1. A Data Set for Evaluating and Comparing Seismic Inversion Methods

Author(s):  
Robert G. Keys ◽  
Douglas J. Foster
Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1457-1473 ◽  
Author(s):  
Carey Bunks ◽  
Fatimetou M. Saleck ◽  
S. Zaleski ◽  
G. Chavent

Iterative inversion methods have been unsuccessful at inverting seismic data obtained from complicated earth models (e.g. the Marmousi model), the primary difficulty being the presence of numerous local minima in the objective function. The presence of local minima at all scales in the seismic inversion problem prevent iterative methods of inversion from attaining a reasonable degree of convergence to the neighborhood of the global minimum. The multigrid method is a technique that improves the performance of iterative inversion by decomposing the problem by scale. At long scales there are fewer local minima and those that remain are further apart from each other. Thus, at long scales iterative methods can get closer to the neighborhood of the global minimum. We apply the multigrid method to a subsampled, low‐frequency version of the Marmousi data set. Although issues of source estimation, source bandwidth, and noise are not treated, results show that iterative inversion methods perform much better when employed with a decomposition by scale. Furthermore, the method greatly reduces the computational burden of the inversion that will be of importance for 3-D extensions to the method.


Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. MR187-MR198 ◽  
Author(s):  
Yi Shen ◽  
Jack Dvorkin ◽  
Yunyue Li

Our goal is to accurately estimate attenuation from seismic data using model regularization in the seismic inversion workflow. One way to achieve this goal is by finding an analytical relation linking [Formula: see text] to [Formula: see text]. We derive an approximate closed-form solution relating [Formula: see text] to [Formula: see text] using rock-physics modeling. This relation is tested on well data from a clean clastic gas reservoir, of which the [Formula: see text] values are computed from the log data. Next, we create a 2D synthetic gas-reservoir section populated with [Formula: see text] and [Formula: see text] and generate respective synthetic seismograms. Now, the goal is to invert this synthetic seismic section for [Formula: see text]. If we use standard seismic inversion based solely on seismic data, the inverted attenuation model has low resolution and incorrect positioning, and it is distorted. However, adding our relation between velocity and attenuation, we obtain an attenuation model very close to the original section. This method is tested on a 2D field seismic data set from Gulf of Mexico. The resulting [Formula: see text] model matches the geologic shape of an absorption body interpreted from the seismic section. Using this [Formula: see text] model in seismic migration, we make the seismic events below the high-absorption layer clearly visible, with improved frequency content and coherency of the events.


Geophysics ◽  
1996 ◽  
Vol 61 (4) ◽  
pp. 1209-1227 ◽  
Author(s):  
Don W. Vasco ◽  
John E. Peterson ◽  
Ernest L. Majer

We examine the nonlinear aspects of seismic traveltime tomography. This is accomplished by completing an extensive set of conjugate gradient inversions on a parallel virtual machine, with each initiated by a different starting model. The goal is an exploratory analysis of a set of conjugate gradient solutions to the traveltime tomography problem. We find that distinct local minima are generated when prior constraints are imposed on traveltime tomographic inverse problems. Methods from cluster analysis determine the number and location of the isolated solutions to the traveltime tomography problem. We apply the cluster analysis techniques to a cross‐borehole traveltime data set gathered at the Gypsy Pilot Site in Pawnee County, Oklahoma. We find that the 1075 final models, satisfying the traveltime data and a model norm penalty, form up to 61 separate solutions. All solutions appear to contain a central low velocity zone bounded above and below by higher velocity layers. Such a structure agrees with well‐logs, hydrological well tests, and a previous seismic inversion.


Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. M1-M10 ◽  
Author(s):  
Leonardo Azevedo ◽  
Ruben Nunes ◽  
Pedro Correia ◽  
Amílcar Soares ◽  
Luis Guerreiro ◽  
...  

Due to the nature of seismic inversion problems, there are multiple possible solutions that can equally fit the observed seismic data while diverging from the real subsurface model. Consequently, it is important to assess how inverse-impedance models are converging toward the real subsurface model. For this purpose, we evaluated a new methodology to combine the multidimensional scaling (MDS) technique with an iterative geostatistical elastic seismic inversion algorithm. The geostatistical inversion algorithm inverted partial angle stacks directly for acoustic and elastic impedance (AI and EI) models. It was based on a genetic algorithm in which the model perturbation at each iteration was performed recurring to stochastic sequential simulation. To assess the reliability and convergence of the inverted models at each step, the simulated models can be projected in a metric space computed by MDS. This projection allowed distinguishing similar from variable models and assessing the convergence of inverted models toward the real impedance ones. The geostatistical inversion results of a synthetic data set, in which the real AI and EI models are known, were plotted in this metric space along with the known impedance models. We applied the same principle to a real data set using a cross-validation technique. These examples revealed that the MDS is a valuable tool to evaluate the convergence of the inverse methodology and the impedance model variability among each iteration of the inversion process. Particularly for the geostatistical inversion algorithm we evaluated, it retrieves reliable impedance models while still producing a set of simulated models with considerable variability.


Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC91-WCC103 ◽  
Author(s):  
Christophe Barnes ◽  
Marwan Charara

Marine reflection seismic data inversion is a compute-intensive process, especially in three dimensions. Approximations often are made to limit the number of physical parameters we invert for, or to speed up the forward modeling. Because the data often are dominated by unconverted P-waves, one popular approximation is to consider the earth as purely acoustic, i.e., no shear modulus. The material density sometimes is taken as a constant. Nonlinear waveform seismic inversion consists of iteratively minimizing the misfit between the amplitudes of the measured and the modeled data. Approximations, such as assuming an acoustic medium, lead to incorrect modeling of the amplitudes of the seismic waves, especially with respect to amplitude variation with offset (AVO), and therefore have a direct impact on the inversion results. For evaluation purposes, we have performed a series of inversions with different approximations and different constraints whereby the synthetic data set to recover is computed for a 1D elastic medium. A series of numerical experiments, although simple, help to define the applicability domain of the acoustic assumption. Acoustic full-wave inversion is applicable only when the S-wave velocity and the density fields are smooth enough to reduce the AVO effect, or when the near-offset seismograms are inverted with a good starting model. However, in many realistic cases, acoustic approximation penalizes the full-wave inversion of marine reflection seismic data in retrieving the acoustic parameters.


2020 ◽  
Author(s):  
Viktoriya Yarushina ◽  
Assia Lakhlifi ◽  
Hongliang Wang ◽  
David Connolly ◽  
Magnus Wangen ◽  
...  

<p>The improved resolution of recent seismic surveys has made seismic chimney structures a common observation in sedimentary basins worldwide and on the Norwegian Continental Shelf. Focused fluid flow in vertical chimneys is an important and poorly understood feature in a petroleum system. Oil and gas migrate through preferential pathways from source rocks to structural traps where they form reservoirs. Further migration or leakage from reservoirs leads to formation of shallow hydrocarbon accumulations and gas pockets. In some cases, leakage through preferential pathways can be traced up to the surface or to the sea floor, where it leads to formation of mud volcanoes, mounds and pockmarks. Here, we present results of an integrated case study, which is performed on a 3D seismic data set that covers an area of approximately 3000km2. The seismic sequence stratigraphic interpretation is complemented with a study of seismic fluid migration paths. Detection of seismic chimneys is a challenging task. State-of-the-art chimney cube technology based on self-educating neural networks was used to automatically identify possible structures. The results of seismic inversion in combination with available well data provided a set of surfaces distinguishing various stratigraphic layers and their properties. Obtained geological model was used as a basis for coupled geo-mechanical / fluid flow modelling that reconstructed the fluid flow processes in the geological past that lead to formation of chimney structures. Our numerical model of chimney formation is based on the two-phase theory of fluid flow through (de)compacting porous rocks. Viscous bulk rheology and strong nonlinear coupling of deforming porous rocks to fluid flow are key ingredients of the model. Chimney formation is linked to pressure build-up in the underlying reservoir. We reconstruct the fluid flow processes in the geological past that lead to formation of chimney structures and provide expectations for their present-day morphology, porosity and fluid pressure. Conditions of chimney formation, their sizes, spatial distribution and times of formation are investigated. The fate of the chimney after it has been created and its role as a fluid pathway in the present-day state is studied.</p>


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