Long-wavelength FWI updates in the presence of cycle skipping

2019 ◽  
Vol 38 (3) ◽  
pp. 193-196 ◽  
Author(s):  
Jaime Ramos-Martínez ◽  
Lingyun Qiu ◽  
Alejandro A. Valenciano ◽  
Xiaoyan Jiang ◽  
Nizar Chemingui

Full-waveform inversion (FWI) has become the tool of choice for building high-resolution velocity models. Its success depends on producing seamless updates of the short- and long-wavelength model features while avoiding cycle skipping. Classic FWI implementations use the L2 norm to measure the data misfit in combination with a gradient computed by a crosscorrelation imaging condition of the source and residual wavefields. The algorithm risks converging to an inaccurate result if the data lack low frequencies and/or the initial model is far from the true one. Additionally, the model updates may display a reflectivity imprint before the long-wavelength features of the model are fully recovered. We propose a new solution to this fundamental challenge by combining the quadratic form of the Wasserstein distance (W2 norm) for measuring the data misfit with a robust implementation of a velocity gradient. The W2 norm reduces the risk of cycle skipping, whereas the velocity gradient effectively eliminates the reflectivity imprint and emphasizes the long-wavelength model updates. We illustrate the performance of the new solution on a field survey acquired offshore Brazil. We demonstrate how FWI successfully updates the earth model and resolves a high-velocity carbonate section missing from the initial velocity model.

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. R223-R233 ◽  
Author(s):  
Yong Ma ◽  
Dave Hale

In reflection seismology, full-waveform inversion (FWI) can generate high-wavenumber subsurface velocity models but often suffers from an objective function with local minima caused mainly by the absence of low frequencies in seismograms. These local minima cause cycle skipping when the low-wavenumber component in the initial velocity model for FWI is far from the true model. To avoid cycle skipping, we discovered a new wave-equation reflection traveltime inversion (WERTI) to update the low-wavenumber component of the velocity model, while using FWI to only update high-wavenumber details of the model. We implemented the low- and high-wavenumber inversions in an alternating way. In WERTI, we used dynamic image warping (DIW) to estimate the time shifts between recorded data and synthetic data. When compared with correlation-based techniques often used in traveltime estimation, DIW can avoid cycle skipping and estimate the time shifts accurately, even when shifts vary rapidly. Hence, by minimizing traveltime shifts estimated by dynamic warping, WERTI reduces errors in reflection traveltime inversion. Then, conventional FWI uses the low-wavenumber component estimated by WERTI as a new initial model and thereby refines the model with high-wavenumber details. The alternating combination of WERTI and FWI mitigates the velocity-depth ambiguity and can recover subsurface velocities using only high-frequency reflection data.


2021 ◽  
Vol 40 (5) ◽  
pp. 324-334
Author(s):  
Rongxin Huang ◽  
Zhigang Zhang ◽  
Zedong Wu ◽  
Zhiyuan Wei ◽  
Jiawei Mei ◽  
...  

Seismic imaging using full-wavefield data that includes primary reflections, transmitted waves, and their multiples has been the holy grail for generations of geophysicists. To be able to use the full-wavefield data effectively requires a forward-modeling process to generate full-wavefield data, an inversion scheme to minimize the difference between modeled and recorded data, and, more importantly, an accurate velocity model to correctly propagate and collapse energy of different wave modes. All of these elements have been embedded in the framework of full-waveform inversion (FWI) since it was proposed three decades ago. However, for a long time, the application of FWI did not find its way into the domain of full-wavefield imaging, mostly owing to the lack of data sets with good constraints to ensure the convergence of inversion, the required compute power to handle large data sets and extend the inversion frequency to the bandwidth needed for imaging, and, most significantly, stable FWI algorithms that could work with different data types in different geologic settings. Recently, with the advancement of high-performance computing and progress in FWI algorithms at tackling issues such as cycle skipping and amplitude mismatch, FWI has found success using different data types in a variety of geologic settings, providing some of the most accurate velocity models for generating significantly improved migration images. Here, we take a step further to modify the FWI workflow to output the subsurface image or reflectivity directly, potentially eliminating the need to go through the time-consuming conventional seismic imaging process that involves preprocessing, velocity model building, and migration. Compared with a conventional migration image, the reflectivity image directly output from FWI often provides additional structural information with better illumination and higher signal-to-noise ratio naturally as a result of many iterations of least-squares fitting of the full-wavefield data.


Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. KS59-KS69 ◽  
Author(s):  
Chao Song ◽  
Zedong Wu ◽  
Tariq Alkhalifah

Passive seismic monitoring has become an effective method to understand underground processes. Time-reversal-based methods are often used to locate passive seismic events directly. However, these kinds of methods are strongly dependent on the accuracy of the velocity model. Full-waveform inversion (FWI) has been used on passive seismic data to invert the velocity model and source image, simultaneously. However, waveform inversion of passive seismic data uses mainly the transmission energy, which results in poor illumination and low resolution. We developed a waveform inversion using multiscattered energy for passive seismic to extract more information from the data than conventional FWI. Using transmission wavepath information from single- and double-scattering, computed from a predicted scatterer field acting as secondary sources, our method provides better illumination of the velocity model than conventional FWI. Using a new objective function, we optimized the source image and velocity model, including multiscattered energy, simultaneously. Because we conducted our method in the frequency domain with a complex source function including spatial and wavelet information, we mitigate the uncertainties of the source wavelet and source origin time. Inversion results from the Marmousi model indicate that by taking advantage of multiscattered energy and starting from a reasonably acceptable frequency (a single source at 3 Hz and multiple sources at 5 Hz), our method yields better inverted velocity models and source images compared with conventional FWI.


Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. R411-R427 ◽  
Author(s):  
Gang Yao ◽  
Nuno V. da Silva ◽  
Michael Warner ◽  
Di Wu ◽  
Chenhao Yang

Full-waveform inversion (FWI) is a promising technique for recovering the earth models for exploration geophysics and global seismology. FWI is generally formulated as the minimization of an objective function, defined as the L2-norm of the data residuals. The nonconvex nature of this objective function is one of the main obstacles for the successful application of FWI. A key manifestation of this nonconvexity is cycle skipping, which happens if the predicted data are more than half a cycle away from the recorded data. We have developed the concept of intermediate data for tackling cycle skipping. This intermediate data set is created to sit between predicted and recorded data, and it is less than half a cycle away from the predicted data. Inverting the intermediate data rather than the cycle-skipped recorded data can then circumvent cycle skipping. We applied this concept to invert cycle-skipped first arrivals. First, we picked up the first breaks of the predicted data and the recorded data. Second, we linearly scaled down the time difference between the two first breaks of each shot into a series of time shifts, the maximum of which was less than half a cycle, for each trace in this shot. Third, we moved the predicted data with the corresponding time shifts to create the intermediate data. Finally, we inverted the intermediate data rather than the recorded data. Because the intermediate data are not cycle-skipped and contain the traveltime information of the recorded data, FWI with intermediate data updates the background velocity model in the correct direction. Thus, it produces a background velocity model accurate enough for carrying out conventional FWI to rebuild the intermediate- and short-wavelength components of the velocity model. Our numerical examples using synthetic data validate the intermediate-data concept for tackling cycle skipping and demonstrate its effectiveness for the application to first arrivals.


Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. R81-R93 ◽  
Author(s):  
Haiyang Wang ◽  
Satish C. Singh ◽  
Francois Audebert ◽  
Henri Calandra

Long-wavelength velocity model building is a nonlinear process. It has traditionally been achieved without appealing to wave-equation-based approaches for combined refracted and reflected waves. We developed a cascaded wave-equation tomography method in the data domain, taking advantage of the information contained in the reflected and refracted waves. The objective function was the traveltime residual that maximized the crosscorrelation function between real and synthetic data. To alleviate the nonlinearity of the inversion problem, refracted waves were initially used to provide vertical constraints on the velocity model, and reflected waves were then included to provide lateral constraints. The use of reflected waves required scale separation. We separated the long- and short-wavelength subsurface structures into velocity and density models, respectively. The velocity model update was restricted to long wavelengths during the wave-equation tomography, whereas the density model was used to absorb all the short-wavelength impedance contrasts. To improve the computation efficiency, the density model was converted into the zero-offset traveltime domain, where it was invariant to changes of the long-wavelength velocity model. After the wave-equation tomography has derived an optimized long-wavelength velocity model, full-waveform inversion was used to invert all the data to retrieve the short-wavelength velocity structures. We developed our method in two synthetic tests and then applied it to a marine field data set. We evaluated the results of the use of refracted and reflected waves, which was critical for accurately building the long-wavelength velocity model. We showed that our wave-equation tomography strategy was robust for the real data application.


2011 ◽  
Author(s):  
Henri Calandra ◽  
Christian Rivera ◽  
Changsoo Shin ◽  
Sukjoon Pyun ◽  
Youngseo Kim ◽  
...  

2016 ◽  
Vol 4 (4) ◽  
pp. SU17-SU24 ◽  
Author(s):  
Vanessa Goh ◽  
Kjetil Halleland ◽  
René-Édouard Plessix ◽  
Alexandre Stopin

Reducing velocity inaccuracy in complex settings is of paramount importance for limiting structural uncertainties, therefore helping the geologic interpretation and reservoir characterization. Shallow velocity variations due, for instance, to gas accumulations or carbonate reefs, are a common issue offshore Malaysia. These velocity variations are difficult to image through standard reflection-based velocity model building. We have applied full-waveform inversion (FWI) to better characterize the upper part of the earth model for a shallow-water field, located in the Central Luconia Basin offshore Sarawak. We have inverted a narrow-azimuth data set with a maximum inline offset of 4.4 km. Thanks to dedicated broadband preprocessing of the data set, we could enhance the signal-to-noise ratio in the 2.5–10 Hz frequency band. We then applied a multiparameter FWI to estimate the background normal moveout velocity and the [Formula: see text]-parameter. Full-waveform inversion together with broadband data processing has helped to better define the faults and resolve the thin layers in the shallow clastic section. The improvements in the velocity model brought by FWI lead to an improved image of the structural closure and flanks. Moreover, the increased velocity resolution helps in distinguishing between two different geologic interpretations.


2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Katherine Flórez ◽  
Sergio Alberto Abreo Carrillo ◽  
Ana Beatriz Ramírez Silva

Full Waveform Inversion (FWI) schemes are gradually becoming more common in the oil and gas industry, as a new tool for studying complex geological zones, based on their reliability for estimating velocity models. FWI is a non-linear inversion method that iteratively estimates subsurface characteristics such as seismic velocity, starting from an initial velocity model and the preconditioned data acquired. Blended sources have been used in marine seismic acquisitions to reduce acquisition costs, reducing the number of times that the vessel needs to cross the exploration delineation trajectory. When blended or simultaneous without previous de-blending or separation, stage data are used in the reconstruction of the velocity model with the FWI method, and the computational time is reduced. However, blended data implies overlapping single shot-gathers, producing interference that affects the result of seismic approaches, such as FWI or seismic image migration. In this document, an encoding strategy is developed, which reduces the overlap areas within the blended data to improve the final velocity model with the FWI method.


2021 ◽  
pp. 1-61
Author(s):  
Adnan Djeffal ◽  
Ingo A. Pecher ◽  
Satish C. Singh ◽  
Gareth J. Crutchley ◽  
Jari Kaipio

Gas hydrates are ice-like crystalline materials that form under submarine environments of moderate pressure and low temperature. Another key factor to their formation is the abundance in gas supply from depth in addition to local biogenic gas. Detailed imaging and velocity analysis of the plumbing system of gas hydrates can provide confidence that amplitude anomalies in seismic data are related to gas hydrate accumulations. We have conducted 2D elastic full-waveform inversion (FWI) along a 14 km long segment of a 2D multichannel seismic profile to obtain a high-resolution velocity model of a hydrate system on the southern Hikurangi margin. We compare the FWI velocity model to previously published semblance- and tomography-based velocity models from the same data to explore how much more can be gained from the FWI. The FWI yielded a structurally more accurate velocity model that better delineated the low-velocity zone associated with free gas beneath the bottom simulating reflector (BSR) compared to the semblance- and tomography-based velocity models. Our results also find a lateral velocity inversion, that is, a narrow low-velocity zone surrounded by bands of higher velocities at a seaward-verging protothrust fault, which the two other methodologies failed to resolve. The FWI provides an improved lateral resolution making it an important tool when imaging the “plumbing” systems of gas hydrate reservoirs. In the southeastern limb of the anticline, our results find that the closely spaced landward-vergent protothrusts provide gas-charged fluids for hydrate formation above the BSR. Moreover, at the center of the anticline, our results find that a seaward-vergent protothrust fault appears to be acting as a conduit for gas-rich fluids into strata, although there is no accumulation of any significant hydrate above the BSR at the apex of the anticline. Our finding emphasizes the significance of densely spaced faults and fractures for providing gas for hydrate formation in the hydrate stability zone.


2019 ◽  
Vol 59 (1) ◽  
pp. 432
Author(s):  
Tony Martin ◽  
Andrew Long

Despite the mathematics behind full waveform inversion (FWI) being published in the early 1980s, it was 30 years before the method could be efficiently implemented on the scale of conventional 3D marine seismic volumes. FWI has evolved from using only transmitted waves and being constrained because towed streamer data lacked the very long offsets and ultra-low frequencies necessary to derive stable velocity updates beyond shallow depths. FWI now uses the full seismic wavefield (both transmitted and scattered wavefields), recovers deep velocity updates for standard offsets and frequencies and increasingly uses a wider range of frequencies that contribute to seismic imaging. We use several case examples to consider the benefits and caveats for robust FWI application: for resolving near-surface features and reducing seismic imaging uncertainty in areas with complex overburden heterogeneities; for resolving near-surface features and improving volumetric estimates; for using an enlarged bandwidth to resolve small model features; for updating the velocity in high contrast regimes; and for the creation of survey-wide, high-resolution models to reduce imaging uncertainty, complement attribute analysis, estimate elastic properties and prospect derisking. Collectively, we demonstrate how to produce high-resolution velocity models when conventional methods cannot and how to generate earth models in an accelerated fashion to reduce project turnaround. We describe pragmatic limits to what maximum FWI frequencies are reasonable and suggest ways that may soon by-pass signal processing and obtain direct earth attributes.


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