Frequency Domain Waveform Inversion in a Tunnel Environment

The aim of the waveform inversion is to find an optimal model for the distribution of the elastic stiffness such that its response is consistent with the seismic data. In this study, a high-order finite element method is being used to solve the forward problem in the frequency domain and a gradient-based approach is followed to invert the model where an adjoint method eases the computational struggle by reducing the number of the required forward simulations significantly. Perfectly Matched Layers (PML) are implemented in order to absorb waves on the fictitious boundaries of the considered geometry. The model is inverted only over a limited number of frequencies. This reduces the number of the required forward simulations and the nonlinearity of the inverse problem. Every model is unique and has to be investigated before being inverted; appropriate boundary conditions, placement of the source and receiver locations, and an initial model close to the real model are crucial points to be considered separately and carefully. Applications to the reconnaissance problem in a tunnel environment are shown. (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Matrix probing: A randomized preconditioner for the wave-equation Hessian

This paper considers the problem of approximating the inverse of the wave-equation Hessian, also called normal operator, in seismology and other types of wave-based imaging. An expansion scheme for the pseudodifferential symbol of the inverse Hessian is set up. The coefficients in this expansion are found via least-squares fitting from a certain number of applications of the normal operator on adequate randomized trial functions built in curvelet space. It is found that the number of parameters that can be fitted increases with the amount of information present in the trial functions, with high probability. Once an approximate inverse Hessian is available, application to an image of the model can be done in very low complexity. Numerical experiments show that randomized operator fitting offers a compelling preconditioner for the linearized seismic inversion problem.     

Noniterative Reconstruction Method for an Inverse Potential Problem Modeled by a Modified Helmholtz Equation

This paper deals with an inverse potential problem posed in two dimensional space whose forward problem is governed by a modified Helmholtz equation. The inverse problem consists in the reconstruction of a set of anomalies embedded into a geometrical domain from partial measurements of the associated potential. Since the inverse problem, we are dealing with, is written in the form of an ill-posed boundary value problem, the idea is to rewrite it as a topology optimization problem. In particular, a shape functional is defined to measure the misfit of the solution obtained from the model and the data taken from the partial measurements. This shape functional is minimized with respect to a set of ball-shaped anomalies using the concept of topological derivatives. It means that the shape functional is expanded asymptotically and then truncated up to the desired order term. The resulting expression is trivially minimized with respect to the parameters under consideration which leads to a noniterative second-order reconstruction algorithm. As a result, the reconstruction process becomes very robust with respect to noisy data and independent of any initial guess. Finally, some numerical experiments are presented to show the effectiveness of the proposed reconstruction algorithm.     

A NEW INVERSION METHOD OF TIME-LAPSE SEISMIC

Time-Lapse Seismic improves oil recovery ratio by dynamic reservoir monitoring. Because of the large number of seismic explorations in the process of time-lapse seismic inversion, traditional methods need plenty of inversion calculations which cost high computational works. The method is therefore inefficient. In this paper, in order to reduce the repeating computations in traditional, a new time-lapse seismic inversion method is put forward. Firstly a homotopy-regularization method is proposed for the first time inversion. Secondly, with the first time inversion results as the initial value of following model, a model of the second time inversion is rebuilt by analyzing the characters of time-lapse seismic and localized inversion method is designed by using the model. Finally, through simulation, the comparison between traditional method and the new scheme is given. Our simulation results show that the new scheme could save the algorithm computations greatly.     

应用地震反演技术预测储层

为了解决开发过程中储层精细刻画难题,提出将曲线重构地震反演技术引入带储层预测工作中,根据曲线不同频带范围对砂岩敏感性特征,开展基于高频恢复、低频补偿原来的曲线重构技术开展地震反演预测.通过对南八区西部的地震反演实例表明:对于大于2m砂岩分辨能力较高的,隔层太小时,两套砂岩只能当一套砂岩组合反演出来;对于小于2米的砂岩,只有当隔层大于4m条件下才能清晰识别.地震反演能很好的推测地下岩层结构和物性参数的空间分布,有效的提高了薄储层预测精度.     

Detecting inclusions with a generalized impedance condition from electrostatic data via sampling

In this paper, we derive a sampling method to solve the inverse shape problem of recovering an inclusion with a generalized impedance condition from electrostatic Cauchy data. The generalized impedance condition is a second order differential operator applied to the boundary of the inclusion. We assume that the Dirichlet‐to‐Neumann mapping is given from measuring the current on the outer boundary from an imposed voltage. A simple numerical example is given to show the effectiveness of the proposed inversion method for recovering the inclusion. We also consider the inverse impedance problem of determining the impedance parameters for a known material from the Dirichlet‐to‐Neumann mapping assuming the inclusion has been reconstructed where uniqueness for the reconstruction of the coefficients is proven.     

Inversion of seismic data: sensitivity and stability via SVD analysis

The problem of recovery of seismic parameters of the media via wavefield produced by array of sources and recorded by array of receivers is considered in this work. In order to invert these data and recover elastic parameters one can use the optimization technique based on the gradient–like or Newton–like methods. In seismic applications this approach is known as “Full waveform inversion”. According to it we search for solution which minimizes mean–square deviation of the observed wavefield from the computed one for current values of elastic parameters. Surely convergence is governed by the properties of the Frechet derivative of nonlinear operator that maps medium parameters to the observed data. Thus studying these properties is an important step before development the numerical methods and algorithms of this inversion. For a simple case it can be shown that this derivative is a compact operator so implementation of any Newton–like approach is connected with necessity to resolve ill–posed problem of resolution of the first–order linear integral operational equation. In order to study the main peculiarities of this operator Singular Value Decomposition is applied. Two acquisition systems are dealt with – the offset vertical seismic profiling and cross–well tomography. Numerical results for realistic media are presented and the main differences of inverse problems for these two acquisition are shown. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Sparse Linear Algebra and Geophysical Migration: A Review of Direct and Iterative Methods

The pre-stack depth migration of reflection seismic data can be expressed, in the framework of waveform inversion, as a linear least squares problem. Together with the precise definition of this operator, we detail additional main characteristics of the forward model, like its huge size, its sparsity and the composition with convolution. It ends up with a so-called discrete ill-posed problem, whose acceptable solutions have to undergo a regularization procedure. Both direct and iterative methods have been implemented with specific attention to the convolution, and then applied to a given data set: a synthetic 2-dimensional profile of revealing size with some added noise. The efficiency with regard to computational effort and storage requirements is evaluated. The needed regularization of the solution is thoroughly studied in both cases. From the point of the global inverse problem, the extra feature of providing a solution that can be differentiated with respect to a parameter such as background velocity is also discussed.     

Approximate dynamic programming with Bézier Curves/Surfaces for Top-percentile Traffic Routing

Multi-homing is used by Internet Service Providers (ISPs) to connect to the Internet via different network providers. This study develops a routing strategy under multi-homing in the case where network providers charge ISPs according to top-percentile pricing (i.e. based on the θth highest volume of traffic shipped). We call this problem the Top-percentile Traffic Routing Problem (TpTRP).Solution approaches based on Stochastic Dynamic Programming require discretization in state space, which introduces a large number of state variables. This is known as the curse of dimensionality in state space. To overcome this, in previous work we have suggested to use approximate dynamic programming (ADP) to construct value function approximations, which allow us to work in continuous state space. The resulting ADP model provides well performing routing policies for medium sized instances of the TpTRP. In this work we extend the ADP model, by using Bézier Curves/Surfaces to obtain continuous-time approximations of the time-dependent ADP parameters. This modification reduces the number of regression parameters to estimate, and thus accelerates the efficiency of parameter training in the solution of the ADP model, which makes realistically sized TpTRP instances tractable. We argue that our routing strategy is near optimal by giving bounds.     

On the uniqueness and reconstruction for an inverse problem of the fractional diffusion process

Consider an inverse problem for the time-fractional diffusion equation in one dimensional spatial space. The aim is to determine the initial status and heat flux on the boundary simultaneously from heat measurement data given on the other boundary. Using the Laplace transform and the unique extension technique, the uniqueness for this inverse problem is proven. Then we construct a regularizing scheme for the reconstruction of boundary flux for known initial status. The convergence rate of the regularizing solution is established under some a priori information about the exact solution. Moreover, the initial distribution can also be recovered approximately from our regularizing scheme. Finally we present some numerical examples, which show the validity of the proposed reconstruction scheme.     

The factorization method for cracks in inhomogeneous media

We consider the inverse scattering problem of determining the shape and location of a crack surrounded by a known inhomogeneous media. Both the Dirichlet boundary condition and a mixed type boundary conditions are considered. In order to avoid using the background Green function in the inversion process, a reciprocity relationship between the Green function and the solution of an auxiliary scattering problem is proved. Then we focus on extending the factorization method to our inverse shape reconstruction problems by using far field measurements at fixed wave number. We remark that this is done in a non intuitive space for the mixed type boundary condition as we indicate in the sequel.     

Relaxed two points projection method for solving the multiple-sets split equality problem

The multiple-sets split equality problem, a generalization and extension of the split feasibility problem, has a variety of specific applications in real world, such as medical care, image reconstruction, and signal processing. It can be a model for many inverse problems where constraints are imposed on the solutions in the domains of two linear operators as well as in the operators’ ranges simultaneously. Although, for the split equality problem, there exist many algorithms, there are but few algorithms for the multiple-sets split equality problem. Hence, in this paper, we present a relaxed two points projection method to solve the problem; under some suitable conditions, we show the weak convergence and give a remark for the strong convergence method in the Hilbert space. The interest of our algorithm is that we transfer the problem to an optimization problem, then, based on the model, we present a modified gradient projection algorithm by selecting two different initial points in different sets for the problem (we call the algorithm as two points algorithm). During the process of iteration, we employ subgradient projections, not use the orthogonal projection, which makes the method implementable. Numerical experiments manifest the algorithm is efficient.     

Reconstruction of electron-phonon interaction function from temperature dependence of electrical resistivity for metals

The determination of the electron-phonon interaction function (EPIF) from the temperature dependence of the electrical resistivity (TDER) for metals within a selected moderate temperature range is numerically demonstrated based on the general theory of the amplitude-phase-retrieval problem and an iterative algorithm. From the model calculation, the convergent solution can be obtained; however, the profile of the recovered EPIF depends on the initial frequency distribution used in the algorithm since this inversion problem is inherently ill-posed. In order to get reasonable result, it is necessary to introduce additional information about the feature of the EPIF for guiding the choice of the initial distribution. The algorithm can also furnish a robust reconstruction of EPIF from TDER contaminated with random noise. It means that this algorithm is relatively stable and insensitive to external perturbation; therefore in a sense, the presented algorithm overcomes the ill-posedness of the inversion problem.     

基于二维随机震源的地震波全波形反演研究

全波形反演利用全部的波场信息做反演求解,兼顾了地震波的运动学特征和动力学特征,是一种直接基于波动方程描述地震波在地下介质中的传播过程,能够获得地质结构和岩性资料的方法.但是作为一种非线性反演算法,如何提高全波形反演的计算速度和成像精度是目前优化反演的难点和重点.针对全波形反演的效率问题,采用分层和模块化的matlab工具箱,开展了基于随机震源的全波形反演数值计算,由于采用的方法可以给定计算节点上的多线程资源,易于编程,无需矩阵,有效的减少了外部krylov迭代的数量,并将提出的方法与常规全波形反演方法进行对比分析,证明了基于随机震源全波形反演更加高效.     

Interpolating solutions of the Poisson equation in the disk based on Radon projections

We consider an algebraic method for reconstruction of a function satisfying the Poisson equation with a polynomial right-hand side in the unit disk. The given data, besides the right-hand side, is assumed to be in the form of a finite number of values of Radon projections of the unknown function. We first homogenize the problem by finding a polynomial which satisfies the given Poisson equation. This leads to an interpolation problem for a harmonic function, which we solve in the space of harmonic polynomials using a previously established method. For the special case where the Radon projections are taken along chords that form a regular convex polygon, we extend the error estimates from the harmonic case to this Poisson problem. Finally we give some numerical examples.     

Research on characterization of wireless LANs traffic

In this paper, we employ actual wireless data that draw from well known archives of network traffic traces and investigate the characterization of the wireless LANs traffic. Firstly, useful preliminary information regarding the general wireless traffic dynamics is obtained using one standard statistical technique named Fourier power spectrum. Then the estimation of the parameters, such as the correlation dimension, the largest Lyapunov exponent and the principal components analysis indicate the existence of low-dimensional deterministic chaos in wireless traffic time series. Our results also show that the parameters selection of the phase space reconstruction influence the value of the correlation dimension and the largest Lyapunov exponent, but can not influence on diagnosis of chaotic nature of wireless traffic.     

Identification of a nonlinear circuit

The identification of a differential equation underlying a measured time series is a prerequisite for numerous types of applications. In the validation of a proposed parameterized model one often faces the dilemma that it is hard to decide whether possible discrepancies between the measured time series and the simulated model output are caused by an inappropriate model or by wrongly specified parameters in a correct type of model. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a nonlinear chaotically oscillating circuit where we finally obtain an extremely accurate reconstruction of the observed attractor.     

A noniterative reconstruction method for the inverse potential problem with partial boundary measurements

In this paper, a noniterative reconstruction method for solving the inverse potential problem is proposed. The forward problem is governed by a modified Helmholtz equation. The inverse problem consists in the reconstruction of a set of anomalies embedded into a geometrical domain from partial or total boundary measurements of the associated potential. Since the inverse problem is written in the form of an ill‐posed boundary value problem, the idea is to rewrite it as a topology optimization problem. In particular, a shape functional measuring the misfit between the solution obtained from the model and the data taken from the boundary measurements is minimized with respect to a set of ball‐shaped anomalies by using the concept of topological derivatives. It means that the shape functional is expanded asymptotically and then truncated up to the desired order term. The resulting truncated expansion is trivially minimized with respect to the parameters under consideration that leads to a noniterative second order reconstruction algorithm. As a result, the reconstruction process becomes very robust with respect to the noisy data and independent of any initial guess. Finally, some numerical experiments are presented showing the capability of the proposed method in reconstructing multiple anomalies of different sizes and shapes by taking into account complete or partial boundary measurements.     

Nonstrictly hyperbolic systems of conservation laws of the conjugate type

We consider an inverse boundary problem for a general second order self-adjoint elliptic differential operator on a compact differential manifold with boundary. The inverse problem is that of the reconstruction of the manifold and operator via all but finite number of eigenvalues and traces on the boundary of the corresponding eigenfunctions of the operator. We prove that the data determine the manifold and the operator to within the group of the generalized gauge transformations. The proof is based upon a procedure of the reconstruction of a canonical object in the orbit of the group. This object, the canonical Schrödinger operator, is uniquely determined via its incomplete boundary spectral data.