Full Waveform Inversion Scheme Research Articles

Full-intensity waveform inversion

Many full-waveform inversion schemes are based on the iterative perturbation theory to fit the observed waveforms. When the observed waveforms lack low frequencies, those schemes may encounter convergence problems due to cycle skipping when the initial velocity model is far from the true model. To mitigate this difficulty, we have developed a new objective function that fits the seismic-waveform intensity, so the dependence of the starting model can be reduced. The waveform intensity is proportional to the square of its amplitude. Forming the intensity using the waveform is a nonlinear operation, which separates the original waveform spectrum into an ultra-low-frequency part and a higher frequency part, even for data that originally do not have low-frequency contents. Therefore, conducting multiscale inversions starting from ultra-low-frequency intensity data can largely avoid the cycle-skipping problem. We formulate the intensity objective function, the minimization process, and the gradient. Using numerical examples, we determine that the proposed method was very promising and could invert for the model using data lacking low-frequency information.

Realistic FDTD GPR Antenna Models Optimized Using a Novel Linear/Nonlinear Full-Waveform Inversion

Finite-difference time-domain forward modeling of ground-penetrating radar (GPR) is becoming regularly used in model-based interpretation methods, such as full-waveform inversion (FWI) and machine learning schemes. Oversimplifications in such forward models can compromise the accuracy and realism with which real GPR responses can be simulated, which degrades the overall performance of interpretation techniques. A forward model must be able to accurately simulate every part of the GPR problem that affects the resulting scattered field. A key element, especially for near-field applications, is the antenna system. Therefore, the model must contain a complete description of the antenna, including the excitation source and waveform, the geometry, and the dielectric properties of any materials in the antenna. The challenge is that some of these parameters are not known or cannot be easily measured, especially for commercial GPR antennas that are used in practice. We present a novel hybrid linear/nonlinear FWI approach that can be used, with only knowledge of the basic antenna geometry, to simultaneously optimize the dielectric properties and excitation waveform of the antenna and minimize the error between real and synthetic data. The accuracy and stability of our proposed methodology are demonstrated by successfully modeling a 1.5-GHz commercial antenna from Geophysical Survey Systems, Inc. Our framework allows accurate models of GPR antennas to be developed without requiring detailed knowledge of every component of the antenna. This is significant because it allows commercial GPR antennas, regularly used in GPR surveys, to be more readily simulated.

Optimal full-waveform inversion strategy for marine data in azimuthally rotated elastic orthorhombic media

The orthorhombic (ORT) anisotropic description of earth layers can allow the capture of much of the earth’s anisotropic complexity. The inversion for high-resolution azimuthal variation of anisotropy is important for reservoir characterization, among other applications. A high-resolution description of the azimuth of fractures can help us to predict flow preferences. To verify the feasibility of multiparameter full-waveform inversion (FWI) for marine data assuming azimuthally rotated elastic ORT media, we have analyzed the radiation patterns and gradient directions of ORT parameters to the reflection data. First, we express the gradient direction of the ORT parameters considering the azimuthal rotation of the symmetric planes. Then, to support our observations in the gradient direction, the radiation patterns of the partial derivative wavefields from each parameter perturbation are also derived under the rotated elastic ORT assumption. To find an optimal parameterization, we compare three different parameterizations: monoclinic, velocity-based, and hierarchical parameterizations. Then, we suggest an optimal multistage update strategy by analyzing the behavior of the rotation angle as a FWI target. To analyze the trade-off among parameters in different parameterizations, we calculate the gradient direction from a hockey-puck model, in which each parameter is perturbed at the different location on a horizontal layer. The trade-off analysis supports that the hierarchical parameterization provides us with more opportunities to build up subsurface models with less trade-off between parameters and less influence of the azimuthal rotation of ORT anisotropy. The feasibility of the proposed FWI strategy is examined using synthetic marine streamer data from a simple 3D reservoir model with a fractured layer.

Characterization of a viscoelastic heterogeneous object with an effective model by nonlinear full waveform inversion

The determination of equivalent viscoelastic properties of heterogeneous objects remains challenging in various scientific fields such as (geo)mechanics, geophysics or biomechanics. The present investigation addresses the issue of the identification of effective constitutive properties of a binary object by using a nonlinear and full waveform inversion scheme. The inversion process, without any regularization technique or a priori information, aims at minimizing directly the discrepancy between the full waveform responses of a bi-material viscoelastic cylindrical object and its corresponding effective homogeneous object. It involves the retrieval of five constitutive equivalent parameters. Numerical simulations are performed in a laboratory-scale two-dimensional configuration: a transient acoustic plane wave impacts the object and the diffracted fluid pressure, solid stress or velocity component fields are determined using a semi-analytical approach. Results show that the retrieval of the density and of the real parts of both the compressional and the shear wave velocities have been carried out successfully regarding the number and location of sensors, the type of sensors, the size of the searching space, the frequency range of the incident plane pressure wave, and the change in the geometric or mechanical constitution of the bi-material object. The retrieval of the imaginary parts of the wave velocities can reveal in some cases the limitations of the proposed approach.

Toward a robust workflow for deep crustal imaging by FWI of OBS data: The eastern Nankai Trough revisited

AbstractCrustal‐scale imaging by the full‐waveform inversion (FWI) of long‐offset seismic data is inherently difficult because the large number of wavelengths propagating through the crust makes the inversion prone to cycle skipping. Therefore, efficient crustal‐scale FWI requires an accurate starting model and a stable workflow minimizing the nonlinearity of the inversion. Here we attempt to reprocess a challenging 2‐D ocean‐bottom seismometer (OBS) data set from the eastern Nankai Trough. The starting model is built by first‐arrival traveltime tomography (FAT), which is FWI assisted for tracking cycle skipping. We iteratively refine the picked traveltimes and then reiterate the FAT until the traveltime residuals remain below the cycle‐skipping limit. Subsequently, we apply Laplace‐Fourier FWI, in which progressive relaxation of time damping is nested within frequency continuation to hierarchically inject more data into the inversion. These two multiscale levels are complemented by a layer‐stripping approach implemented through offset continuation. The reliability of the FWI velocity model is assessed by means of source wavelet estimation, synthetic seismogram modeling, ray tracing modeling, dynamic warping, and checkerboard tests. Although the viscoacoustic approximation is used for wave modeling, the synthetic seismograms reproduce most of the complexity of the data with a high traveltime accuracy. The revised FWI scheme produces a high‐resolution velocity model of the entire crust that can be jointly interpreted with migrated images derived from multichannel seismic data. This study opens a new perspective on the design of OBS crustal‐scale experiments amenable to FWI; however, a further assessment of the optimal OBS spacing is required for reliable FWI.

From classical reflectivity-to-velocity inversion to full-waveform inversion using phase-modified and deconvolved reverse time migration images

To obtain a physical understanding of gradient-based descent methods in full-waveform inversion (FWI), we find a connection between the FWI gradient and the image provided by reverse time migration (RTM). The gradient uses the residual data as a virtual source, and RTM uses the observed data directly as the boundary condition, so the FWI gradient is similar to a time integration of the RTM image using the residual data, which physically converts the phase of the reflectivity to the phase of the velocity. Therefore, gradient-based FWI can be connected to the classical reflectivity-to-velocity/impedance inversion (RVI). We have developed a new FWI scheme that provides a self-contained and physically intuitive derivation, which naturally establishes a connection among the amplitude-preserved RTM, the Zoeppritz equations (amplitude variation with angle inversion), and RVI, and combines them into a single framework to produce a preconditioned inversion formula. In this scheme, the relative velocity update is a phase-modified and deconvolved RTM image obtained with the residual data. Consistent with the deconvolution, the multiscale approach applies a gradually widening low-pass frequency filter to the deconvolved wavelet at early iterations, and then it uses the unfiltered deconvolved wavelet for the final iterations. Our numerical testing determined that the new method makes a significant improvement to the quality of the inversion result.

FWI for model updates in large-contrast media

We describe a new solution for recovering the long-wavelength features of a velocity model in gradient-based full-waveform inversion (FWI). The method uses reflected and transmitted wave modes to recover high-resolution velocity models. The new FWI gradient enables reliable velocity updates deeper than the maximum penetration depth of diving waves and reduces the FWI dependency on recording ultralong offsets. We also discuss a new FWI regularization scheme that overcomes the limitations of the inversion in the presence of high-contrast geobodies and cycle skipping. The solution utilizes a priori information about the earth model in the regularization as an extra term in the objective function. The implementation makes use of the split Bregman method, making it efficient and accurate. Results from applying the new FWI gradient to field data show that we can combine both transmitted and reflected energy in a global FWI scheme to obtain high-resolution velocity models without imprint of the reflectivity on the velocity updates. We illustrate the new regularization method's potential on the BP 2004 velocity benchmark model where our regularized FWI solution is capable of using a simple starting velocity model to deliver a high-quality reconstruction of salt bodies.

A robust gradient for long wavelength FWI updates

We introduce a robust method to produce long wavelength updates in gradient-based Full Waveform Inversion (FWI). The solution introduces dynamic weights in the velocity sensitivity kernel derived from impedance and velocity parameterization of the classical objective function. The new kernel implementation effectively eliminates the migration isochrones produced by the specular reflections, enhances the low wavenumber components in the gradient in heterogeneous media, and is able to deliver velocity updates beyond the penetration depth of diving waves. We use synthetic examples to illustrate how this dynamic weighted FWI gradient successfully recovers the velocity from pre-critical reflections. We also show with dual-sensor streamer data from deep-water Gulf of Mexico how the dynamic weighted FWI gradient can combine both transmitted and reflected energy in a global FWI scheme.

Wavefield compression for adjoint methods in full-waveform inversion

Adjoint methods are a key ingredient of gradient-based full-waveform inversion schemes. While being conceptually elegant, they face the challenge of massive memory requirements caused by the opposite time directions of forward and adjoint simulations and the necessity to access both wavefields simultaneously for the computation of the sensitivity kernel. To overcome this bottleneck, we have developed lossy compression techniques that significantly reduce the memory requirements with only a small computational overhead. Our approach is tailored to adjoint methods and uses the fact that the computation of a sufficiently accurate sensitivity kernel does not require the fully resolved forward wavefield. The collection of methods comprises reinterpolation with a coarse temporal grid as well as adaptively chosen polynomial degree and floating-point precision to represent spatial snapshots of the forward wavefield on hierarchical grids. Furthermore, the first arrivals of adjoint waves are used to identify “shadow zones” that do not contribute to the sensitivity kernel. Numerical experiments show the high potential of this approach achieving an effective compression factor of three orders of magnitude with only a minor reduction in the rate of convergence. Moreover, it is computationally cheap and straightforward to integrate in finite-element wave propagation codes with possible extensions to finite-difference methods.

Building good starting models for full-waveform inversion using adaptive matching filtering misfit

We have proposed a misfit function based on adaptive matching filtering (AMF) to tackle challenges associated with cycle skipping and local minima in full-waveform inversion (FWI). This AMF is designed to measure time-varying phase differences between observations and predictions. Compared with classical least-squares waveform differences, our misfit function behaves as a smooth, quadratic function with a broad basin of attraction. These characters are important because local gradient-based optimization approaches used in most FWI schemes cannot guarantee convergence toward true models if misfit functions include local minima or if the starting model is far away from the global minimum. The 1D and 2D synthetic experiments illustrate the advantages of the proposed misfit function compared with the classical least-squares waveform misfit. Furthermore, we have derived adjoint sources associated with the proposed misfit function and applied them in several 2D time-domain acoustic FWI experiments. Numerical results found that the proposed misfit function can provide good starting models for FWI, particularly when low-frequency signals are absent in recorded data.

Time-lapse full-waveform inversion with ocean-bottom-cable data: Application on Valhall field

Knowledge of changes in reservoir properties resulting from extracting hydrocarbons or injecting fluid is critical to future production planning. Full-waveform inversion (FWI) of time-lapse seismic data provides a quantitative approach to characterize the changes by taking the difference of the inverted baseline and monitor models. The baseline and monitor data sets can be inverted either independently or jointly. Time-lapse seismic data collected by ocean-bottom cables (OBCs) in the Valhall field in the North Sea are suitable for such time-lapse FWI practice because the acquisitions are of a long offset, and the surveys are well-repeated. We have applied independent and joint FWI schemes to two time-lapse Valhall OBC data sets, which were acquired 28 months apart. The joint FWI scheme is double-difference waveform inversion (DDWI), which inverts differenced data (the monitor survey subtracted by the baseline survey) for model changes. We have found that DDWI gave a cleaner and more easily interpreted image of the reservoir changes compared with that obtained with the independent FWI schemes. A synthetic example is used to demonstrate the advantage of DDWI in mitigating spurious estimates of property changes and to provide cross validations for the Valhall data results.

A hierarchical elastic full-waveform inversion scheme based on wavefield separation and the multistep-length approach

Elastic full-waveform inversion (FWI) updates model parameters by minimizing the residuals of the P- and S-wavefields, resulting in more local minima and serious nonlinearity. In addition, the coupling of different parameters degrades the inversion results. To address these problems, we have developed a hierarchical elastic FWI scheme based on wavefield separation and a multistep-length gradient approach. First, we have derived the gradients expressed by different wave modes; analyzed the crosstalk between various parameters; and evaluated the sensitivity of separated P-wave, separated S-wave, and P- and S-wave misfit functions. Then, a practical four-stage inversion workflow was developed. In the first stage, conventional FWI is used to achieve rough estimates of the P- and S-wave velocities. In the second stage, we only invert the P-wave velocity applying the separated P-wavefields when strong S-wave energy is involved, or we merely update the S-wave velocity by matching the separated S-wavefields for the weak S-wave case. The PP and PS gradient formulas are used in these two cases, respectively. Therefore, the nonlinearity of inversion and the crosstalk between parameters are greatly reduced. In the third stage, the multistep-length gradient scheme is adopted. The density structure can be improved owing to the use of individual step lengths for different parameters. In the fourth stage, we make minor adjustments to the recovered P- and S-wave velocities and density by implementing conventional FWI again. Synthetic examples have determined that our hierarchical FWI scheme with the aforementioned steps obtains more plausible models than the conventional method. Inversion results of each stage and any three stages reveal that wavefield decomposition and the multistep-length approach are helpful to improve the accuracy of velocities and density, respectively, and all the stages of our hierarchical FWI method are necessary to give a good recovery of P- and S-wave velocities and density.

Strategy and Application of Waveform Inversion Based on Seismic Data Subset

AbstractThe main difficulty in seismic full waveform inversion (FWI) is the strong nonlinearity, which is caused by the complexity of seismic wave propagation. Different components of elastic parameters result in different characteristics in seismic data. Meanwhile, different inversion quality is required in different stages of exploration or exploitation. So, there is no need to pursue matching all the seismic information during the inversion. Some problems can be solved by matching part of seismic information and the strong nonlinearity can also be avoided by this way. According to this consideration, a generalized FWI strategy and method based on seismic data subsets is presented. For different seismic data subsets, the gradients of the misfits have the same form and can be calculated by two times of seismic wave forward modeling just as traditional FWI. The only difference in calculating the gradients is the adjoint source. During the waveform inversion based on seismic data subsets, the responses of seismic data to different scales of perturbation on different media parameters should be analyzed intensively. Different seismic data subsets should be used in different stages of full waveform inversion. And then the residual of this seismic data subset is back‐projected along the reasonable sub‐kernels to decide where and which component of the model parameter need to be updated. As examples, envelope and reflection data subsets are used in FWI with synthetic and practical data to prove the validity and effectiveness of our presented FWI strategy and method. Especially, in the absence of low frequency contents, reasonable misfits can be used to recover the background compressional and shear velocity models using these FWI methods.

MULTI‐PARAMETER FULL WAVEFORM INVERSION FOR ACOUSTIC VTI MEDIA USING THE TRUNCATED NEWTON METHOD

AbstractIn multi‐parameter full waveform inversion (FWI), the trade‐off between different parameter classes increases its nonlinearity severely. The magnitude orders of seismic velocities and anisotropic parameters are significantly different, which makes the inverse problem poorly conditioned. Judiciously incorporating the inverse Hessian operator into the FWI scheme can help to alleviate the negative impacts of these two problems in the inversion and improve the inversion accuracy. The truncated Newton (TN) method is one of the optimization methods which can better estimate the inverse Hessian operator. This paper studies the simultaneous inversion of two parameters for acoustic VTI media in the time domain using the TN method. Numerical experiments on different models show that in the context of simultaneous inversion of two parameters for acoustic VTI media, the TN method can account for more accurate inverse Hessian operator than the limited memory Broyden‐Fletcher‐Goldfarb‐Shanno (L‐BFGS) method so that it can better balance the updates of two different parameter classes, and reconstruct more accurate parameter models.

Elastic full-waveform inversion using the second-generation wavelet and an adaptive-operator-length scheme

Elastic full-waveform inversion (FWI) can generally yield subsurface model parameters of high spatial resolution. However, the computational and storage burden is tremendous. To mitigate this problem, we developed the following three strategies: First, we derived a time-space-domain adaptive staggered-grid finite-difference method. The size of the calculation was reduced by using smaller operator lengths for high S-wave velocities. Second, we evaluated a multiscale elastic FWI scheme based on the second-generation wavelet, by which scale decompositions of data and model space were implemented. With the scale increasing, spatial sampling intervals and time steps became larger. Therefore, the minimum computational cost could be achieved by combining the variable-operator-length scheme with the multiscale scheme. Third, to economize the memory consumption, we extended the efficient boundary storage and checkpointing schemes into elastic FWI. Only wavefields of several parts in the boundary area between two adjacent checkpoints were stored and used to reconstruct source wavefields of the inner area. Furthermore, the optimal number of checkpoints could be automatically determined by minimizing the amount of storage. We validated these new strategies for the SEG/EAGE overthrust model. The synthetic example suggested the feasibility and robustness of the new elastic FWI method in terms of improving computational efficiency and alleviating large amounts of data storage. We also analyzed the accuracy of our FWI method. The inversion results revealed that our wavelet-based method had better reconstructed structures and higher convergence rate than the conventional filtering-based multiscale FWI method.

Comparison of multifrequency selection strategies for simultaneous-source full-waveform inversion

The computational cost of full-waveform inversion (FWI) is a major obstacle to estimating the velocity model for large-scale problems. One way to reduce the overall cost of waveform inversion is by adopting a simultaneous-source strategy. In other words, multiple sources are simultaneously fired to simulate supershot gathers and thereby reduce the number of seismic modeling simulations that are performed during the inversion. However, the use of simultaneous sources introduces crosstalk artifacts that arise from the interference among the sources that constitute a supershot. We analyzed the influence of different simultaneous multifrequency selection strategies on crosstalk artifacts. Our analysis focused on a frequency-domain FWI algorithm that is implemented with simultaneous sources that are randomly encoded with random time shifts. In the multiscale conventional FWI strategies, a finite set of discrete frequencies was selected and the inversion was carried out sequentially from low- to high-frequency data components. First, the long wavelength components of model parameters were recovered from the low-frequency data, and then more details and features were extracted as the inversion proceeded to the higher frequency data. We examined six frequency selection strategies and tested the performance of the algorithm with encoded data sets. Numerical tests showed that high-fidelity results could be attained by inverting partially overlapped groups of temporal frequencies. Our FWI algorithm is based on a matrix-free Gauss-Newton method. To mitigate crosstalk artifacts during the numerical inversion, a new encoding was generated at every iteration. We also found that high-resolution images can be obtained by resampling new source positions and new encoding functions at every iteration of the FWI algorithm.

Improved Characterization of Fine-Texture Soils Using On-Ground GPR Full-Waveform Inversion

Ground-penetrating radar (GPR) uses the recording of electromagnetic waves and is increasingly applied for a wide range of applications. Traditionally, the main focus was on the analysis of the medium permittivity since estimates of the conductivity using the far-field approximation contain relatively large errors and cannot be interpreted quantitatively. Recently, a full-waveform inversion (FWI) scheme has been developed that is able to reliably estimate permittivity and conductivity values by analyzing reflected waves present in on-ground GPR data. It is based on a frequency-domain solution of Maxwell's equations including far, intermediate, and near fields assuming a 3-D subsurface. Here, we adapt the FWI scheme for on-ground GPR to invert the direct ground wave traveling through the shallow subsurface. Due to possible interference with the airwaves and other reflections, an automated time-domain filter needed to be included in the inversion. In addition to the obtained permittivity and conductivity values, also the wavelet center frequency and amplitude return valuable information that can be used for soil characterization. Combined geophysical measurements were carried out over a silty loam with significant variability in the soil texture. The obtained medium properties are consistent with Theta probe, electromagnetic resistivity tomography, and electromagnetic induction results and enable the formulation of an empirical relationship between soil texture and soil properties. The permittivities and conductivities increase with increasing clay and silt and decreasing skeleton content. Moreover, with increasing permittivities and conductivities, the wavelet center frequency decreases, whereas the wavelet amplitude increases, which is consistent with the radiation pattern and the antenna coupling characteristics.

A recipe for practical full-waveform inversion in anisotropic media: An analytical parameter resolution study

In multiparameter full-waveform inversion (FWI) and specifically one describing the anisotropic behavior of the medium, it is essential that we have an understanding of the parameter resolution possibilities and limits. Because the imaging kernel is at the heart of the inversion engine (the model update), we drew our development and choice of parameters from what we have experienced in imaging seismic data in anisotropic media. In representing the most common (first-order influence and gravity induced) acoustic anisotropy, specifically, a transversely isotropic medium with a vertical symmetry direction (VTI), with the [Formula: see text]-wave normal moveout velocity, anisotropy parameters [Formula: see text], and [Formula: see text], we obtained a perturbation radiation pattern that has limited trade-off between the parameters. Because [Formula: see text] is weakly resolvable from the kinematics of [Formula: see text]-wave propagation, we can use it to play the role that density plays in improving the data fit for an imperfect physical model that ignores the elastic nature of the earth. An FWI scheme that starts from diving waves would benefit from representing the acoustic VTI model with the [Formula: see text]-wave horizontal velocity, [Formula: see text], and [Formula: see text]. In this representation, the diving waves will help us first resolve the horizontal velocity and then reflections, if the nonlinearity is properly handled, could help us resolve [Formula: see text], and [Formula: see text] could help improve the amplitude fit (instead of the density). The model update wavenumber for acoustic anisotropic FWI is very similar to that for the isotropic case, which is mainly dependent on the scattering angle and frequency.

High-resolution quantitative seismic imaging of a strike-slip fault with small vertical offset in clay rocks from underground galleries: Experimental platform of Tournemire, France

Imaging tectonic faults with small vertical offsets in argillites (clay rock) using geophysical methods is challenging. In the context of deep radioactive waste disposals, the presence of such faults has to be assessed because they can modify the rock-confining properties. In the Tournemire Experimental Platform (TEP, Aveyron, France), fault zones with small vertical offsets and complex shape have been identified from underground works. However, 3D high-resolution surface seismic methods have limitations in this context that led us to consider the detection and characterization of the faults directly from underground works. We investigated the potential of seismic full-waveform inversion (FWI) applied in a transmission configuration to image the clay rock medium in a horizontal plane between galleries and compared it with first-arrival traveltime tomography (FATT). Our objective was to characterize seismic velocities of a block of argillites crossed by a subvertical fault zone with a small vertical offset. The specific measurement configuration allowed us to neglect the influence of the galleries on the wave propagation and to simplify the problem by considering a 2D isotropic horizontal imaging domain. Our FWI scheme relied on a robust adaptation of early arrival waveform tomography. The results obtained with FATT and FWI were in accordance, and both correlated with the geologic observations from the gallery walls and boreholes. We found that even though various simplifications was done in the inversion scheme and only a part of the data was used, FWI allowed us to get higher resolution images than FATT, and it was especially less sensitive to the incomplete illumination because it also used diffracted energy. Our results highlighted the complexity of the fault zone, showing a complex interaction of the main fault system with a secondary system composed of decimetric fractures associated with the presence of water.

Quantitative conductivity and permittivity estimation using full-waveform inversion of on-ground GPR data

Conventional ray-based techniques for analyzing common-midpoint (CMP) ground-penetrating radar (GPR) data use part of the measured data and simplified approximations of the reality to return qualitative results with limited spatial resolution. Whereas these methods can give reliable values for the permittivity of the subsurface by employing only the phase information, the far-field approximations used to estimate the conductivity of the ground are not valid for near-surface on-ground GPR, such that the estimated conductivity values are not representative for the area of investigation. Full-waveform inversion overcomes these limitations by using an accurate forward modeling and inverts significant parts of the measured data to return reliable quantitative estimates of permittivity and conductivity. Here, we developed a full-waveform inversion scheme that uses a 3D frequency-domain solution of Maxwell’s equations for a horizontally layered subsurface. Although a straightforward full-waveform inversion is relatively independent of the permittivity starting model, inaccuracies in the conductivity starting model result in erroneous effective wavelet amplitudes and therefore in erroneous inversion results, because the conductivity and wavelet amplitudes are coupled. Therefore, the permittivity and conductivity are updated together with the phase and the amplitude of the source wavelet with a gradient-free optimization approach. This novel full-waveform inversion is applied to synthetic and measured CMP data. In the case of synthetic single layered and waveguide data, where the starting model differs significantly from the true model parameter, we were able to reconstruct the obtained model properties and the effective source wavelet. For measured waveguide data, different starting values returned the same wavelet and quantitative permittivities and conductivities. This novel approach enables the quantitative estimation of permittivity and conductivity for the same sensing volume and enables an improved characterization for a wide range of applications.