Full waveform inversion of SH‐ and Love‐wave data in near‐surface prospecting

Dokter, E.; Köhn, D.; Wilken, Dennis; Nil, D. De; Rabbel, Wolfgang

doi:10.1111/1365-2478.12549

Cited by 61 publications

(35 citation statements)

References 67 publications

(101 reference statements)

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“…More recently, the existence of a beyond‐VTI anisotropy was reconfirmed (Wookey et al, ). Horizontally polarized shear waves and their superpositions propagating as Love waves had a significant impact on recent near‐surface inversions (Dokter et al, ; Pan et al, ). Typically, inversions focus on the velocity of SH waves along the horizontal axis; below we investigate which trade‐offs are irresolvable in inversions of this particular mode.…”

Section: Spectral Sensitivity Matrices and Numerical Analysis Of Tradmentioning

confidence: 99%

Scattering Radiation Pattern Atlas: What Anisotropic Elastic Properties Can Body Waves Resolve?

Kazei

Alkhalifah

2019

JGR Solid Earth

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Full‐waveform inversion (FWI) optimizes the subsurface properties of geophysical Earth models in such a way that the modeled data, based on these subsurface properties, match the observed data. The anisotropic properties, whether monoclinic, orthorhombic, triclinic, or vertical transversally isotropic (VTI), of the subsurface, be it a fractured reservoir or the core‐mantle boundary, are necessary to describe the observed wave phenomena. There are no principal limitations on the complexity of the anisotropy that can be inverted using FWI. However, the question remains—what kind of anisotropic descriptions of the elastic properties of the Earth can or cannot be inverted reliably from seismic waveforms? We reveal the resolution that can be achieved through reconstructions of each elastic parameter by building vertical resolution patterns from the scattering radiation patterns of body waves. A visual analysis of these patterns indicates “trade‐offs,” that is, perturbations of parameters that have the same reflection‐based scattering patterns as other perturbations. Each trade‐off leads to an apparent ambiguity in the inversion, which must be addressed by additional assumptions, constraints, or regularizations. For orthorhombic media, we find the exact trade‐offs that exist between parameters. Our parameterization isolates the VTI parameters, and therefore, we also obtain trade‐offs for every scattering mode for VTI media. We discover that only monoclinic parameters are recoverable from the first‐order scattering of monotypic waves. We summarize the trade‐offs in tables for easy reference. This paper is intended to be useful for researchers setting up anisotropic FWI problems, and interpreting or controlling the quality of such inversions.

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Section: Spectral Sensitivity Matrices and Numerical Analysis Of Tradmentioning

confidence: 99%

Scattering Radiation Pattern Atlas: What Anisotropic Elastic Properties Can Body Waves Resolve?

Kazei

Alkhalifah

2019

JGR Solid Earth

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“…It also applies to other dispersive waves, which have a liner moveout. For example, Love waves also could be used in the proposed inversion (Dokter et al, 2017). The proposed method also has the potential to estimate the anisotropy of the near-surface using the difference in dispersion spectra in the inline and crossline directions.…”

Section: Discussionmentioning

confidence: 99%

Wave-equation Rayleigh-wave dispersion inversion using fundamental and higher modes

Zhang

Alkhalifah

2019

GEOPHYSICS

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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 Rayleigh-wave modes (if they exist) included in the inversion. The [Formula: see text] spectrum is calculated using the linear Radon transform applied to a local similarity-based objective function; thus, we do not need to pick velocities in spectrum plots. As a result, the best match between the predicted and observed [Formula: see text] spectrum provides the optimal estimation of the S-wave velocity. We derive S-wave velocity updates using the adjoint-state method and solve the optimization problem using a limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Our method excels in cases in which the S-wave velocity has vertical reversals and lateral variations because we used all-modes dispersion, and it can suppress the local minimum problem often associated with full-waveform inversion applications. Synthetic and field examples are used to verify the effectiveness of our method.

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“…Numerical examples (Romdhane et al 2011;Zeng et al 2011a;Bretaudeau et al 2013;Borisov et al 2017;Pan et al 2018a) have demonstrated that FWI is a promising way in quantitatively imaging near-surface structures. Applications of FWI on field data sets (Tran et al 2013;Kallivokas et al 2013;Amrouche and Yamanaka 2015;Nguyen et al 2016;Pan et al 2016b;Dokter et al 2017) have also proved the applicability as well as the high resolution of FWI for characterizing near-surface heterogeneity. Shallow-seismic FWI is an ill-posed problem and could converge toward a local minimum especially when a poor initial model is provided ).…”

Section: Introductionmentioning

confidence: 96%

High-Resolution Characterization of Near-Surface Structures by Surface-Wave Inversions: From Dispersion Curve to Full Waveform

2019

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Surface waves are widely used in near-surface geophysics and provide a non-invasive way to determine near-surface structures. By extracting and inverting dispersion curves to obtain local 1D S-wave velocity profiles, multichannel analysis of surface waves (MASW) has been proven as an efficient way to analyze shallow-seismic surface waves. By directly inverting the observed waveforms, full-waveform inversion (FWI) provides another feasible way to use surface waves in reconstructing near-surface structures. This paper provides a state of the art on MASW and shallow-seismic FWI, and a comparison of both methods. A two-parameter numerical test is performed to analyze the nonlinearity of MASW and FWI, including the classical, the multiscale, the envelope-based, and the amplitude-spectrum-based FWI approaches. A checkerboard model is used to compare the resolution of MASW and FWI. These numerical examples show that classical FWI has the highest nonlinearity and resolution among these methods, while MASW has the lowest nonlinearity and resolution. The modified FWI approaches have an intermediate nonlinearity and resolution between classical FWI and MASW. These features suggest that a sequential application of MASW and FWI could provide an efficient hierarchical way to delineate near-surface structures. We apply the sequential-inversion strategy to two field data sets acquired in Olathe, Kansas, USA, and Rheinstetten, Germany, respectively. We build a 1D initial model by using MASW and then apply the multiscale FWI to the data. High-resolution 2D S-wave velocity images are obtained in both cases, whose reliabilities are proven by borehole data and a GPR profile, respectively. It demonstrates the effectiveness of combining MASW and FWI for high-resolution imaging of near-surface structures.

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Full waveform inversion of SH‐ and Love‐wave data in near‐surface prospecting

Cited by 61 publications

References 67 publications

Scattering Radiation Pattern Atlas: What Anisotropic Elastic Properties Can Body Waves Resolve?

Scattering Radiation Pattern Atlas: What Anisotropic Elastic Properties Can Body Waves Resolve?

Wave-equation Rayleigh-wave dispersion inversion using fundamental and higher modes

High-Resolution Characterization of Near-Surface Structures by Surface-Wave Inversions: From Dispersion Curve to Full Waveform

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