scholarly journals Evolutionary full-waveform inversion

2020 ◽  
Vol 224 (1) ◽  
pp. 306-311
Author(s):  
Dirk Philip van Herwaarden ◽  
Michael Afanasiev ◽  
Solvi Thrastarson ◽  
Andreas Fichtner
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Data Set ◽  
New Approach ◽  
Full Waveform ◽  
Upper Mantle Structure ◽  
Data Coverage ◽  
D Model

SUMMARY We present a new approach to full-waveform inversion (FWI) that enables the assimilation of data sets that expand over time without the need to reinvert all data. This evolutionary inversion rests on a reinterpretation of stochastic Limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS), which randomly exploits redundancies to achieve convergence without ever considering the data set as a whole. Specifically for seismological applications, we consider a dynamic mini-batch stochastic L-BFGS, where the size of mini-batches adapts to the number of sources needed to approximate the complete gradient. As an illustration we present an evolutionary FWI for upper-mantle structure beneath Africa. Starting from a 1-D model and data recorded until 1995, we sequentially add contemporary data into an ongoing inversion, showing how (i) new events can be added without compromising convergence, (ii) a consistent measure of misfit can be maintained and (iii) the model evolves over times as a function of data coverage. Though applied retrospectively in this example, our method constitutes a possible approach to the continuous assimilation of seismic data volumes that often tend to grow exponentially.

scholarly journals Semiglobal viscoacoustic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (2) ◽  
pp. R271-R293 ◽  
Author(s):  
Nuno V. da Silva ◽  
Gang Yao ◽  
Michael Warner
Keyword(s):  
Physical Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Waveform Inversion ◽  
P Wave ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Intrinsic Attenuation ◽  
Full Waveform ◽  
P Wave Velocity

Full-waveform inversion deals with estimating physical properties of the earth’s subsurface by matching simulated to recorded seismic data. Intrinsic attenuation in the medium leads to the dispersion of propagating waves and the absorption of energy — media with this type of rheology are not perfectly elastic. Accounting for that effect is necessary to simulate wave propagation in realistic geologic media, leading to the need to estimate intrinsic attenuation from the seismic data. That increases the complexity of the constitutive laws leading to additional issues related to the ill-posed nature of the inverse problem. In particular, the joint estimation of several physical properties increases the null space of the parameter space, leading to a larger domain of ambiguity and increasing the number of different models that can equally well explain the data. We have evaluated a method for the joint inversion of velocity and intrinsic attenuation using semiglobal inversion; this combines quantum particle-swarm optimization for the estimation of the intrinsic attenuation with nested gradient-descent iterations for the estimation of the P-wave velocity. This approach takes advantage of the fact that some physical properties, and in particular the intrinsic attenuation, can be represented using a reduced basis, substantially decreasing the dimension of the search space. We determine the feasibility of the method and its robustness to ambiguity with 2D synthetic examples. The 3D inversion of a field data set for a geologic medium with transversely isotropic anisotropy in velocity indicates the feasibility of the method for inverting large-scale real seismic data and improving the data fitting. The principal benefits of the semiglobal multiparameter inversion are the recovery of the intrinsic attenuation from the data and the recovery of the true undispersed infinite-frequency P-wave velocity, while mitigating ambiguity between the estimated parameters.

Full waveform inversion and distance separated simultaneous sweeping: a study with a land seismic data set

2012 ◽  
Vol 60 (4) ◽  
pp. 733-747 ◽  
Author(s):  
René-Édouard Plessix ◽  
Guido Baeten ◽  
Jan Willem de Maag ◽  
Fons ten Kroode ◽  
Zhang Rujie
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform

Applications of low-rank compressed seismic data to full-waveform inversion and extended image volumes

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. R371-R383 ◽  
Author(s):  
Curt Da Silva ◽  
Yiming Zhang ◽  
Rajiv Kumar ◽  
Felix J. Herrmann
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Waveform Inversion ◽  
Extraction Process ◽  
Low Rank ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform ◽  
Computational Resources ◽  
Compressed Data

Conventional oil and gas fields are increasingly difficult to explore and image, resulting in the call for more complex wave-equation-based inversion algorithms that require dense long-offset samplings. Consequently, there is an exponential growth in the size of data volumes and prohibitive demands on computational resources. We have developed a method to compress and process seismic data directly in a low-rank tensor format, which drastically reduces the amount of storage required to represent the data. Seismic data exhibit a low-rank structure in a particular transform domain, which can be exploited to compress the dense data in one extremely storage-efficient tensor format when the data are fully sampled or can be interpolated when the data have missing entries. In either case, once our data are represented in the compressed tensor form, we have developed an algorithm to extract source or receiver gathers directly from the compressed parameters. This extraction process can be done on the fly directly on the compressed data, and it does not require scanning through the entire data set to form shot gathers. We apply this shot-extraction technique in the context of stochastic full-waveform inversion as well as forming full subsurface image gathers through probing techniques and reveal the minor differences between using the full and compressed data, while drastically reducing the total memory costs.

scholarly journals Regularized full-waveform inversion with automated salt flooding

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. R569-R582 ◽  
Author(s):  
Mahesh Kalita ◽  
Vladimir Kazei ◽  
Yunseok Choi ◽  
Tariq Alkhalifah
Keyword(s):  
Optimization Problem ◽  
Waveform Inversion ◽  
Dominant Frequency ◽  
Model Parameters ◽  
Constant Density ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Low Frequencies ◽  
Full Waveform

Full-waveform inversion (FWI) attempts to resolve an ill-posed nonlinear optimization problem to retrieve the unknown subsurface model parameters from seismic data. In general, FWI fails to obtain an adequate representation of models with large high-velocity structures over a wide region, such as salt bodies and the sediments beneath them, in the absence of low frequencies in the recorded seismic signal, due to nonlinearity and nonuniqueness. We alleviate the ill posedness of FWI associated with data sets affected by salt bodies using model regularization. We have split the optimization problem into two parts: First, we minimize the data misfit and the total variation in the model, seeking to achieve an inverted model with sharp interfaces; and second, we minimize sharp velocity drops with depth in the model. Unlike conventional industrial salt flooding, our technique requires minimal human intervention and no information about the top of the salt. Those features are demonstrated on data sets of the BP 2004 and Sigsbee2A models, synthesized from a Ricker wavelet of dominant frequency 5.5 Hz and minimum frequency 3 Hz. We initiate the inversion process with a simple model in which the velocity increases linearly with depth. The model is well-retrieved when the same constant density acoustic code is used to simulate the observed data, which is still one of the most common FWI tests. Moreover, our technique allows us to reconstruct a reasonable depiction of the salt structure from the data synthesized independently with the BP 2004 model with variable density. In the Sigsbee2A model, we manage to even capture some of the fine layering beneath the salt. In addition, we evaluate the versatility of our method on a field data set from the Gulf of Mexico.

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

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. R225-R235 ◽  
Author(s):  
Di Yang ◽  
Faqi Liu ◽  
Scott Morton ◽  
Alison Malcolm ◽  
Michael Fehler
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Time Lapse ◽  
Double Difference ◽  
Baseline Survey ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Ocean Bottom ◽  
Full Waveform ◽  
Future Production

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.

scholarly journals Acoustic full-waveform inversion in an elastic world

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. R257-R271 ◽  
Author(s):  
Òscar Calderón Agudo ◽  
Nuno Vieira da Silva ◽  
Michael Warner ◽  
Joanna Morgan
Keyword(s):  
Wave Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
P Wave ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Velocity Models ◽  
Full Waveform ◽  
Elastic Data

Full-waveform inversion (FWI) is a technique used to obtain high-quality velocity models of the subsurface. Despite the elastic nature of the earth, the anisotropic acoustic wave equation is typically used to model wave propagation in FWI. In part, this simplification is essential for being efficient when inverting large 3D data sets, but it has the adverse effect of reducing the accuracy and resolution of the recovered P-wave velocity models, as well as a loss in potential to constrain other physical properties, such as the S-wave velocity given that amplitude information in the observed data set is not fully used. Here, we first apply conventional acoustic FWI to acoustic and elastic data generated using the same velocity model to investigate the effect of neglecting the elastic component in field data and we find that it leads to a loss in resolution and accuracy in the recovered velocity model. Then, we develop a method to mitigate elastic effects in acoustic FWI using matching filters that transform elastic data into acoustic data and find that it is applicable to marine and land data sets. Tests show that our approach is successful: The imprint of elastic effects on the recovered P-wave models is mitigated, leading to better-resolved models than those obtained after conventional acoustic FWI. Our method requires a guess of [Formula: see text] and is marginally more computationally demanding than acoustic FWI, but much less so than elastic FWI.

Innovative application of full-waveform inversion applied to extended wide-azimuth marine streamer seismic in a complex salt environment

Geophysics ◽  
2022 ◽  
pp. 1-51
Author(s):  
Peter Lanzarone ◽  
Xukai Shen ◽  
Andrew Brenders ◽  
Ganyuan Xia ◽  
Joe Dellinger ◽  
...  
Keyword(s):  
Seismic Data ◽  
Model Building ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Complex Salt ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform ◽  
Velocity Model Building ◽  
Reservoir Systems

We demonstrated the application of full-waveform inversion (FWI) guided velocity model building to an extended wide-azimuth towed streamer (EWATS) seismic data set in the Gulf of Mexico. Field data were collected over a historically challenging imaging area, colloquially called the “grunge zone” due to the formation of a compressional allosuture emplaced between two colliding salt sheets. These data had a poor subsalt image below the suture with conventional narrow-azimuth data. Additional geologic complexities were observed including high-velocity carbonate carapace near the top of salt and multiple intrasalt sedimentary inclusions. As such, improved seismic imaging was required to plan and execute wells targeting subsalt strata. Significant improvements to the velocity model and subsalt image were evident with wide-azimuth towed streamer and later EWATS data using conventional top-down velocity model building approaches. Then, high-impact improvements were made using EWATS data with an FWI velocity model building workflow; this study represented an early successful application of FWI used to update salt body geometries from streamer seismic data, in which many past applications were limited to improving sedimentary velocities. Later petrophysical data verified the new FWI-derived model, which had significantly increased confidence in the structural and stratigraphic interpretation of subsalt reservoir systems below the grunge zone.

Lower crustal structures at Rockall Trough (west of Ireland) by Full waveform inversion

2020 ◽  
Author(s):  
Gaurav Tomar ◽  
Christopher J. Bean ◽  
Satish C. Singh
Keyword(s):  
Travel Time ◽  
Seismic Data ◽  
High Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Full Waveform ◽  
Travel Time Tomography ◽  
Rockall Trough

<p>Rockall trough lies to the west of Ireland in NE Atlantic, it has a complex geology and has been debated for controversial geology for more than two decades. We have performed Full waveform inversion (FWI) on 2D seismic data set that is recorded in 2013-14 by using 10 km long streamer, this 2D seismic line is situated near the North-West margin in the Rockall Bank area. Full waveform inversion (FWI) is a powerful technique for obtaining elastic properties of the sub-surface from the seismic data. FWI provides properties of the sub-surface at the scale of the wavelength of the data set. We used travel time tomography on downward extrapolated data set to obtain a smooth starting velocity model for FWI. Downward continuation is a technique that enhances the first arrival and also reduces the computation time for forward modelling in FWI. The velocity model obtained from refraction travel time tomography, indicates the velocity from 1.6-4 km/s for the sediments and we have also observed very high velocity ~ 6-7.5 km/s just 3 km below sea-floor. We have performed FWI using these TTT velocity model as a starting model and inverted the refractions along with the wide angle reflections in the frequency range of 3-10 hz. FWI results gives the velocity of 6-7.2 km/s as well as defines geological structures that can be seen in the migrated seismic section. These high velocity structures could be a part of the continental crust and/or lower oceanic crustal igneous rocks like Gabbro.</p>

scholarly journals Full-Waveform Inversion for Imaging Faulted Structures: A Case Study from the Japan Trench Forearc Slope

2021 ◽  
Author(s):  
Ehsan Jamali Hondori ◽  
Chen Guo ◽  
Hitoshi Mikada ◽  
Jin-Oh Park
Keyword(s):  
Seismic Data ◽  
Initial Velocity ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Control Measures ◽  
Japan Trench ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Time Migration ◽  
Shallow Sediments

AbstractFull-waveform inversion (FWI) of limited-offset marine seismic data is a challenging task due to the lack of refracted energy and diving waves from the shallow sediments, which are fundamentally required to update the long-wavelength background velocity model in a tomographic fashion. When these events are absent, a reliable initial velocity model is necessary to ensure that the observed and simulated waveforms kinematically fit within an error of less than half a wavelength to protect the FWI iterative local optimization scheme from cycle skipping. We use a migration-based velocity analysis (MVA) method, including a combination of the layer-stripping approach and iterations of Kirchhoff prestack depth migration (KPSDM), to build an accurate initial velocity model for the FWI application on 2D seismic data with a maximum offset of 5.8 km. The data are acquired in the Japan Trench subduction zone, and we focus on the area where the shallow sediments overlying a highly reflective basement on top of the Cretaceous erosional unconformity are severely faulted and deformed. Despite the limited offsets available in the seismic data, our carefully designed workflow for data preconditioning, initial model building, and waveform inversion provides a velocity model that could improve the depth images down to almost 3.5 km. We present several quality control measures to assess the reliability of the resulting FWI model, including ray path illuminations, sensitivity kernels, reverse time migration (RTM) images, and KPSDM common image gathers. A direct comparison between the FWI and MVA velocity profiles reveals a sharp boundary at the Cretaceous basement interface, a feature that could not be observed in the MVA velocity model. The normal faults caused by the basal erosion of the upper plate in the study area reach the seafloor with evident subsidence of the shallow strata, implying that the faults are active.

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