12 resultados para Regularization

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.

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基于同伦映射的思想,改进了求解非线性反问题的梯度正则化算法.通过路径跟踪有效地拓宽了梯度正则化算法求解的收敛范围.对于正则化参数的修正,通过引入拟Sigmoid函数,提出了一种下降速率可调的连续化参数修正方法,在保证迭代稳定的条件下,得到较好的计算效率,同时保证该算法具有很好的抵抗观测噪声能力.实际算例表明,该方法收敛范围宽,计算效率高,在存在较强观测噪声的条件下也能得到很好的反演结果.

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The density distribution of inhomogeneous dense deuterium-tritium plasmas in laser fusion is revealed by the energy loss of fast protons going through the plasma. In our simulation of a plasma density diagnostics, the fast protons used for the diagnostics may be generated in the laser-plasma interaction. Dividing a two-dimensional area into grids and knowing the initial and final energies of the protons, we can obtain a large linear and ill-posed equation set. for the densities of all grids, which is solved with the Tikhonov regularization method. We find that the accuracy of the set plan with four proton sources is better than those of the set plans with less than four proton sources. Also we have done the density reconstruction especially. for four proton sources with and without assuming circularly symmetrical density distribution, and find that the accuracy is better for the reconstruction assuming circular symmetry. The error is about 9% when no noise is added to the final energy for the reconstruction of four proton sources assuming circular symmetry. The accuracies for different random noises to final proton energies with four proton sources are also calculated.

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Multi-frame image super-resolution (SR) aims to utilize information from a set of low-resolution (LR) images to compose a high-resolution (HR) one. As it is desirable or essential in many real applications, recent years have witnessed the growing interest in the problem of multi-frame SR reconstruction. This set of algorithms commonly utilizes a linear observation model to construct the relationship between the recorded LR images to the unknown reconstructed HR image estimates. Recently, regularization-based schemes have been demonstrated to be effective because SR reconstruction is actually an ill-posed problem. Working within this promising framework, this paper first proposes two new regularization items, termed as locally adaptive bilateral total variation and consistency of gradients, to keep edges and flat regions, which are implicitly described in LR images, sharp and smooth, respectively. Thereafter, the combination of the proposed regularization items is superior to existing regularization items because it considers both edges and flat regions while existing ones consider only edges. Thorough experimental results show the effectiveness of the new algorithm for SR reconstruction. (C) 2009 Elsevier B.V. All rights reserved.

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This paper deals with the dynamic rheological behavior of polypropylene/polyamide6 (PP/PA6) uncompatibilized blends and those compatibilized with a maleic anhydride grafted PP (PP/PP-g-MAH/PA6). The terminal relaxation times of the blends predicted by the Palierne emulsion model were compared with those obtained from experimental relaxation time spectra. The Palierne model succeeded well in describing PP/PA6 uncompatibilized blends with relatively low dispersed phase contents (10 wt%) and failed doing so for those of which the dispersed contents were high (30 wt%). It also failed for the compatibilized ones, irrespective of the dispersed phase content (10 or 30 wt%) and whether or not interface relaxation was taken into consideration. In the case of the uncompatibilized blend with high dispersed-phase content, interconnections among inclusions of the dispersed phase were responsible for the failure of the Palierne model. As for the compatiblized blends, in addition to particle interconnections, the existence of emulsion-in-emulsion (EE) structures was another factor responsible for the failure of Palieme model.

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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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An high-resolution prestack imaging technique of seismic data is developed in this thesis. By using this technique, the reflected coefficients of sheet sands can be gained in order to understand and identify thin oil reservoirs. One-way wave equation based migration methods can more accurately model seismic wave propagation effect such as multi-arrivals and obtain almost correct reflected energy in the presence of complex inhomogeneous media, and therefore, achieve more superiorities in imaging complex structure. So it is a good choice to apply the proposed high-resolution imaging to the presatck depth migration gathers. But one of the main shorting of one-way wave equation based migration methods is the low computational efficiency, thus the improvement on computational efficiency is first carried out. The method to improve the computational efficiency of prestack depth migration is first presented in this thesis, that is frequency-dependent varying-step depth exploration scheme plus a table-driven, one-point wavefield interpolation technology for wave equation based migration methods; The frequency-dependent varying-step depth exploration scheme reduces the computational cost of wavefield depth extrapolation, and the a table-driven, one-point wavefield interpolation technology reconstructs the extrapolated wavefield with an equal, desired vertical step with high computational efficiency. The proposed varying-step depth extrapolation plus one-point interpolation scheme results in 2/3 reduction in computational cost when compared to the equal-step depth extrapolation of wavefield, but gives the almost same imaging. The frequency-dependent varying-step depth exploration scheme is presented in theory by using the optimum split-step Fourier. But the proposed scheme can also be used by other wave equation based migration methods of the frequency domain. The proposed method is demonstrated by using impulse response, 2-D Marmousi dataset, 3-D salt dataset and the 3-D field dataset. A method of high-resolution prestack imaging is presented in the 2nd part of this thesis. The seismic interference method to solve the relative reflected coefficients is presented. The high-resolution imaging is obtained by introducing a sparseness- constrained least-square inversion into the reflected coefficient imaging. Gaussian regularization is first imposed and a smoothed solution is obtained by solving equation derived from the least-square inversion. Then the Cauchy regularization is introducing to the least-square inversion , the sparse solution of relative reflected coefficients can be obtained, that is high-resolution solution. The proposed scheme can be used together with other prestack imaging if the higher resolution is needed in a target zone. The seismic interference method in theory and the solution to sparseness-constrained least-square inversion are presented. The proposed method is demonstrated by synthetic examples and filed data.

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In this paper we base on the anisotropic theory and Zoeppritz function of the transmission theory and the law of amplitude versus offset simplify seismic reflection coefficient of different media, analyze the characteristic of the gas or oil saturated stratum or the VTI and HTI models. Discuss the P wave reflection relationship and the meanings of the different parameters. We use measured parameters of a reservoir to simulate the characteristic of the reservoir, study the different effects of stratum saturated with gas or oil and analyze the characteristic of the seismic response of different models which change with different incident angles and different azimuths. Using the field data of logs ,analyze the rock property parameters, build the relationship of logs and parameters by Gassmann theory or empirical function. Calculate the density and the shear modulus and bulk modulus, reconstruct the log curves, calculate shear wave logs and correlate the logs affected by mud and other environmental factors. Finally perform the relationship of the seismic data log of saturated stratum and enhance the ability and reliability in reservoir prediction. Our aim is by the prestack seismic processing to get high solution and amplitude preserved seismic data. Because in incident angle gathers or azimuthal gathers, the low signal to noise ratio and low different covers affect the result of the prestack reservoir prediction. We apply prestack noise erase, cell regularization process and relatively amplitude preservation in the high solution seismic process routine to preserve the characteristic of stratum response, and erase the effects of the noise. In this paper we finished prestack invertion in the BYT survey and fractured reservoir depiction in MB survey. By the invertion and multiple attributes crossplot. we can get the stratum profiles and oil indicator profiles which can predict the distribution of the reservoir and oil. In the MB survey, we get orientation and density of fractured reservoir by the azimuthal seismic amplitude and depict the potential oil and gas reservoir. Prestak invertion works better in distinguishing oil and reservoir.

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Seismic technique is in the leading position for discovering oil and gas trap and searching for reserves throughout the course of oil and gas exploration. It needs high quality of seismic processed data, not only required exact spatial position, but also the true information of amplitude and AVO attribute and velocity. Acquisition footprint has an impact on highly precision and best quality of imaging and analysis of AVO attribute and velocity. Acquisition footprint is a new conception of describing seismic noise in 3-D exploration. It is not easy to understand the acquisition footprint. This paper begins with forward modeling seismic data from the simple sound wave model, then processes it and discusses the cause for producing the acquisition footprint. It agreed that the recording geometry is the main cause which leads to the distribution asymmetry of coverage and offset and azimuth in different grid cells. It summarizes the characters and description methods and analysis acquisition footprint’s influence on data geology interpretation and the analysis of seismic attribute and velocity. The data reconstruct based on Fourier transform is the main method at present for non uniform data interpolation and extrapolate, but this method always is an inverse problem with bad condition. Tikhonov regularization strategy which includes a priori information on class of solution in search can reduce the computation difficulty duo to discrete kernel condition disadvantage and scarcity of the number of observations. The method is quiet statistical, which does not require the selection of regularization parameter; and hence it has appropriate inversion coefficient. The result of programming and tentat-ive calculation verifies the acquisition footprint can be removed through prestack data reconstruct. This paper applies migration to the processing method of removing the acquisition footprint. The fundamental principle and algorithms are surveyed, seismic traces are weighted according to the area which occupied by seismic trace in different source-receiver distances. Adopting grid method in stead of accounting the area of Voroni map can reduce difficulty of calculation the weight. The result of processing the model data and actual seismic demonstrate, incorporating a weighting scheme based on the relative area that is associated with each input trace with respect to its neighbors acts to minimize the artifacts caused by irregular acquisition geometry.

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Post-stack seismic impedance inversion is the key technology of reservoir prediction and identification. Geophysicists have done a lot of research for the problem, but the developed methods still cannot satisfy practical requirements completely. The results of different inversion methods are different and the results of one method used by different people are different too. The reasons are due to the quality of seismic data, inaccurate wavelet extraction, errors between normal incidence assumption and real situation, and so on. In addition, there are two main influence factors: one is the band-limited property of seismic data; the other is the ill-posed property of impedance inversion. Thus far, the most effective way to solve the band-limited problem is the constrained inversion. And the most effective way to solve ill-posed problems is the regularization method assisted with proper optimization techniques. This thesis systematically introduces the iterative regularization methods and numerical optimization methods for impedance inversion. A regularized restarted conjugate gradient method for solving ill-posed problems in impedance inversion is proposed. Theoretic simulations are made and field data applications are performed. It reveals that the proposed algorithm possesses the superiority to conventional conjugate gradient method. Finally, non-smooth optimization is proposed as the further research direction in seismic impedance inversion according to practical situation.

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The seismic survey is the most effective geophysical method during exploration and development of oil/gas. As a main means in processing and interpreting seismic data, impedance inversion takes up a special position in seismic survey. This is because the impedance parameter is a ligament which connects seismic data with well-logging and geological information, while it is also essential in predicting reservoir properties and sand-body. In fact, the result of traditional impedance inversion is not ideal. This is because the mathematical inverse problem of impedance is poor-pose so that the inverse result has instability and multi-result, so it is necessary to introduce regularization. Most simple regularizations are presented in existent literature, there is a premise that the image(or model) is globally smooth. In fact, as an actual geological model, it not only has made of smooth region but also be separated by the obvious edge, the edge is very important attribute of geological model. It's difficult to preserve these characteristics of the model and to avoid an edge too smooth to clear. Thereby, in this paper, we propose a impedance inverse method controlled by hyperparameters with edge-preserving regularization, the inverse convergence speed and result would be improved. In order to preserve the edge, the potential function of regularization should satisfy nine conditions such as basic assumptions edge preservation and convergence assumptions etc. Eventually, a model with clear background and edge-abnormity can be acquired. The several potential functions and the corresponding weight functions are presented in this paper. The potential functionφLφHL andφGM can meet the need of inverse precision by calculating the models. For the local constant planar and quadric models, we respectively present the neighborhood system of Markov random field corresponding to the regularization term. We linearity nonlinear regularization by using half-quadratic regularization, it not only preserve the edge, and but also simplify the inversion, and can use some linear methods. We introduced two regularization parameters (or hyperparameters) λ2 and δ in the regularization term. λ2 is used to balance the influence between the data term and the transcendental term; δ is a calibrating parameter used to adjust the gradient value at the discontinuous position(or formation interface). Meanwhile, in the inverse procedure, it is important to select the initial value of hyperparameters and to change hyperparameters, these will then have influence on convergence speed and inverse effect. In this paper, we roughly give the initial value of hyperparameters by using a trend- curve of φ-(λ2, δ) and by a method of calculating the upper limit value of hyperparameters. At one time, we change hyperparameters by using a certain coefficient or Maximum Likelihood method, this can be simultaneously fulfilled with the inverse procedure. Actually, we used the Fast Simulated Annealing algorithm in the inverse procedure. This method overcame restrictions from the local extremum without depending on the initial value, and got a global optimal result. Meanwhile, we expound in detail the convergence condition of FSA, the metropolis receiving probability form Metropolis-Hasting, the thermal procession based on the Gibbs sample and other methods integrated with FSA. These content can help us to understand and improve FSA. Through calculating in the theoretic model and applying it to the field data, it is proved that the impedance inverse method in this paper has the advantage of high precision practicability and obvious effect.

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The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.