30 resultados para preconditioner


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I address of reconstruction of spatial irregular sampling seismic data to regular grids. Spatial irregular sampling data impairs results of prestack migration, multiple attenuations, spectra estimation. Prestack 5-D volumes are often divided into sub-sections for further processing. Shot gathers are easy to obtain from irregular sampling volumes. My strategy for reconstruction is as follows: I resort irregular sampling gathers into a form of easy to bin and perform bin regularization, then utilize F-K inversion to reconstruct seismic data. In consideration of poor ability of F-K regularization to fill in large gaps, I sort regular sampling gathers to CMP and proposed high-resolution parabolic Radon transform to interpolate data and extrapolate offsets. To strong interfering noise--multiples, I use hybrid-domain high-resolution parabolic Radon transform to attenuate it. F-K regularization demand ultimately for lower computing costs. I proposed several methods to further improve efficiency of F-K inversion: first I introduce 1D and 2D NFFT algorithm for a rapid calculation of DFT operators; then develop fast 1D and 2D CG method to solve least-square equations, and utilize preconditioner to accelerate convergence of CG iterations; what’s more, I use Delaunay triangulation for weight calculation and use bandlimit frequency and varying bandwidth technique for competitive computation. Numerical 2D and 3D examples are offered to verify reasonable results and more efficiency. F-K regularization has poor ability to fill in large gaps, so I rearrange data as CMP gathers and develop hybrid-domain high-resolution parabolic Radon transforms which be used ether to interpolate null traces and extrapolate near and far offsets or suppress a strong interfere noise: multiples. I use it to attenuate multiples to verify performances of our algorithm and proposed routines for industrial application. Numerical examples and field data examples show a nice performance of our method.

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In this paper, we have presented the combined preconditioner which is derived from k =±-1~(1/2) circulant extensions of the real symmetric positive-definite Toeplitz matrices, proved it with great efficiency and stability and shown that it is easy to make error analysis and to remove the boundary effect with the combined preconditioner. This paper has also presented the methods for the direct and inverse computation of the real Toeplitz sets of equations and discussed many problems correspondingly, especially replaced the Toeplitz matrices with the combined preconditoners for analysis. The paper has also discussed the spectral analysis and boundary effect. Finally, as an application in geophysics, the paper makes some discussion about the squared root of a real matrix which comes from the Laplace algorithm.

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The content of this paper is based on the research work while the author took part in the key project of NSFC and the key project of Knowledge Innovation of CAS. The whole paper is expanded by introduction of the inevitable boundary problem during seismic migration and inversion. Boundary problem is a popular issue in seismic data processing. At the presence of artificial boundary, reflected wave which does not exist in reality comes to presence when the incident seismic wave arrives at the artificial boundary. That will interfere the propagation of seismic wave and cause alias information on the processed profile. Furthermore, the quality of the whole seismic profile will decrease and the subsequent work will fail.This paper has also made a review on the development of seismic migration, expatiated temporary seismic migration status and predicted the possible break through. Aiming at the absorbing boundary problem in migration, we have deduced the wide angle absorbing boundary condition and made a compare with the boundary effect of Toepiitz matrix fast approximate computation.During the process of fast approximate inversion computation of Toepiitz system, we have introduced the pre-conditioned conjugate gradient method employing co circulant extension to construct pre-conditioned matrix. Especially, employment of combined preconditioner will reduce the boundary effect during computation.Comparing the boundary problem in seismic migration with that in Toepiitz matrix inversion we find that the change of boundary condition will lead to the change of coefficient matrix eigenvalues and the change of coefficient matrix eigenvalues will cause boundary effect. In this paper, the author has made an qualitative analysis of the relationship between the coefficient matrix eigenvalues and the boundary effect. Quantitative analysis is worthy of further research.

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We present a dynamic distributed load balancing algorithm for parallel, adaptive Finite Element simulations in which we use preconditioned Conjugate Gradient solvers based on domain-decomposition. The load balancing is designed to maintain good partition aspect ratio and we show that cut size is not always the appropriate measure in load balancing. Furthermore, we attempt to answer the question why the aspect ratio of partitions plays an important role for certain solvers. We define and rate different kinds of aspect ratio and present a new center-based partitioning method of calculating the initial distribution which implicitly optimizes this measure. During the adaptive simulation, the load balancer calculates a balancing flow using different versions of the diffusion algorithm and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. Experimental results for Bramble's preconditioner and comparisons to state-of-the-art load balancers show the benefits of the construction.

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This paper discusses preconditioned Krylov subspace methods for solving large scale linear systems that originate from oil reservoir numerical simulations. Two types of preconditioners, one being based on an incomplete LU decomposition and the other being based on iterative algorithms, are used together in a combination strategy in order to achieve an adaptive and efficient preconditioner. Numerical tests show that different Krylov subspace methods combining with appropriate preconditioners are able to achieve optimal performance.

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In [4], Guillard and Viozat propose a finite volume method for the simulation of inviscid steady as well as unsteady flows at low Mach numbers, based on a preconditioning technique. The scheme satisfies the results of a single scale asymptotic analysis in a discrete sense and comprises the advantage that this can be derived by a slight modification of the dissipation term within the numerical flux function. Unfortunately, it can be observed by numerical experiments that the preconditioned approach combined with an explicit time integration scheme turns out to be unstable if the time step Dt does not satisfy the requirement to be O(M2) as the Mach number M tends to zero, whereas the corresponding standard method remains stable up to Dt=O(M), M to 0, which results from the well-known CFL-condition. We present a comprehensive mathematical substantiation of this numerical phenomenon by means of a von Neumann stability analysis, which reveals that in contrast to the standard approach, the dissipation matrix of the preconditioned numerical flux function possesses an eigenvalue growing like M-2 as M tends to zero, thus causing the diminishment of the stability region of the explicit scheme. Thereby, we present statements for both the standard preconditioner used by Guillard and Viozat [4] and the more general one due to Turkel [21]. The theoretical results are after wards confirmed by numerical experiments.

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We study the preconditioning of symmetric indefinite linear systems of equations that arise in interior point solution of linear optimization problems. The preconditioning method that we study exploits the block structure of the augmented matrix to design a similar block structure preconditioner to improve the spectral properties of the resulting preconditioned matrix so as to improve the convergence rate of the iterative solution of the system. We also propose a two-phase algorithm that takes advantage of the spectral properties of the transformed matrix to solve for the Newton directions in the interior-point method. Numerical experiments have been performed on some LP test problems in the NETLIB suite to demonstrate the potential of the preconditioning method discussed.

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Os efeitos Delaware e Groningen são dois tipos de anomalia que afetam ferramentas de eletrodos para perfilagem de resistividade. Ambos os efeitos ocorrem quando há uma camada muito resistiva, como anidrita ou halita, acima do(s) reservatório(s), produzindo um gradiente de resistividade muito similar ao produzido por um contato óleo-água. Os erros de interpretação produzidos têm ocasionado prejuízos consideráveis à indústria de petróleo. A PETROBRÁS, em particular, tem enfrentado problemas ocasionados pelo efeito Groningen sobre perfis obtidos em bacias paleozóicas da região norte do Brasil. Neste trabalho adaptamos, com avanços, uma metodologia desenvolvida por LOVELL (1990), baseada na equação de Helmholtz para HΦ, para modelagem dos efeitos Delaware e Groningen. Solucionamos esta equação por elementos finitos triangulares e retangulares. O sistema linear gerado pelo método de elementos finitos é resolvido por gradiente bi-conjugado pré-condicionado, sendo este pré-condicionador obtido por decomposição LU (Low Up) da matriz de stiffness. As voltagens são calculadas por um algoritmo, mais preciso, recentemente desenvolvido. Os perfis são gerados por um novo algoritmo envolvendo uma sucessiva troca de resistividade de subdomínios. Este procedimento permite obter cada nova matriz de stiffness a partir da anterior pelo cálculo, muito mais rápido, da variação dessa matriz. Este método permite ainda, acelerar a solução iterativa pelo uso da solução na posição anterior da ferramenta. Finalmente geramos perfis sintéticos afetados por cada um dos efeitos para um modelo da ferramenta Dual Laterolog.

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A implementação convencional do método de migração por diferenças finitas 3D, usa a técnica de splitting inline e crossline para melhorar a eficiência computacional deste algoritmo. Esta abordagem torna o algoritmo eficiente computacionalmente, porém cria anisotropia numérica. Esta anisotropia numérica por sua vez, pode levar a falsos posicionamentos de refletores inclinados, especialmente refletores com grandes ângulos de mergulho. Neste trabalho, como objetivo de evitar o surgimento da anisotropia numérica, implementamos o operador de extrapolação do campo de onda para baixo sem usar a técnica splitting inline e crossline no domínio frequência-espaço via método de diferenças finitas implícito, usando a aproximação de Padé complexa. Comparamos a performance do algoritmo iterativo Bi-gradiente conjugado estabilizado (Bi-CGSTAB) com o multifrontal massively parallel solver (MUMPS) para resolver o sistema linear oriundo do método de migração por diferenças finitas. Verifica-se que usando a expansão de Padé complexa ao invés da expansão de Padé real, o algoritmo iterativo Bi-CGSTAB fica mais eficientes computacionalmente, ou seja, a expansão de Padé complexa atua como um precondicionador para este algoritmo iterativo. Como consequência, o algoritmo iterativo Bi-CGSTAB é bem mais eficiente computacionalmente que o MUMPS para resolver o sistema linear quando usado apenas um termo da expansão de Padé complexa. Para aproximações de grandes ângulos, métodos diretos são necessários. Para validar e avaliar as propriedades desses algoritmos de migração, usamos o modelo de sal SEG/EAGE para calcular a sua resposta ao impulso.

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Implementações dos métodos de migração diferença finita e Fourier (FFD) usam fatoração direcional para acelerar a performance e economizar custo computacional. Entretanto essa técnica introduz anisotropia numérica que podem erroneamente posicionar os refletores em mergulho ao longo das direções em que o não foi aplicado a fatoração no operador de migração. Implementamos a migração FFD 3D, sem usar a técnica do fatoração direcional, no domínio da frequência usando aproximação de Padé complexa. Essa aproximação elimina a anisotropia numérica ao preço de maior custo computacional buscando a solução do campo de onda para um sistema linear de banda larga. Experimentos numéricos, tanto no modelo homogêneo e heterogêneo, mostram que a técnica da fatoração direcional produz notáveis erros de posicionamento dos refletores em meios com forte variação lateral de velocidade. Comparamos a performance de resolução do algoritmo de FFD usando o método iterativo gradiente biconjugado estabilizado (BICGSTAB) e o multifrontal massively parallel direct solver (MUMPS). Mostrando que a aproximação de Padé complexa é um eficiente precondicionador para o BICGSTAB, reduzindo o número de iterações em relação a aproximação de Padé real. O método iterativo BICGSTAB é mais eficiente que o método direto MUMPS, quando usamos apenas um termo da expansão de Padé complexa. Para maior ângulo de abertura do operador, mais termos da série são requeridos no operador de migração, e neste caso, a performance do método direto é mais eficiente. A validação do algoritmo e as propriedades da evolução computacional foram avaliadas para a resposta ao impulso do modelo de sal SEG/EAGE.

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A novel time-stepping shift-invert algorithm for linear stability analysis of laminar flows in complex geometries is presented. This method, based on a Krylov subspace iteration, enables the solution of complex non-symmetric eigenvalue problems in a matrix-free framework. Validations and comparisons to the classical exponential method have been performed in three different cases: (i) stenotic flow, (ii) backward-facing step and (iii) lid-driven swirling flow. Results show that this new approach speeds up the required Krylov subspace iterations and has the capability of converging to specific parts of the global spectrum. It is shown that, although the exponential method remains the method of choice if leading eigenvalues are sought, the performance of the present method could be dramatically improved with the use of a preconditioner. In addition, as opposed to other methods, this strategy can be directly applied to any time-stepper, regardless of the temporal or spatial discretization of the latter.

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We present a dynamic distributed load balancing algorithm for parallel, adaptive finite element simulations using preconditioned conjugate gradient solvers based on domain-decomposition. The load balancer is designed to maintain good partition aspect ratios. It can calculate a balancing flow using different versions of diffusion and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. We show how to use information from the second step to guide the first. Experimental results using Bramble's preconditioner and comparisons to existing state-ot-the-art load balancers show the benefits of the construction.

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We present a dynamic distributed load balancing algorithm for parallel, adaptive finite element simulations using preconditioned conjugate gradient solvers based on domain-decomposition. The load balancer is designed to maintain good partition aspect ratios. It calculates a balancing flow using different versions of diffusion and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. We show how to use information from the second step to guide the first. Experimental results using Bramble's preconditioner and comparisons to existing state-of-the-art balancers show the benefits of the construction.