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Добірка наукової літератури з теми "Full wavefrom inversion"

Автор: Grafiati
Опубліковано: 5 жовтня 2024

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Статті в журналах з теми "Full wavefrom inversion"

1

Liu, Yike, Bin He, Huiyi Lu, Zhendong Zhang, Xiao-Bi Xie, and Yingcai Zheng. "Full-intensity waveform inversion." GEOPHYSICS 83, no. 6 (November 1, 2018): R649—R658. http://dx.doi.org/10.1190/geo2017-0682.1.

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Анотація:
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.
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2

Ha, Wansoo, and Changsoo Shin. "Laplace-domain full-waveform inversion of seismic data lacking low-frequency information." GEOPHYSICS 77, no. 5 (September 1, 2012): R199—R206. http://dx.doi.org/10.1190/geo2011-0411.1.

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Анотація:
The lack of the low-frequency information in field data prohibits the time- or frequency-domain waveform inversions from recovering large-scale background velocity models. On the other hand, Laplace-domain waveform inversion is less sensitive to the lack of the low frequencies than conventional inversions. In theory, frequency filtering of the seismic signal in the time domain is equivalent to a constant multiplication of the wavefield in the Laplace domain. Because the constant can be retrieved using the source estimation process, the frequency content of the seismic data does not affect the gradient direction of the Laplace-domain waveform inversion. We obtained inversion results of the frequency-filtered field data acquired in the Gulf of Mexico and two synthetic data sets obtained using a first-derivative Gaussian source wavelet and a single-frequency causal sine function. They demonstrated that Laplace-domain inversion yielded consistent results regardless of the frequency content within the seismic data.
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3

Zhang, Tuo, and Christoph Sens-Schönfelder. "Adjoint envelope tomography for scattering and absorption using radiative transfer theory." Geophysical Journal International 229, no. 1 (November 11, 2021): 566–88. http://dx.doi.org/10.1093/gji/ggab457.

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SUMMARY To investigate the small-scale elastic structure of the subsurface at length scales below the resolution limits of waveform tomography, envelopes of high-frequency scattered seismic waveforms have been used with a variety of approaches. However, a rigorous framework for the iterative inversion of seismogram envelopes to image heterogeneity and high-frequency attenuation comparable to full waveform inversion (FWI) is missing. We present the mathematical framework for an iterative full envelope inversion using forward and adjoint simulations of the radiative transfer equations, in full analogy to FWI that is based on the wave equation. The forward and adjoint problems are solved by modelling 2-D multiple non-isotropic scattering in a random elastic medium with spatially variable heterogeneity and attenuation using the Monte Carlo method. Sensitivity kernels are derived for the squared difference between the full observed and modelled envelopes which is iteratively minimized with the L-BFGS method. We apply this algorithm in numerical tests in the acoustic approximation and show that it is possible to image the spatial distribution of small-scale heterogeneity and attenuation in iterative inversions. Our analysis shows that the relative importance of scattering and attenuation anomalies needs to be considered when the model resolution is assessed. The inversions confirm that the early coda is important for imaging the distribution of heterogeneity while later coda waves are more sensitive to intrinsic attenuation and we show that this dependency can be used to cope with the trade-off that exists between both material properties.
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4

AlTheyab, Abdullah, and G. T. Schuster. "Wavefront picking for 3D tomography and full-waveform inversion." GEOPHYSICS 81, no. 6 (November 2016): B201—B210. http://dx.doi.org/10.1190/geo2015-0544.1.

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Анотація:
We have developed an efficient approach for picking first-break wavefronts on coarsely sampled time slices of 3D shot gathers. Our objective was to compute a smooth initial velocity model for multiscale full-waveform inversion (FWI). Using interactive software, first-break wavefronts were geometrically modeled on time slices with a minimal number of picks. We picked sparse time slices, performed traveltime tomography, and then compared the predicted traveltimes with the data in-between the picked slices. The picking interval was refined with iterations until the errors in traveltime predictions fell within the limits necessary to avoid cycle skipping in early arrivals FWI. This approach was applied to a 3D ocean-bottom-station data set. Our results indicate that wavefront picking has 28% fewer data slices to pick compared with picking traveltimes in shot gathers. In addition, by using sparse time samples for picking, data storage is reduced by 88%, and therefore allows for a faster visualization and quality control of the picks. Our final traveltime tomogram is sufficient as a starting model for early arrival FWI.
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5

Smithyman, Brendan R., and Ronald M. Clowes. "Waveform tomography of field vibroseis data using an approximate 2D geometry leads to improved velocity models." GEOPHYSICS 77, no. 1 (January 2012): R33—R43. http://dx.doi.org/10.1190/geo2011-0076.1.

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Анотація:
Waveform tomography, a combination of traveltime tomography (or inversion) and waveform inversion, is applied to vibroseis first-arrival data to generate an interpretable model of P-wave velocity for a site in the Nechako Basin, south-central British Columbia, Canada. We use constrained 3D traveltime inversion followed by 2D full-waveform inversion to process long-offset (14.4 km) first-arrival refraction waveforms, resulting in a velocity model of significantly higher detail than a conventional refraction-statics model generated for a processing workflow. The crooked-line acquisition of the data set makes 2D full-waveform inversion difficult. Thus, a procedure that improves the tractability of waveform tomography processing of vibroseis data recorded on crooked roads is developed to generate a near-surface ([Formula: see text]) velocity model for the study area. The data waveforms are first static corrected using a time shift determined by 3D raytracing, which accounts for the crossline offsets produced by the crooked-line acquisition. The velocity model generated from waveform tomography exhibits substantial improvement when compared with a conventional refraction-statics model. It also shows improved resolution of sharp discontinuities and low-velocity regions when compared to the model from traveltime tomography alone, especially in regions where the geometry errors are moderate. Interpretation of the near-surface velocity model indicates possible subbasins in the Nechako Basin and delineates the Eocene volcanic rocks of the study area. This approach limits the ability of the full-waveform inversion to fit some propagation modes; however, the tractability of the inversion in the near-surface region is improved. This new development is especially useful in studies that do not warrant 3D seismic acquisition and processing.
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6

Xing, Zhen, and Alfredo Mazzotti. "Two-grid full-waveform Rayleigh-wave inversion via a genetic algorithm — Part 2: Application to two actual data sets." GEOPHYSICS 84, no. 5 (September 1, 2019): R815—R825. http://dx.doi.org/10.1190/geo2018-0800.1.

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Анотація:
We have applied our two-grid genetic-algorithm Rayleigh-wave full-waveform inversion (FWI) to two actual data sets acquired in Luni (Italy) and Grenoble (France), respectively. Because our technique used 2D elastic finite-difference modeling for solving the forward problem, the observed data were 3D to 2D corrected prior to the inversion. To limit the computing time, both inversions focused on predicting low-resolution, smooth models by using quite coarse inversion grids. The wavelets for FWI were estimated directly from the observed data by using the Wiener method. In the Luni case, due to the strong dispersion effects on the data, to strengthen the inversion, envelopes and waveforms were considered in the objective function and an offset-marching strategy was applied. Though no a priori information was exploited, the outcomes of the Luni and Grenoble data inversion were fair. The predicted Luni [Formula: see text] model indicates a strong velocity increase from approximately 3 to 6 m, and velocity inversions have been detected at approximately 2 and 9 m depths. Analyzing the dispersion spectra, it results that the predicted Luni data reasonably reproduced the waveforms related to the fundamental mode and, likely, a small part of those related to the first higher mode. Concerning the Grenoble example, the predicted [Formula: see text] model coincides reasonably well with the long-wavelength structures presented in the [Formula: see text] profiles obtained from nearby boreholes. The data reconstruction is generally satisfactory, and when mismatches occur between the predicted and observed traces, the phase differences are always within half-periods. The fair inversion outcomes suggest that the predicted Luni and Grenoble models would likely be adequate initial models for local FWI, which could further increase the resolution and the details of the estimated [Formula: see text] models.
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7

Zhang, Zhen-dong, and Tariq Alkhalifah. "Local-crosscorrelation elastic full-waveform inversion." GEOPHYSICS 84, no. 6 (November 1, 2019): R897—R908. http://dx.doi.org/10.1190/geo2018-0660.1.

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Анотація:
Full-waveform inversion (FWI) in its classic form is a method based on minimizing the [Formula: see text] norm of the difference between the observed and simulated seismic waveforms at the receiver locations. The objective is to find a subsurface model that reproduces the full waveform including the traveltimes and amplitudes of the observed seismic data. However, the widely used [Formula: see text]-norm-based FWI faces many issues in practice. The point-wise comparison of waveforms fails when the phase difference between the compared waveforms of the predicted and observed data is larger than a half-cycle. In addition, amplitude matching is impractical considering the simplified physics that we often use to describe the medium. To avoid these known problems, we have developed a novel elastic FWI algorithm using the local-similarity attribute. It compares two traces within a predefined local time extension; thus, is not limited by the half-cycle criterion. The algorithm strives to maximize the local similarities of the predicted and observed data by stretching/squeezing the observed data. Phases instead of amplitudes of the seismic data are used in the comparison. The algorithm compares two data sets locally; thus, it performs better than the global correlation in matching multiple arrivals. Instead of picking/calculating one stationary stretching/squeezing curve, we used a weighted integral to find all possible stationary curves. We also introduced a polynomial-type weighting function, which is determined only by the predefined maximum stretching/squeezing and is guaranteed to be smoothly varying within the extension range. Compared with the previously used Gaussian or linear weighting functions, our polynomial one has fewer parameters to play around with. A modified synthetic elastic Marmousi model and the North Sea field data are used to verify the effectiveness of the developed approach and also reveal some of its limitations.
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8

Maurer, Hansruedi, Stewart A. Greenhalgh, Edgar Manukyan, Stefano Marelli, and Alan G. Green. "Receiver-coupling effects in seismic waveform inversions." GEOPHYSICS 77, no. 1 (January 2012): R57—R63. http://dx.doi.org/10.1190/geo2010-0402.1.

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Анотація:
Seismic waveform-inversion offers opportunities for detailed characterization of the subsurface. However, its full potential can only be exploited when any systematic source and receiver effects are either carefully avoided or appropriately accounted for during the inversions. Repeated crosshole measurements in the Mont Terri (Switzerland) underground laboratory have revealed that receiver coupling may significantly affect the seismic waveforms. More seriously, coupling conditions may vary during the course of a monitoring experiment. To address this problem, we have developed a novel scheme that estimates medium properties, frequency-dependent source functions, and frequency-dependent receiver-coupling factors. We demonstrate the efficacy of the new scheme via a synthetic 2D crosshole experiment in which realistic receiver-coupling factors are incorporated. Because determination of medium parameters and estimation of source functions and receiver-coupling factors are largely separated, the method can be easily adapted to any other waveform-inversion problem, including elastic, anisotropic, 2.5D, or 3D situations.
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9

Bleibinhaus, Florian, and Stéphane Rondenay. "Effects of surface scattering in full-waveform inversion." GEOPHYSICS 74, no. 6 (November 2009): WCC69—WCC77. http://dx.doi.org/10.1190/1.3223315.

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Анотація:
In full-waveform inversion of seismic body waves, often the free surface is ignored on grounds of computational efficiency. A synthetic study was performed to investigate the effects of this simplification. In terms of size and frequency, the test model and data conform to a real long-offset survey of the upper crust across the San Andreas fault. Random fractal variations are superimposed on a background model with strong lateral and vertical velocity variations ranging from 1200 to 6800 m/s. Synthetic data were computed and inverted for this model and different topographies. A fully viscoelastic time-domain code was used to synthesize the seismograms, and a viscoacoustic frequency-domain code was utilized to invert them. The inversion was focused on early arrivals, which are dominated by P-waves but also contain strong P-Rayleigh wave conversions from the near-field of the receiver. Resulting waveform models show artifacts and a loss of resolution from neglecting the free surface in the inversion, but the inversions are stable, and they still improve the resolution of kinematic models. The extent of deterioration depends more on the subsurface than on the surface structure. Inversion results were improved at no additional expense by introducing a weak contrast along a staircase function above shots and receivers.
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10

Charara, Marwan, and Christophe Barnes. "Constrained Full Waveform Inversion for Borehole Multicomponent Seismic Data." Geosciences 9, no. 1 (January 16, 2019): 45. http://dx.doi.org/10.3390/geosciences9010045.

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Анотація:
Full-waveform inversion for borehole seismic data is an ill-posed problem and constraining the problem is crucial. Constraints can be imposed on the data and model space through covariance matrices. Usually, they are set to a diagonal matrix. For the data space, signal polarization information can be used to evaluate the data uncertainties. The inversion forces the synthetic data to fit the polarization of observed data. A synthetic inversion for a 2D-2C data estimating a 1D elastic model shows a clear improvement, especially at the level of the receivers. For the model space, horizontal and vertical spatial correlations using a Laplace distribution can be used to fill the model space covariance matrix. This approach reduces the degree of freedom of the inverse problem, which can be quantitatively evaluated. Strong horizontal spatial correlation distances favor a tabular geological model whenever it does not contradict the data. The relaxation of the spatial correlation distances from large to small during the iterative inversion process allows the recovery of geological objects of the same size, which regularizes the inverse problem. Synthetic constrained and unconstrained inversions for 2D-2C crosswell data show the clear improvement of the inversion results when constraints are used.
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Дисертації з теми "Full wavefrom inversion"

1

Guo, Gaoshan. "Inversion de la forme d'onde complète à source étendue dans le domaine temporel : théorie, algorithme et application." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ5014.

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Анотація:
La Full waveform inversion (FWI) est devenue la méthode d'imagerie de référence en exploration géophysique. FWI utilise les formes d'ondes complètes pour imager le sous-sol avec une résolution d'un demi longueur d'onde. Etant donné la dimension de l'espace des données et des modèles, la FWI est implémentée avec des méthodes d'optimisation locale sur un espace de recherche réduit où l'équation d'onde est résolue exactement à chaque itération. Cela requiert des modèles initiaux précis pour que les données simulées prédisent les données enregistrées sans saut de phase. Pour relâcher cette condition, plusieurs variantes de la FWI ont été proposées telles que les approches sur des espaces de recherche étendus. Parmi ces approches, la 'Wavefield Reconstruction Inversion (WRI)' implémente l'équation d'onde comme une contrainte faible pour ajuster les observables avec des champs d'onde calculées avec des sources étendues. Les extensions de sources sont estimées en ajustant au sens des moindres carrés la différence entre les données enregistrées et simulées traitées comme les données diffractées enregistrées. Il en résulte que ces sources volumiques sont calculées par renversement temporel (retro-propagation) des résidus déconvolués par le Hessien dans l'espace des données. Cette approche est nommée 'extended-source' FWI (ES-FWI).Dans cette thèse, je développe un algorithme opérationnel pour la ES-FWI. Le premier problème est le calcul des sources volumiques où la déconvolution des résidus par le Hessien est coûteuse. Des études précédentes approximent ce Hessien avec une matrice diagonale ce qui peut suffire dans des contextes favorables mais sujet à des minimums secondaires dans des milieux complexes. Je propose d'approximer l'inverse du Hessien par des filtres de Wiener/Gabor. Des tests numériques sur le modèle Marmousi II démontrent les améliorations apportées par ces filtres comparativement à l'approximation diagonale. Les champs d'ondes calculés avec l'assimilation des données ont une précision qui diminue loin des points de mesure ce qui peut piéger l'inversion dans des minimums secondaires. Pour améliorer la robustesse de la méthode, j'ai implémenté des opérateurs de pondération dans l'espace des données pour injecter progressivement des donnés plus complexes dans l'inversion et reconstruire le milieu de la surface vers les niveaux profonds. Cette approche de 'layer stripping' est illustrée avec les géomodèles complexes 2004 BP Salt et GO3DOBS.La ES-FWI est une forme généralisée de la FWI où l'inverse du Hessien du problème de source est utilisé comme une matrice de pondération dans l'espace des données. Cela engendre une décomposition du Hessien en un opérateur diagonal dans le domaine des sources et un opérateur par source dans l'espace des données représentant le Hessien du problème de source évoqué ci dessus. Je montre comment ré-utiliser cette décomposition dans la FWI pour développer une approximation du Hessien Gauss-Newton qui puisse être calculée efficacement tout en accélérant la convergence de la FWI. Alternativement, l'approximation proposée peut être utilisée comme préconditioneur pour des algorithmes de quasi-Newton.Finalement, j'étends l'application de la reconstruction des champs d'onde avec assimilation des données au problème de ‘redatuming'. Cette application requiert des champs d'ondes de haute précision si bien que j'implémente la déconvolution des données diffractées avec le solveur itératif MINRES plutôt qu'avec des filtres de Gabor. L'approche consiste simplement à calculer les champs d'onde avec l'assimilation des données et à les échantillonner sur la surface d'acquisition virtuelle. Cette approche est précise lorsqu'on connaît le milieu situé entre les surfaces définies par les acquisitions réelle et virtuelle. Le ‘redatuming' des sources et des capteurs peuvent être couplés. Cette approche est illustrée avec des géomodèles marins et terrestres et avec un jeu de données réels de fond de mer
Full waveform inversion (FWI) has emerged as the baseline seismic imaging method in exploration geophysics. Given the size of the data and model spaces, FWI relies on iterative local optimization methods and reduced search space where the wave equation is strictly satisfied at each iteration. This framework requires an accurate initial model allowing for the simulated data to match the recorded data with kinematic errors less than half the period to avoid cycle skipping. To mitigate cycle skipping, several variants of FWI have been developed over the last decade such as extended-space FWI where degrees of freedom are added to the forward problem. Among them, the wavefield reconstruction inversion (WRI) implements the wave equation as a soft constraint to match the data by combining a wave-equation relaxation with data assimilation. While WRI has been initially implemented in the frequency domain where the data-assimilated wavefields can be computed with linear algebra methods, the time-domain implementation with explicit time-marching schemes has proven challenging. It was recently recognized that the source extensions generated by the wave-equation relaxation are the least-squares solutions of the scattered-data fitting problem. As such, they are computed by backward modeling of deconvolved FWI data residuals by the data-domain Hessian. This reformulation of the wavefield reconstruction as a scattering source reconstruction has led to the extended-source FWI (ES-FWI).In this thesis, I develop a practical algorithm for ES-FWI. Firstly, I focus on the efficient computation of the source extensions where the deconvolution of the data residuals by the data-domain Hessian is the main computational bottleneck. Previous studies implement the Hessian with a scaled identity matrix, which is acceptable in certain favorable scenarios but prone to failure in complex media. I propose a more accurate approximation of the inverse Hessian with various matching filters such as 1D/2D Wiener and Gabor filters. Numerical tests conducted on the Marmousi II model show the relevance of these approximations. Moreover, the data-assimilated wavefields primarily consist of the ‘migration/demigration' of the recorded data. Accordingly, their accuracy diminishes away from the receivers, which can drive the inversion towards spurious minima in particular when surface multiples are involved in the inversion. To address this issue, I design a weighting operator based on time-offset windowing in the data misfit function to inject progressively more complex data in the inversion and reconstruct the medium from the shallow parts to the deep ones. The application of the BPsalt model illustrates the relevance of this layer-stripping scheme in a very challenging context.ES-FWI can be recast as a generalized FWI, where the data misfit function is weighted by the inverse data-domain Hessian of the source extension problem. This leads to a decomposition of the Gauss-Newton (GN) Hessian into a diagonal source-side Hessian and source-dependent receiver-side data-domain Hessians. I use this decomposition to propose a computationally efficient approximation of the GN Hessian. I approximate the inverse Hessian with 2D Gabor matching filters, which can be readily used as an approximation of the GN Hessian or as a preconditioner for the quasi-Newton method. Numerical tests demonstrate the improved convergence speed of FWI provided by this Hessian.Finally, I extend the application of the data-assimilated wavefield reconstruction towards seismic redatuming, where highly-accurate wavefield reconstruction is necessary. This prompts me to use the iterative solver to perform the deconvolution of the scattered data. Using reciprocity, I can chain source and receiver redatuming. Numerical tests and application to ocean-bottom seismic data validate the effectiveness of the proposed method
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2

Thomassen, Espen. "Full-waveform inversion studies." Thesis, Norwegian University of Science and Technology, Department of Electronics and Telecommunications, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9722.

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Анотація:

In this master thesis, full-waveform inversion (FWI) was applied to a synthetic, and very complex, geological structure containing a salt body. The main objective was to evaluate the capabilities of FWI to estimate velocities in this context, and more specially below the salt. Seismic depth imaging is now the preferred seismic imaging tool for today's most challenging exploration projects. Seismic depth imaging problem usually requires the definition of a smooth background velocity model before determining the short wavelength component of the structure by pre-stack depth migration. It is well established that success of pre-stack depth migration in complex geological media strongly depends from the definition of the background velocity model. Standard tools for building velocity models generally fail to reconstruct the correct sub-salt velocities. Sub-salt imaging is a very challenging problem and a lot of resources are spent trying to solve this problem, since salt bodies in the sub-surface are known to be very good hydrocarbon traps. In this master thesis, the work have been performed on a modified version of the 2004 BP velocity benchmark model. This model represents a very interesting salt context, where conventional imaging methods can not provide any good results. After describing the seismic inversion problem, and the FWI theory and code used in this work, the application to the 2004 BP benchmark model is described. FWI was first applied to the synthetic data using a starting model derived by smoothing the true velocity model. This is an easy way to ensure an adequate starting model, as the method is very dependent on a good starting model. In the inversion process 17 frequency components were used, ranging between 1 and 15 Hz. This resulted in a velocity model that accurately recovered both the salt body and the sub-salt velocities. The average deviation between the true and estimated sub-salt velocities was found to be approximately 6 %. A more realistic starting model was then derived using first-arrival traveltime tomography, a well known method for obtaining velocity models. FWI was applied to this starting model, and the result was also positive when using this starting model. The salt body was well delineated, whereas the sub-salt velocities were generally more inaccurate than for the previous application. The sub-salt velocity difference was increased to roughly 10 %. However, if more effort had been spent on reconstructing a more accurate starting model, the results might have improved. When fewer frequency components are used in the inversion, the result declined. A test using only 6 frequency components showed that the final reconstructed model suffered from a lack of recovered wavenumbers, especially at the deeper and more complex parts of the model. In such a complex medium as the 2004 BP benchmark model, it is hence necessary to introduce wavenumbers by including a sufficient number of frequency components in the inversion process. Other tests that were conducted showed that, in this particular case, the non-linearity of the inversion problem increased with higher frequencies, and was reduced by larger offset ranges included in the seismic data. The inversion is hence sensitive to the starting frequency as well as the starting model. The results in this master thesis demonstrate that FWI has a great potential in reconstructing sub-salt velocities in salt media. For the future, both applying the method to real data from a salt basin area, and develop a migration tool and test the effect of FWI on a migrated image, are interesting challenges.

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3

Irabor, Kenneth Otabor. "Reflection full waveform inversion." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/60594.

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Анотація:
The Full Waveform Inversion (FWI) gradient is composed of a low wavenumber tomographic component and a high wavenumber migration component. A successful application of FWI requires that the low wavenumber parts of the model be recovered before the high wavenumbers. This process becomes difficult in datasets dominated by pre-critical angle reflection energies. Reflection waveform inversion (RWI) has been proposed as an alternative to help bootstrap the FWI method for reflection data. In this thesis, I have made a novel contribution to RWI using Finite Di fference Explicit Wavefi eld Decomposition (FDEWD). This method improves the wavefi eld decomposition process by cleanly decomposing the wavefi elds into four components using fi nite diff erence method and Fourier transform. Four component wavefi elds travelling left, right, up and down are simultaneously derived in this method compared to just opposite directions possible with most other methods. FDEWD also lacks the evanescent energy present in traditional Fourier based separation. The extra layer of separation introduced by FDEWD ensures that the tomographic component of the gradient is formed by energies propagating within and close to the first Fresnel zone, hence yielding a cleaner tomographic update. The FDEWD method developed here was then used in an RWI context to successfully invert a synthetic dataset and a blind dataset. The scheme involved a migration update step with an exaggerated step length and a tomographic update step with true step length computation. The results obtained shows that the new method produces superior results compared to the method based on direct separation of the total wavefi elds. FDEWD also allows for transmission FWI to be performed without the need to mute the data in any way. We have implemented the scheme here in a 2-D constant density acoustic wave equation. It is, however, possible to extend this method to 3-D, anisotropic and elastic problems.
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4

Guasch, Lluis. "3D elastic full-waveform inversion." Thesis, Imperial College London, 2012. http://hdl.handle.net/10044/1/9974.

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Анотація:
Full Waveform Inversion (FWI) is a depth imaging technique that takes advantage of the full information contained in recorded seismic data. FWI provide high resolution images of subsurface properties, usually seismic velocities or related parameters, although in theory it could image any property used to formulate the wave equation. The computational cost of the methodology has historically limited its application to 3D acoustic approximations but recent developments in hardware capabilities have increased computer power to the point that more realistic approximations are viable. In this work the traditional acoustic approximation is extended to include elastic effects by introducing the elastic wave equation as the governing law that describes wave propagation. I have developed a software based on finite-differences to solve the elastic wave equation in 3D, which I applied in the development of a full-waveform inversion algorithm. The software is fully parallelised for both distributed and shared-memory systems. The first level of parallelisation distributes seismic sources across cluster nodes. Each node solves the 3D elastic wave equation in the whole computational domain. The second level of parallelisation takes advantage of present multi-core computer processor units (CPU) to decompose the computational domain into different volumes that are solved independently by each core. Such parallel design allows the algorithm to handle models of realistic sizes, increasing the computational times only a factor of two compared to those of 3D acoustic full-waveform inversion on the same mesh. I have also implemented a perfectly matched layer absorbing boundary condition to reproduce a semi-infinite model geometry and prevent spurious reflections from the model boundaries from contaminating the modelled wavefields. The inversion algorithm is based upon the adjoint-state method, which I reformulated for the wave equation that I implemented, which was based on particle-velocities and stresses, providing a comparison and demonstration of equivalence with previous developments. To examine the performance of the code, I have inverted several synthetic problems of increasing realism. I have principally used only pressure sources and receivers to assess the potential of the method's application to the most common industry surveys: streamer data for offshore and vertical geophones (only one component) for onshore exploration surveys. The results show that the imaged properties increase with the heterogeneity of the models, due to the increase in P-S-P conversions which provides the main source of information to invert shear-wave velocity models from pressure sources and receivers. It remains to demonstrate the inversion of field datasets and my future research project will focused on achieving this goal.
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5

Debens, Henry Alexander. "Three-dimensional anisotropic full-waveform inversion." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/32407.

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Full-waveform inversion (FWI) is a powerful nonlinear tool for quantitative estimation of high-resolution high-fidelity models of subsurface seismic parameters, typically P-wave velocity. A solution is obtained via a series of iterative local linearised updates to a start model, requiring this model to lie within the basin of attraction of the solution space's global minimum. The consideration of seismic anisotropy during FWI is vital, as it holds influence over both the kinematics and dynamics of seismic waveforms. If not appropriately taken into account, then inadequacies in the anisotropy model are likely to manifest as significant error in the recovered velocity model. Conventionally, anisotropic FWI either employs an a priori anisotropy model, held fixed during FWI, or uses a local inversion scheme to recover anisotropy as part of FWI; both of these methods can be problematic. Constructing an anisotropy model prior to FWI often involves intensive (and hence expensive) iterative procedures. On the other hand, introducing multiple parameters to FWI itself increases the complexity of what is already an underdetermined problem. As an alternative I propose here a novel approach referred to as combined FWI. This uses a global inversion for long-wavelength acoustic anisotropy, involving no start model, while simultaneously updating P-wave velocity using mono-parameter local FWI. Combined FWI is then followed by multi-parameter local FWI to recover the detailed final model. To validate the combined FWI scheme, I evaluate its performance with several 2D synthetic datasets, and apply it to a full 3D field dataset. The synthetic results establish the combined FWI, as part of a two-stage workflow, as more accurate than an equivalent conventional workflow. The solution obtained from the field data reconciles well with in situ borehole measurements. Although combined FWI includes a global inversion, I demonstrate that it is nonetheless affordable and commercially practical for 3D field data.
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6

Kamath, Nishant. "Full-waveform inversion in 2D VTI media." Thesis, Colorado School of Mines, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10116167.

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Full-waveform inversion (FWI) is a technique designed to produce a high-resolution model of the subsurface by using information contained in entire seismic waveforms. This thesis presents a methodology for FWI in elastic VTI (transversely isotropic with a vertical axis of symmetry) media and discusses synthetic results for heterogeneous VTI models.

First, I develop FWI for multicomponent data from a horizontally layered VTI model. The reflectivity method, which permits computation of only PP reflections or a combination of PP and PSV events, is employed to model the data. The Gauss-Newton technique is used to invert for the interval Thomsen parameters, while keeping the densities fixed at the correct values. Eigenvalue/eigenvector decompostion of the Hessian matrix helps analyze the sensitivity of the objective function to the model parameters. Whereas PP data alone are generally sufficient to constrain all four Thomsen parameters even for conventional spreads, including PS reflections provides better constraints, especially for the deeper part of the model.

Next, I derive the gradients of the FWI objective function with respect to the stiffness coefficients of arbitrarily anisotropic media by employing the adjoint-state method. From these expressions, it is straightforward to compute the gradients for parameters of 2D heterogeneous VTI media. FWI is implemented in the time domain with the steepest-descent method used to iteratively update the model. The algorithm is tested on transmitted multicomponent data generated for Gaussian anomalies in Thomsen parameters embedded in homogeneous VTI media.

To test the sensitivity of the objective function to different model parameters, I derive an an- alytic expression for the Fréchet kernel of FWI for arbitrary anisotropic symmetry by using the Born approximation and asymptotic Green’s functions. The amplitude of the kernel, which represents the radiation pattern of a secondary source (that source describes a perturbation in a model parameter), yields the angle-dependent energy scattered by the perturbation. Then the radiation patterns are obtained for anomalies in VTI parameters embedded in isotropic homogeneous media and employed to analyze the inversion results for the transmission FWI experiments.

To understand some of the challenges posed by data recorded in surface surveys, I generate the multicomponent wavefield for a model based on a geologic section of the Valhall Field in the North Sea. A multiscale approach is adopted to perform FWI in the time domain. For the available offset range, diving-wave energy illuminates the top 1.5 km of the section, with the updates in the deeper regions due primarily to the reflections. FWI is tested for three model parameterizations and the results are explained in terms of the P- and SV-radiation patterns described above. These parameterizations lead to different trade-offs, and the choice of parameterization for a given data set depends on the recorded offset range, the quality of the initial model, and the parameter that needs to be recovered most accurately.

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7

Li, Xiang. "Sparsity promoting seismic imaging and full-waveform inversion." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54255.

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This thesis will address the large computational costs of solving least-squares migration and full-waveform inversion problems. Least-squares seismic imaging and full-waveform inversion are seismic inversion techniques that require iterative minimizations of large least-squares misfit functions. Each iteration requires an evaluation of the Jacobian operator and its adjoint, both of which require two wave-equation solves for all sources, creating prohibitive computational costs. In order to reduce costs, we utilize randomized dimensionality reduction techniques, reducing the number of sources used during inversion. The randomized dimensionality reduction techniques create subsampling related artifacts, which we mitigate by using curvelet-domain sparsity-promoting inversion techniques. Our method conducts least-squares imaging at the approximate cost of one reverse-time migration with all sources, and computes the Gauss-Newton full-waveform inversion update at roughly the cost of one gradient update with all sources. Finally, during our research of the full-waveform inversion problem, we discovered that we can utilize our method as an alternative approach to add sparse constraints on the entire velocity model by imposing sparsity constraints on each model update separately, rather than regularizing the total velocity model as typically practiced. We also observed this alternative approach yields a faster decay of the residual and model error as a function of iterations. We provided empirical arguments why and when imposing sparsity on the updates can lead to improved full-waveform inversion results.
Science, Faculty of
Earth, Ocean and Atmospheric Sciences, Department of
Graduate
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8

Roberts, Mark Alvin. "Full waveform inversion of walk-away VSP data." Paris, Institut de physique du globe, 2007. http://www.theses.fr/2007GLOB0020.

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Du fait de l’épuisement des réserves de pétrole, l’exploration et la production sont réalisées dans des environnements de plus en plus complexes. Faire de l’imagerie sismique sous le sel allochtone (par exemple dômes de sel) demeure une tâche difficile à cause du fait contraste de vitesse dentre le sel et les sédiments voisins et les structures très complexes produites par les déplacements de sel. Les nappes de sel allochtone couvrent de nombreuses régions potentiellement productives dans l’offshore profond du Golfe du Mexique. Forer la base du sel est une tâche extrêmement difficile en raison des pressions de pore fortement variables que l’on recontre dans les sédiments sous le sel. Des méthodes sismiques pour estimer la vitesse des ondes sismiques peuvent être employées en même temps que des formules empiriques pour prévoir la pression de pore. Cependant, il est souvent impossible de mesures précises depuis la surface, et nous avons donc employé des données VSP (Vertical Seismic Profile) “walk-away” cela implique d’effectuer plusieurs tirs sismique à diverses distances du forage (géneralement avec un dispositif de canons á air) tout en enregistrement les vitesses mesurees par des geophones placés à des profondeurs appropriées dans le forage. Avant cette thèse, les données étaient traitées en utilisant l’information d’amplitude en fonction de l’angle dans un simple approximation 1D ou en utilisant l’information de temps de parcours (également avec une approximation 1D). Dans cette thèse, j’ai effectué une inversion 2D de forme d’onde pour résoudre le problème d’estimation des vitesses. Cela a l’avantage d’inverser simultanément l’ensemble des données (comprenant les ondes transmises, les ondes refléchies et les ondes converties) et la méthode inclut l’information de temps de parcours et d’amplitude. L’inversion a été exécute avec des méthodes locales d’inversion du fait de la taille du problème inverse et de la difficulté du problème direct. Les problèmes liés aux grandes variations de le sensibilité inhérents à l’acquisition de données, ont conduit à un examen de la méthode de Gauss- Newton et à des matrices, de préconditionnement possibles pour la méthode du gradient conjugué. En raison de la nature mal contrainte du problème inverse, une régularisation a été appliquée avec une méthode de préconditionnement innovatrice. La méthodologie a été appliquée à des données réelles et la pression de pore a été prédite en utilisant l’équation bien établie de Eaton. En outre, les structures sous le sel ont été déterminées, confirment ainsi l’efficacité de cette technique
Depletion of the earth’s hydrocarbon reserves has led to exploration and production in increasingly complex environments. Imaging beneath allochthonous salt (e. G. Salt domes) remains a challenging task for seismic techniques due to the large velocity contrast of the salt with neighbouring sediments and the very complex structures generated by salt movement. Extensive allochthonous salt sheets cover many potentially productive regions in the deep-water Gulf of Mexico. Drilling through the base of salt is an extremely challenging task due to widely varying pore-pressure found in the sediments beneath. Seismic methods to estimate the seismic velocity can be used in conjunction with empirical formula to predict the pore pressure. However, accurate measurements are often not possible from surface reflection seismic data, so walk-away Vertical Seismic Profile (VSP) data has been used. This involves repeatedly firing a seismic source at various distances from the borehole (usually an airgun array) while recording the velocities measured by geophones in the borehole placed at appropriate depths near the base of the salt. Before this thesis, the data had been processed using the amplitude versus angle information in a simple one-dimension approximation or using travel time information (also using a 1D assumption). In this thesis, I have used 2D full waveform inversion to tackle the problem of velocity estimation. This has the advantage of simultaneously inverting the whole dataset (including transmitted waves, reflected waves, converted waves) and the method includes traveltime and amplitude information. The inversion was performed using local inversion methods due to the size of the inverse problem and the cost of the forward problem. Concerns over large sensitivity variations, that are inherent in the data acquisition, have lead to an examination of the Gauss-Newton method and possible preconditioning matrices for the conjugate gradient method. Due to the poorly constrained nature of the inverse problem, a smoothness constraint has been applied with an innovative preconditioning method. The methodology has been applied to real data and the pore pressure has been predicted using the well established Eaton equation. In addition, the sub-salt structure was recovered, further demonstrating the value of this technique
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9

Al-Yaqoobi, Ahmed Musallam Ali. "Full-waveform inversion to 3D seismic land data." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/10927.

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Full-waveform inversion (FWI) is a technique that seeks to find a high-resolution high-fidelity model of the Earth's subsurface that is capable of matching individual seismic waveforms, within an original raw field dataset, trace by trace. The method begins from a best-guess starting model, which is then iteratively improved using a sequence of linearized local inversions to solve a fully non-linear problem. In principle, FWI can be used to recover any physical property that has an influence upon the seismic wavefield, but in practice the technique has been used predominantly to recover P-wave velocity, and this is the route that is followed here. Full-waveform tomographic techniques seek to determine a highly resolved quantitative model of the sub-surface that will ultimately be able to explain the entire seismic wavefield including those phases that conventional processing and migration seek to remove such as refracted arrivals. Although the underlying theory of FWI is well established, its practical application to 3D land data, and especially to seismic data that have been acquired using vibrators, in a form that is effective and robust, is still a subject of intense research. In this study, 2D and 3D FWI techniques have been applied to a vibrator dataset from onshore Oman. Both the raw dataset and the subsurface model cause difficulties for FWI. In particular, the data are noisy, have weak early arrivals, are strongly elastic, and especially are lacking in low-frequency content. The Earth model appears to contain shallow low-velocity layers, and these compromise the use of first-arrival travel-time tomography for the generation of a starting velocity model. The 2D results show good recovery of the shallow part of the velocity models. The results show a low-velocity layer that extends across the velocity model, but lacking in a high-resolution image due to the absence of the third dimension. The seismograms of the final inversion models give a good comparison with the field data and produce a reasonably high correlation coefficient compared to the starting model. An inversion scheme has been developed in this study in which only data from the shorter offsets are initially inverted since these represent the subset of the data that is not cycle skipped. The offset range is then gradually extended as the model improves. The final 3D model contains a strongly developed low-velocity layer in the shallow section. The results from this inversion appear to match p-wave logs from a shallow drill hole, better flatten the gathers, and better stack and migrate the reflection data. The inversion scheme is generic, and should have applications to other similar difficult datasets.
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10

Egorov, Anton. "Full waveform inversion of time-lapse VSP data." Thesis, Curtin University, 2018. http://hdl.handle.net/20.500.11937/79285.

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Vertical seismic profile (VSP) is one of the technologies for monitoring hydrocarbon production and CO2 geosequestration. However, quantitative interpretation of time-lapse VSP is challenging due to its irregular distribution of source-receiver offsets. One way to overcome this challenge is to use full waveform inversion (FWI), which does not require regular offsets. We present a workflow of elastic FWI applied to offset vertical seismic profile data for the purpose of identification and estimation of time-lapse changes introduced by injection of 15,000 t of CO2-rich gas mixture at 1.5 km depth. Application of this workflow to both synthetic and field data shows that elastic FWI is able to detect and quantify the time-lapse anomaly in P wave velocity with the magnitude of 100–150 m/s.
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Книги з теми "Full wavefrom inversion"

1

Chen, Po, and En-Jui Lee. Full-3D Seismic Waveform Inversion. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9.

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2

Fichtner, Andreas. Full Seismic Waveform Modelling and Inversion. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-15807-0.

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service), SpringerLink (Online, ed. Full Seismic Waveform Modelling and Inversion. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Fichtner, Andreas. Full Seismic Waveform Modelling and Inversion. Springer, 2013.

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Fichtner, Andreas. Full Seismic Waveform Modelling and Inversion. Springer, 2011.

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6

Chen, Po, and En-Jui Lee. Full-3D Seismic Waveform Inversion: Theory, Software and Practice. Springer, 2015.

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7

Chen, Po, and En-Jui Lee. Full-3D Seismic Waveform Inversion: Theory, Software and Practice. Springer International Publishing AG, 2016.

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8

Singh, Satish Chandra. Wave propogation in anisotropic media and full waveform inversion. 1987.

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9

Chen, Po, and En-Jui Lee. Full-3D Seismic Waveform Inversion: Theory, Software and Practice. Springer London, Limited, 2015.

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10

Al-Khalifah, Tariq. Full waveform inversion in an anisotropic world Where are the parameters hiding? (EET 10). EAGE Publications bv, 2014. http://dx.doi.org/10.3997/9789073834835.

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Частини книг з теми "Full wavefrom inversion"

1

Hanasoge, Shravan. "Full Waveform Inversion." In SpringerBriefs in Mathematics, 75–103. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27330-3_4.

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2

Köhn, Daniel, Manuel Zolchow, Rebekka Mecking, Dennis Wilken, Tina Wunderlich, Denise De Nil, and Wolfgang Rabbel. "Seismic full waveform inversion in archaeological prospecting." In Advances in On- and Offshore Archaeological Prospection, 31–40. Kiel: Universitätsverlag Kiel | Kiel University Publishing, 2023. http://dx.doi.org/10.38072/978-3-928794-83-1/p4.

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Seismic full waveform inversion is introduced as novel high-resolution imaging tool in archaeological prospection. The full waveform inversion approach allows the high-resolution characterization of low-contrast sedimentary layers, high-contrast stone wall structures and air-filled cavities.
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3

Chen, Po, and En-Jui Lee. "Introduction." In Full-3D Seismic Waveform Inversion, 1–14. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9_1.

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4

Chen, Po, and En-Jui Lee. "Anelastic Wave Propagation (AWP)." In Full-3D Seismic Waveform Inversion, 15–90. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9_2.

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Chen, Po, and En-Jui Lee. "Green’s Functions." In Full-3D Seismic Waveform Inversion, 91–190. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9_3.

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Chen, Po, and En-Jui Lee. "Data Sensitivity Kernels." In Full-3D Seismic Waveform Inversion, 191–310. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9_4.

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Chen, Po, and En-Jui Lee. "Optimization Algorithms." In Full-3D Seismic Waveform Inversion, 311–43. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9_5.

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Chen, Po, and En-Jui Lee. "CVM-S4.26." In Full-3D Seismic Waveform Inversion, 345–509. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16604-9_6.

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9

Fichtner, Andreas. "Preliminaries." In Full Seismic Waveform Modelling and Inversion, 1–5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_1.

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10

Fichtner, Andreas. "The Frequency-Domain Discrete Adjoint Method." In Full Seismic Waveform Modelling and Inversion, 189–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15807-0_10.

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Тези доповідей конференцій з теми "Full wavefrom inversion"

1

Liu, Hai, Zhijun Long, Chen Qiu, Feng Han, and Qing Huo Liu. "Reverse-time migration and full wavefrom inversion for subsurface imaging." In 2016 Progress in Electromagnetic Research Symposium (PIERS). IEEE, 2016. http://dx.doi.org/10.1109/piers.2016.7734272.

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2

Fuse, S., H. Mikada, and J. Takekawa. "Full Waveform Inversion of Cross-Dipole Acoustic Waveforms." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2016. http://dx.doi.org/10.2523/18726-ms.

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Fuse, S., H. Mikada, and J. Takekawa. "Full Waveform Inversion of Cross-Dipole Acoustic Waveforms." In International Petroleum Technology Conference. International Petroleum Technology Conference, 2016. http://dx.doi.org/10.2523/iptc-18726-ms.

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4

Allemand, T., and G. Lambaré. "Combining Full Waveform Inversion and Tomography: Full Waveform Inversion-guided Tomography." In 77th EAGE Conference and Exhibition 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201412591.

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5

Mardan, A., B. Giroux, and G. Fabien-Ouellet. "Time-Lapse Seismic Full Waveform Inversion Using Improved Cascaded Method." In Second EAGE Conference on Seismic Inversion. European Association of Geoscientists & Engineers, 2022. http://dx.doi.org/10.3997/2214-4609.202229003.

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6

Jiao*, Kun, Dong Sun, Xin Cheng, and Denes Vigh. "Adjustive full waveform inversion." In SEG Technical Program Expanded Abstracts 2015. Society of Exploration Geophysicists, 2015. http://dx.doi.org/10.1190/segam2015-5901541.1.

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7

Kadu, A., and R. Kumar. "Decentralized Full-Waveform Inversion." In 80th EAGE Conference and Exhibition 2018. Netherlands: EAGE Publications BV, 2018. http://dx.doi.org/10.3997/2214-4609.201801230.

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8

Zhang, X., and A. Curtis. "Variational Full Waveform Inversion." In 2nd EAGE Workshop on Quantifying Uncertainty in Depth Imaging. European Association of Geoscientists & Engineers, 2023. http://dx.doi.org/10.3997/2214-4609.202379012.

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9

Bai, J., and O. Yilmaz. "Full-Waveform Imaging Inversion." In 85th EAGE Annual Conference & Exhibition - Workshop Programme. European Association of Geoscientists & Engineers, 2024. http://dx.doi.org/10.3997/2214-4609.202410904.

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10

Qu, Y. M., J. P. Huang, Z. C. Li, Y. T. Han, and Q. Y. Li. "A Joint Waveform Inversion Strategy - Combing Full Waveform Inversion with Prismatic Waveform Inversion." In 77th EAGE Conference and Exhibition 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201412766.

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Звіти організацій з теми "Full wavefrom inversion"

1

Preston, Leiph. Computation of Kernels for Full Waveform Seismic Inversion Using Parelasti. Office of Scientific and Technical Information (OSTI), August 2018. http://dx.doi.org/10.2172/1468379.

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2

Simmons, N., and C. Morency. Report on the LLNL Global Full-waveform Inversion Workflow and Progress. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1813693.

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3

Pan, Wenyong. Multiparameter full-waveform inversion in complex media applied to walk-away vertical seismic profile data. Office of Scientific and Technical Information (OSTI), December 2018. http://dx.doi.org/10.2172/1489919.

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