently to mitigate this issue: adaptive waveform inversion, instantaneous envelope, normalized integration, and two methods based on optimal transport. We explain which principles these methods are based on and illustrate how they are designed to better handle kinematic mismatch than a least-squares misfit function. By doing so, we can exhibit specific limitations of these methods in canonical cases. We further assess the interest of these five approaches for application to field data based on a synthetic Marmousi case study. We illustrate how adaptive waveform inversion and the two methods based on optimal transport possess interesting properties, making them appealing strategies applicable to field data. Another outcome is the definition of generic tools to compare misfit functions for full-waveform inversion.

scholarly journals Land seismic multiparameter full waveform inversion in elastic VTI media by simultaneously interpreting body waves and surface waves with an optimal transport based objective function

2019 ◽  
Vol 219 (3) ◽  
pp. 1970-1988 ◽  
Author(s):  
Weiguang He ◽  
Romain Brossier ◽  
Ludovic Métivier ◽  
René-Édouard Plessix
Keyword(s):  
Objective Function ◽  
Surface Waves ◽  
Least Squares ◽  
Optimal Transport ◽  
Waveform Inversion ◽  
Body Waves ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Initial Model ◽  
Full Waveform

SUMMARY Land seismic multiparameter full waveform inversion in anisotropic media is challenging because of high medium contrasts and surface waves. With a data-residual least-squares objective function, the surface wave energy usually masks the body waves and the gradient of the objective function exhibits high values in the very shallow depths preventing from recovering the deeper part of the earth model parameters. The optimal transport objective function, coupled with a Gaussian time-windowing strategy, allows to overcome this issue by more focusing on phase shifts and by balancing the contributions of the different events in the adjoint-source and the gradients. We first illustrate the advantages of the optimal transport function with respect to the least-squares one, with two realistic examples. We then discuss a vertical transverse isotropic (VTI) example starting from a quasi 1-D isotropic initial model. Despite some cycle-skipping issues in the initial model, the inversion based on the windowed optimal transport approach converges. Both the near-surface complexities and the variations at depth are recovered.

scholarly journals Application of optimal transport and the quadratic Wasserstein metric to full-waveform inversion

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. R43-R62 ◽  
Author(s):  
Yunan Yang ◽  
Björn Engquist ◽  
Junzhe Sun ◽  
Brittany F. Hamfeldt
Keyword(s):  
Least Squares ◽  
Optimal Transport ◽  
Waveform Inversion ◽  
Transportation Cost ◽  
Velocity Model ◽  
Seismic Inversion ◽  
Full Waveform Inversion ◽  
Wasserstein Metric ◽  
Full Waveform ◽  
Adjoint State

Conventional full-waveform inversion (FWI) using the least-squares norm as a misfit function is known to suffer from cycle-skipping issues that increase the risk of computing a local rather than the global minimum of the misfit. The quadratic Wasserstein metric has proven to have many ideal properties with regard to convexity and insensitivity to noise. When the observed and predicted seismic data are considered to be two density functions, the quadratic Wasserstein metric corresponds to the optimal cost of rearranging one density into the other, in which the transportation cost is quadratic in distance. Unlike the least-squares norm, the quadratic Wasserstein metric measures not only amplitude differences but also global phase shifts, which helps to avoid cycle-skipping issues. We have developed a new way of using the quadratic Wasserstein metric trace by trace in FWI and compare it with the global quadratic Wasserstein metric via the solution of the Monge-Ampère equation. We incorporate the quadratic Wasserstein metric technique into the framework of the adjoint-state method and apply it to several 2D examples. With the corresponding adjoint source, the velocity model can be updated using a quasi-Newton method. Numerical results indicate the effectiveness of the quadratic Wasserstein metric in alleviating cycle-skipping issues and sensitivity to noise. The mathematical theory and numerical examples demonstrate that the quadratic Wasserstein metric is a good candidate for a misfit function in seismic inversion.

Optimal transport for mitigating cycle skipping in full-waveform inversion: A graph-space transform approach

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R515-R540 ◽  
Author(s):  
Ludovic Métivier ◽  
Aude Allain ◽  
Romain Brossier ◽  
Quentin Mérigot ◽  
Edouard Oudet ◽  
...  
Keyword(s):  
Seismic Data ◽  
Optimal Transport ◽  
Waveform Inversion ◽  
P Wave ◽  
Imaging Method ◽  
Convexity Property ◽  
Full Waveform Inversion ◽  
Low Frequencies ◽  
Transport Distance ◽  
Full Waveform

Optimal transport distance has been recently promoted as a tool to measure the discrepancy between observed and seismic data within the full-waveform-inversion strategy. This high-resolution seismic imaging method, based on a data-fitting procedure, suffers from the nonconvexity of the standard least-squares discrepancy measure, an issue commonly referred to as cycle skipping. The convexity of the optimal transport distance with respect to time shifts makes it a good candidate to provide a more convex misfit function. However, the optimal transport distance is defined only for the comparison of positive functions, while seismic data are oscillatory. A review of the different attempts proposed in the literature to overcome this difficulty is proposed. Their limitations are illustrated: Basically, the proposed strategies are either not applicable to real data, or they lose the convexity property of optimal transport. On this basis, we introduce a novel strategy based on the interpretation of the seismic data in the graph space. Each individual trace is considered, after discretization, as a set of Dirac points in a 2D space, where the amplitude becomes a geometric attribute of the data. This ensures the positivity of the data, while preserving the geometry of the signal. The differentiability of the misfit function is obtained by approximating the Dirac distributions through 2D Gaussian functions. The interest of this approach is illustrated numerically by computing misfit-function maps in schematic examples before moving to more realistic synthetic full-waveform exercises, including the Marmousi model. The better convexity of the graph-based optimal transport distance is shown. On the Marmousi model, starting from a 1D linearly increasing initial model, with data without low frequencies (no energy less than 3 Hz), a meaningful estimation of the P-wave velocity model is recovered, outperforming previously proposed optimal-transport-based misfit functions.

scholarly journals Normalized nonzero-lag crosscorrelation elastic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. R1-R10 ◽  
Author(s):  
Zhendong Zhang ◽  
Tariq Alkhalifah ◽  
Zedong Wu ◽  
Yike Liu ◽  
Bin He ◽  
...  
Keyword(s):  
Field Data ◽  
Extreme Values ◽  
Time Lag ◽  
Waveform Inversion ◽  
Optimal Time ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Velocity Models ◽  
Full Waveform ◽  
The Earth

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 to simulate the propagation of seismic waves in the earth. Our proposed objective function emphasizes the matching of the phases of the events in the calculated and observed data, and thus, it is more immune to inaccuracies in the initial model and the difference between the true and modeled physics. The normalization term can compensate the energy loss in the far offsets because of geometric spreading and avoid a bias in estimation toward extreme values in the observed data. We develop a polynomial-type weighting function and evaluate an approach to determine the optimal time lag. We use a synthetic elastic Marmousi model and the BigSky field data set to verify the effectiveness of the proposed method. To suppress the short-wavelength artifacts in the estimated S-wave velocity and noise in the field data, we apply a Laplacian regularization and a total variation constraint on the synthetic and field data examples, respectively.

A Graph-Space Optimal Transport Approach for Full Waveform Inversion

2018 ◽  
Author(s):  
L. Metivier ◽  
A. Allain ◽  
R. Brossier ◽  
Q. Merigot ◽  
E. Oudet ◽  
...  
Keyword(s):  
Optimal Transport ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Transport Approach

Full-waveform inversion of salt models using shape optimization and simulated annealing

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R793-R804 ◽  
Author(s):  
Debanjan Datta ◽  
Mrinal K. Sen ◽  
Faqi Liu ◽  
Scott Morton
Keyword(s):  
Simulated Annealing ◽  
Least Squares ◽  
Level Set ◽  
Waveform Inversion ◽  
Optimization Techniques ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Velocity Models ◽  
Full Waveform ◽  
Starting Model

A good starting model is imperative in full-waveform inversion (FWI) because it solves a least-squares inversion problem using a local gradient-based optimization method. A suboptimal starting model can result in cycle skipping leading to poor convergence and incorrect estimation of subsurface properties. This problem is especially crucial for salt models because the strong velocity contrasts create substantial time shifts in the modeled seismogram. Incorrect estimation of salt bodies leads to velocity inaccuracies in the sediments because the least-squares gradient aims to reduce traveltime differences without considering the sharp velocity jump between sediments and salt. We have developed a technique to estimate velocity models containing salt bodies using a combination of global and local optimization techniques. To stabilize the global optimization algorithm and keep it computationally tractable, we reduce the number of model parameters by using sparse parameterization formulations. The sparse formulation represents sediments using a set of interfaces and velocities across them, whereas a set of ellipses represents the salt body. We use very fast simulated annealing (VFSA) to minimize the misfit between the observed and synthetic data and estimate an optimal model in the sparsely parameterized space. The VFSA inverted model is then used as a starting model in FWI in which the sediments and salt body are updated in the least-squares sense. We partition model updates into sediment and salt updates in which the sediments are updated like conventional FWI, whereas the shape of the salt is updated by taking the zero crossing of an evolving level set surface. Our algorithm is tested on two 2D synthetic salt models, namely, the Sigsbee 2A model and a modified SEG Advanced Modeling Program (SEAM) Phase I model while fixing the top of the salt. We determine the efficiency of the VFSA inversion and imaging improvements from the level set FWI approach and evaluate a few sources of uncertainty in the estimation of salt shapes.

scholarly journals Increasing the robustness and applicability of full-waveform inversion: An optimal transport distance strategy

2016 ◽  
Vol 35 (12) ◽  
pp. 1060-1067 ◽  
Author(s):  
L. Métivier ◽  
R. Brossier ◽  
Q. Mérigot ◽  
E. Oudet ◽  
J. Virieux
Keyword(s):  
Optimal Transport ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Transport Distance ◽  
Full Waveform
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