Preconditioned non‐linear conjugate gradient method for frequency domain full‐waveform seismic inversion

We present preconditioned non‐linear conjugate gradient algorithms as alternatives to the Gauss‐Newton method for frequency domain full‐waveform seismic inversion. We designed two preconditioning operators. For the first preconditioner, we introduce the inverse of an approximate sparse Hessian matrix. The approximate Hessian matrix, which is highly sparse, is constructed by judiciously truncating the Gauss‐Newton Hessian matrix based on examining the auto‐correlation and cross‐correlation of the Jacobian matrix. As the second preconditioner, we employ the approximation of the inverse of the Gauss‐Newton Hessian matrix. This preconditioner is constructed by terminating the iteration process of the conjugate gradient least‐squares method, which is used for inverting the Hessian matrix before it converges. In our preconditioned non‐linear conjugate gradient algorithms, the step‐length along the search direction, which is a crucial factor for the convergence, is carefully chosen to maximize the reduction of the cost function after each iteration. The numerical simulation results show that by including a very limited number of non‐zero elements in the approximate Hessian, the first preconditioned non‐linear conjugate gradient algorithm is able to yield comparable inversion results to the Gauss‐Newton method while maintaining the efficiency of the un‐preconditioned non‐linear conjugate gradient method. The only extra cost is the computation of the inverse of the approximate sparse Hessian matrix, which is less expensive than the computation of a forward simulation of one source at one frequency of operation. The second preconditioned non‐linear conjugate gradient algorithm also significantly saves the computational expense in comparison with the Gauss‐Newton method while maintaining the Gauss‐Newton reconstruction quality. However, this second preconditioned non‐linear conjugate gradient algorithm is more expensive than the first one.     

大地电磁非线性共轭梯度拟三维反演

提出了非线性共轭梯度法大地电磁拟三维反演.该方法选取共轭梯度反演算法为拟三维反演的核心.在计算灵敏度（Jacobian）矩阵时,吸取近似灵敏度矩阵思想,采用一维灵敏度矩阵来代替三维灵敏度矩阵,并对非测点的灵敏度元素提出一种近似方法.在第一次反演之后,采用拟牛顿法更新灵敏度矩阵.拟三维反演法在很大程度上节省了计算时间,并且理论模型和实际资料的反演试算结果表明大地电磁拟三维反演法具有一定的实用价值.     

Computing the Sensitivity Kernels for 2.5-D Seismic Waveform Inversion in Heterogeneous,Anisotropic Media

2.5-D modeling and inversion techniques are much closer to reality than the simple and traditional 2-D seismic wave modeling and inversion. The sensitivity kernels required in full waveform seismic tomographic inversion are the Fréchet derivatives of the displacement vector with respect to the independent anisotropic model parameters of the subsurface. They give the sensitivity of the seismograms to changes in the model parameters. This paper applies two methods, called ‘the perturbation method’ and ‘the matrix method’, to derive the sensitivity kernels for 2.5-D seismic waveform inversion. We show that the two methods yield the same explicit expressions for the Fréchet derivatives using a constant-block model parameterization, and are available for both the line-source (2-D) and the point-source (2.5-D) cases. The method involves two Green’s function vectors and their gradients, as well as the derivatives of the elastic modulus tensor with respect to the independent model parameters. The two Green’s function vectors are the responses of the displacement vector to the two directed unit vectors located at the source and geophone positions, respectively; they can be generally obtained by numerical methods. The gradients of the Green’s function vectors may be approximated in the same manner as the differential computations in the forward modeling. The derivatives of the elastic modulus tensor with respect to the independent model parameters can be obtained analytically, dependent on the class of medium anisotropy. Explicit expressions are given for two special cases—isotropic and tilted transversely isotropic (TTI) media. Numerical examples are given for the latter case, which involves five independent elastic moduli (or Thomsen parameters) plus one angle defining the symmetry axis.     

三维复杂地壳结构非线性走时反演

中国大陆中西部乃至全球造山带普遍具有复杂地壳结构.随着矿产资源勘探和深部探测研究的深入,探测造山带及盆山耦合区下方地壳精细结构正逐渐成为当前面临的巨大挑战.人工源深地震测深方法正越来越清晰地揭示出不同构造域地壳速度结构的基本特征,然而传统的层状结构模型参数化方法难以准确描述复杂地质模型,通常情况下多忽略速度结构的精细间断面且采用层边界平滑处理,难以满足地壳精细结构成像的发展要求.针对上述困难,本文采用最近发展的块状结构建模方案构建三维复杂地壳模型,基于逐段迭代射线追踪正演走时计算方法,推导了走时对三角形界面深度以及网格速度的偏导数,开展了非线性共轭梯度走时反演方法研究.发展了利用直达波和反射波等多震相走时数据对界面深度和网格速度的多参数联合反演方法,并引人不同种类震相数据的权系数和不同类型参数偏导数归一化的方法.数值算例表明,基于块状结构的非线性共轭梯度走时反演方法适用于复杂地壳结构模型,在利用人工源走时数据反演复杂地壳精细结构领域具有良好的应用前景.     

井地有限线源三维电阻率反演研究

有限线源的三维电阻率反演,是地学探测研究的重要课题之一.本文主要讨论了以下几个方面的内容:(1)结合反演方程式改进的共轭梯度算法;(2)基于扰动法的线源Jacobi矩阵的近似计算方法及光滑系数矩阵在各个方向上的光滑因子的计算公式;(3)通过分析阻尼系数与修改量校正量对反演结果的影响,提出了利用校正系数对模型修正量进行校正;(4)较为系统的讨论了阻尼系数λ对反演分辨能力的影响,较好的改善了三维电阻率反演中的电性异常体重心的"上漂"现象.数值实验表明,改进后的共轭梯度法反演对初始模型的依赖程度较小,反演能够稳定收敛,对模型的空间位置分辨率较高.     

A comparison of different radiomagnetotelluric data inversion methods for buried waste sites

This study deals with two-dimensional (2D) inversions of synthetic and observed radiomagnetotelluric (RMT) data on typical buried conductive waste sites in Europe, and with the practical aspects of different inversion algorithms. In the inversion calculations, we used smoothing and L2-norm stabilizers and compared the results. The resolution of the geometry of the highly conductive waste site, in particular, was investigated. In the inversion with the L2-norm stabilizer, we used the least-squares solution with singular value decomposition (LSSVD) and conjugate gradient (CG), whereas only the conjugate gradient solver was used in the 2D-inversion with the smoothing stabilizer. The inversion results of the synthetic data showed a better resolution of the geometry of the highly conductive waste site when a L2-norm stabilizer was applied in the inversion; in particular, a better detection of the bottom of the waste deposit was achieved. Additional model studies were carried out using synthetic RMT data in order to investigate the 2D inversion of RMT data observed on a 3D structure; these studies showed that the use of TM mode data yields a better resolution of the structure than joint inversion of TE and TM modes.2D inversions of RMT data on a waste site near Cologne showed that the inversion of the TM mode could resolve well the geometry, especially the bottom of the waste site, if information about the background conductivity structure was available. In this case study, inversion with the L2-norm stabilizer produced a sharper image of the waste site than inversion with the smoothing stabilizer, as indicated also by the inversion study that used synthetic data.     

井地电法的准解析近似三维反演研究

研究复杂地电模型上的井地电法三维反演一直是一个具有挑战性的课题。本文在准解析近似和重加权正则化的共轭梯度法的基础上,用visualFortran6.5开发了井地电法三维准解析近似反演程序。反演过程中的正演和Frechet导数矩阵计算都应用准解析近似大大提高了计算的速度。通过理论模型的合成数据反演试算,说明基于准解析近似法和加权正则化的共轭梯度法的井地电法三维反演程序有着计算速度快,反演精度高等特点。     

可控源音频大地电磁三维共轭梯度反演研究

可控源音频大地电磁法在资源勘探等领域中发挥着重要的作用.我们把有限差分数值模拟方法用于可控源音频大地电磁三维正演,结合正则化反演方案和共轭梯度反演的思路,将反演中的雅可比矩阵计算问题转为求解两次"拟正演"问题,得到模型参数的更新步长,形成反演迭代,实现了可控源音频大地电磁三维共轭梯度反演算法.该反演算法可用于对有限长度电偶源激发下采集到的可控源音频大地电磁全区(近区、过渡区和远区)视电阻率和相位资料进行三维反演定量解释,获得地下三维模型的电阻率结构.理论模型合成数据的反演算例验证了所实现的可控源音频大地电磁三维共轭梯度反演算法的有效性和稳定性.     

Full waveform inversion and the truncated Newton method: quantitative imaging of complex subsurface structures

Full waveform inversion is a powerful tool for quantitative seismic imaging from wide‐azimuth seismic data. The method is based on the minimization of the misfit between observed and simulated data. This amounts to the solution of a large‐scale nonlinear minimization problem. The inverse Hessian operator plays a crucial role in this reconstruction process. Accounting accurately for the effect of this operator within the minimization scheme should correct for illumination deficits, restore the amplitude of the subsurface parameters, and help to remove artefacts generated by energetic multiple reflections. Conventional minimization methods (nonlinear conjugate gradient, quasi‐Newton methods) only roughly approximate the effect of this operator. In this study, we are interested in the truncated Newton minimization method. These methods are based on the computation of the model update through a matrix‐free conjugate gradient solution of the Newton linear system. We present a feasible implementation of this method for the full waveform inversion problem, based on a second‐order adjoint state formulation for the computation of Hessian‐vector products. We compare this method with conventional methods within the context of 2D acoustic frequency full waveform inversion for the reconstruction of P‐wave velocity models. Two test cases are investigated. The first is the synthetic BP 2004 model, representative of the Gulf of Mexico geology with high velocity contrasts associated with the presence of salt structures. The second is a 2D real data‐set from the Valhall oil field in North sea. Although, from a computational cost point of view, the truncated Newton method appears to be more expensive than conventional optimization algorithms, the results emphasize its increased robustness. A better reconstruction of the P‐wave velocity model is provided when energetic multiple reflections make it difficult to interpret the seismic data. A better trade‐off between regularization and resolution is obtained when noise contamination of the data requires one to regularize the solution of the inverse problem.     

Two-dimensional inversion of magnetotelluric data with consecutive use of conjugate gradient and least-squares solution with singular value decomposition algorithms

I investigated the two‐dimensional magnetotelluric data inversion algorithms in studying two significant aspects within a linearized inversion approach. The first one is the method of minimization and second one is the type of stabilizing functional used in parametric functionals. The results of two well‐known inversion algorithms, namely conjugate gradient and the least‐squares solution with singular value decomposition, were compared in terms of accuracy and CPU time. In addition, magnetotelluric data inversion with various stabilizers, such as L2‐norm, smoothing, minimum support, minimum gradient support and first‐order minimum entropy, were examined. A new inversion algorithm named least‐squares solution with singular value decomposition and conjugate gradient is suggested in seeing the outcomes of the comparisons carried out on least‐squares solutions with singular value decomposition and conjugate gradient algorithms subject to a variety of stabilizers. Inversion results of synthetic data showed that the newly suggested algorithm yields better results than those of the individual implementations of conjugate gradient and least‐squares solution with singular value decomposition algorithms. The suggested algorithm and the above‐mentioned algorithms inversion results for the field data collected along a line crossing the North Anatolian Fault zone were also compared each other and results are discussed.     

大地电磁法三维共轭梯度反演研究

Based on the analysis of the conjugate gradient algorithm, we implement a threedimensional （3D） conjugate gradient inversion algorithm with magnetotelluric impedance data. During the inversion process, the 3D conjugate gradient inversion algorithm doesn＇ t need to compute and store the Jacobian matrix but directly updates the model from the computation of the Jacobian matrix. Requiring only one forward and four pseudo-forward modeling applications per frequency to produce the model update at each iteration, this algorithm efficiently reduces the computation of the inversion. From a trial inversion with synthetic magnetotelluric data, the validity and stability of the 3D conjugate gradient inversion algorithm is verified.     

基于数据空间和稀疏约束的三维重力和重力梯度数据联合反演

随着重力和重力梯度测量技术的日趋成熟,基于重力和重力梯度数据的反演技术得到了广泛关注.针对反演多解性严重、计算效率低和内存消耗大等难点问题,本文开展了三维重力和重力梯度数据的联合反演研究,该方法结合重力和重力梯度两种数据,将L0范数正则化项加入到目标函数中,并在数据空间下采用改进的共轭梯度算法求解反演最优化问题.同时,本文摒弃了依赖先验信息的深度加权函数,引入了自适应模型积分灵敏度矩阵,用来克服因重力和重力梯度数据核函数随深度增加而衰减引起的趋肤效应问题.为了提高反演计算效率,本文又推导出基于规则网格化的重力和重力梯度快速正演计算方法.模拟试算表明,改进的共轭梯度法可以降低反演的迭代次数,提高反演的收敛速度;自适应模型积分灵敏度矩阵,可以有效解决趋肤效应,提高反演纵向分辨能力;数据空间和改进的共轭梯度算法结合,可以更好地降低反演求解方程的维度,避免存储灵敏度矩阵,有效地降低反演计算时间和内存消耗量.野外实例表明,该算法可以在普通计算机下快速地获得地下密度分布模型,表现出较强的稳定性和适用性.     

Delineation of layer boundaries from smooth models obtained from the geoelectrical sounding data inversion

Two techniques have been presented for the delineation of boundaries from smooth models obtained by smooth inversion techniques of geoelectrical sounding data, such as straightforward inversion scheme, Occam’s and Zohdy’s methods. The smooth model consists of a large number of equally spaced layers, wherein the real geological boundaries are missing. The techniques proposed here suppress the geologically irrelevant boundaries and support the real structural boundaries present in the geoelectrical data. In the first technique, solution of linear inverse problem is improved iteratively through weighted minimum norm inverse, the weight being taken from the current solution. The technique is referred as Iterative Straightforward Inversion Scheme. The second method is analytical, based on the application of smoothing filter, referred in the literature as edge-preserving smoothing. A few examples of theoretical magnetotelluric, dc resistivity and field sounding data have been presented to demonstrate the capabilities of the techniques. The methodologies also reduce the conspicuous oscillations in the smooth solutions caused by the conversion of sharp boundaries to the smooth ones.     

Application of Large‐Scale Inversion Algorithms to Hydraulic Tomography in an Alluvial Aquifer

Large‐scale inversion methods have been recently developed and permitted now to considerably reduce the computation time and memory needed for inversions of models with a large amount of parameters and data. In this work, we have applied a deterministic geostatistical inversion algorithm to a hydraulic tomography investigation conducted in an experimental field site situated within an alluvial aquifer in Southern France. This application aims to achieve a 2‐D large‐scale modeling of the spatial transmissivity distribution of the site. The inversion algorithm uses a quasi‐Newton iterative process based on a Bayesian approach. We compared the results obtained by using three different methodologies for sensitivity analysis: an adjoint‐state method, a finite‐difference method, and a principal component geostatistical approach (PCGA). The PCGA is a large‐scale adapted method which was developed for inversions with a large number of parameters by using an approximation of the covariance matrix, and by avoiding the calculation of the full Jacobian sensitivity matrix. We reconstructed high‐resolution transmissivity fields (composed of up to 25,600 cells) which generated good correlations between the measured and computed hydraulic heads. In particular, we show that, by combining the PCGA inversion method and the hydraulic tomography method, we are able to substantially reduce the computation time of the inversions, while still producing high‐quality inversion results as those obtained from the other sensitivity analysis methodologies.     

基于模型空间压缩的大地电磁三维反演研究

本文提出了一种基于模型空间压缩技术的大地电磁三维反演方法.该方法在传统大地电磁三维反演理论的基础上,通过小波变换将待反演的空间域模型参数映射到小波域进行反演,获得小波域更新模型后再通过小波逆变换得到空间域反演模型.由于小波变换具有压缩特性和多尺度分辨能力,本文反演方法可在一定程度上提高反演分辨率.为了提高反演效率,我们针对基于L_1范数的模型约束求解不易收敛的反演问题,提出了一种基于模型粗糙度的简单有效的预条件处理技术.为验证本文算法的有效性,本文首先对经典的"棋盘"模型进行三维反演测试.反演结果表明本文算法的反演效率与传统方法相当,但对于深部异常体具有更好的分辨能力.最后,我们通过对实测数据反演进一步验证本文算法的有效性.     

Double parameterized regularization inversion method for migration velocity analysis in transversely isotropic media with a vertical symmetry axis

Simultaneous estimation of velocity gradients and anisotropic parameters from seismic reflection data is one of the main challenges in transversely isotropic media with a vertical symmetry axis migration velocity analysis. In migration velocity analysis, we usually construct the objective function using the l₂ norm along with a linear conjugate gradient scheme to solve the inversion problem. Nevertheless, for seismic data this inversion scheme is not stable and may not converge in finite time. In order to ensure the uniform convergence of parameter inversion and improve the efficiency of migration velocity analysis, this paper develops a double parameterized regularization model and gives the corresponding algorithms. The model is based on the combination of the l₂ norm and the non‐smooth l₁ norm. For solving such an inversion problem, the quasi‐Newton method is utilized to make the iterative process stable, which can ensure the positive definiteness of the Hessian matrix. Numerical simulation indicates that this method allows fast convergence to the true model and simultaneously generates inversion results with a higher accuracy. Therefore, our proposed method is very promising for practical migration velocity analysis in anisotropic media.     

重力异常的BP神经网络三维物性反演

三维物性反演参数多,计算量巨大,传统的方法难以实现.本文使用BP神经网络实现重力三维物性反演,介绍了BP神经网络的基本原理及特性,并构造一个适用于重力位场反演的BP神经网络.并用其对模型进行反演计算,结果表明:BP网络具有较好的泛化能力和容错能力,反演速度快、准确,并且较好的反应了场源的分布情况.     

Linearized rays,amplitude and inversion

In this paper, ray theoretical amplitudes and travel times are calculated in slightly perturbed velocity models using perturbation analysis. Also, test inversions using travel time and amplitude are computed. The pertubation method is tested using a 3-D velocity model for NORSAR having velocity variations up to 8.0 percent. The perturbed amplitudes are found to be in excellent agreement with the calculated ray amplitudes. Velocity inversions based on travel time and amplitude are next investigated. Perturbation analysis using linearized ray equations is efficiently used to compute amplitude derivatives with respect to model parameters. The trial linearized inversions use smaller velocity variations of 1.7 percent to avoid possible effects due to ray shift, even though the perturbation analysis is valid for larger variations. The trial 2-D inversion results show that linearized amplitude inversions are complementary and not redundant to travel time inversions, even in smoothly varying models.     

Effect of lateral variation and model parameterization on surface wave dispersion inversion to estimate the average shallow structure in the Paraná Basin

The average layered structure of the intracratonic Paraná Basin, SE Brazil, is investigated with surface-wave group velocities from a small regional earthquake recorded by two broadband stations. Rayleigh and Love waves in the period range 1–4.2 s are used to infer average properties down to about 4 km. Genetic algorithm techniques are used to find the best fitting 1-D S-wave model. The inverted 1-D models show fair correlation with the average properties of the propagation paths as expected from geology and borehole information. However, different S-wave velocity models are obtained for the different inversion parameterizations. Since lateral heterogeneities are expected along the paths, several synthetic tests are performed with heterogeneous propagation paths. For approximately homogenous path (i.e., little lateral variation), the main features of the average synthetic model can be retrieved for different model parameterizations. For strong lateral variations, however, the average dispersion curve can produce very different 1-D inverted models depending on the parameterization. Also, the 1-D inverted models may differ significantly from the average properties of the inhomogeneous path, and wrong depths to interfaces may be inferred. For real data inversions, it is then suggested that various different parameterizations should be tested. If the resulting models show consistent features, this probably indicates homogeneity in the propagation path. But, if very different and unstable features are obtained in the 1-D inversions, then strong lateral variation may be present in the propagation path, and the average 1-D model may not represent average properties along the path.     

基于印模法的地面磁电阻率数据三维非线性共轭梯度反演

本文提出了能提高异常体分辨能力,同时得到绝对电导率的地面磁电阻率数据三维反演方法.磁电阻率响应用准直流的低频磁场代替;数值模拟由频率域电场满足的Helmholtz方程出发,采用三维交错网格有限差分法;长直导线源作为发射源,其中源的计算包含在背景场中;结合地面磁电阻率数据各分量的特点,选择y分量进行反演研究;反演采用三维非线性共轭梯度反演技术,为了提高异常体的深度分辨能力,进行迭代重构反演;用印模法对初始模型进行重构,采用的是辅模型在浅部,元模型在深部的组合方式.从合成数据和实际数据的反演结果可以得到以下的认识:(1)由频率域麦克斯韦方程组出发,低频磁场数据反演可以直接得到电导率,而不是相对电导率之比;(2)采用印模法组合初始模型,进行迭代重构反演,可以提高地面磁电阻率数据反演对异常体的分辨能力,确定埋深位置,同时不会丧失对于浅部异常体的分辨能力;(3)在结合印模法的地面磁电阻率数据三维反演中,深部异常体的分辨能力受地表不均匀导电体影响较小;(4)确定印模深度可以采用上一次重构反演结束时的模型变化量,通过相邻两次重构反演结束时的模型变化量之差来确定迭代重构是否终止.因为静磁场与重力场在数学上的相似性,本文的反演方法可以被运用到重力场等位场的地面数据的反演中.