First‐arrival traveltime tomography with modified total‐variation regularization

First‐arrival traveltime tomography is a robust tool for near‐surface velocity estimation. A common approach to stabilizing the ill‐posed inverse problem is to apply Tikhonov regularization to the inversion. However, the Tikhonov regularization method recovers smooth local structures while blurring the sharp features in the model solution. We present a first‐arrival traveltime tomography method with modified total‐variation regularization to preserve sharp velocity contrasts and improve the accuracy of velocity inversion. To solve the minimization problem of the new traveltime tomography method, we decouple the original optimization problem into the two following subproblems: a standard traveltime tomography problem with the traditional Tikhonov regularization and a L₂ total‐variation problem. We apply the conjugate gradient method and split‐Bregman iterative method to solve these two subproblems, respectively. Our synthetic examples show that the new method produces higher resolution models than the conventional traveltime tomography with Tikhonov regularization, and creates less artefacts than the total variation regularization method for the models with sharp interfaces. For the field data, pre‐stack time migration sections show that the modified total‐variation traveltime tomography produces a near‐surface velocity model, which makes statics corrections more accurate.     

基于精确震源函数的解调包络多尺度全波形反演

本文提出解调包络方法来重构地震记录中缺失的低频信号,同时该方法能够降低全波形反演的非线性程度;提出伴随状态震源函数反演方法来得到精确的震源函数,并推导了梯度计算公式;解调包络方法结合低通滤波技术,实现了从低频到高频的多尺度反演策略,有效缓解了全波形反演的周波跳跃问题.数值算例证明了解调包络、伴随状态震源函数反演方法和低通滤波多尺度反演策略的可行性及优越性.震源函数反演精度测试结果表明:即使观测记录在缺失低频信息的情况下,也能反演得到精确的震源函数.缺失低频测试和抗噪能力测试结果表明:即使地震数据中缺失9Hz以下的低频信号或者信噪比极低的情况下,利用反演得到的精确震源函数进行解调包络多尺度全波形反演,同样可以得到高精度的全波形反演结果.与Hilbert包络全波形反演对比结果表明:解调包络在重构低频和降低伴随震源主频方面具有一定优势.     

不依赖子波、基于包络的FWI初始模型建立方法研究

地震全波形反演(FWI)从理论走向实际面临着诸多难题,其中之一就是需要一个较高精度的初始模型,另一个难题就是需要一个较为精确的震源子波,初始模型和震源子波的准确程度严重影响着全波形反演的最终结果.为此,本文提出了不依赖子波、基于包络的FWI初始模型建立的方法,建立了相应的目标函数,推导出了反演的梯度,给出了伴随震源的表达式,理论上分析了不依赖子波FWI的可行性.在数值试验中,讨论了参考道的选取方式,通过分析归一化目标函数收敛速率,认为近偏移距参考道优于远偏移距参考道,在地震数据含干扰噪音时,平均道作为参考道要优于最小偏移距参考道.通过包络、包络对数、包络平方三种目标函数反演结果的比较,发现包络对数目标函数对深层的反演效果最好.通过不同子波的试验进一步验证了本方法的正确性.     

Identification of lateral discontinuities via multi‐offset phase analysis of surface wave data

Surface wave methods are based on the inversion of observed Rayleigh wave phase‐velocity dispersion curves. The goal is to estimate mainly the shear‐wave velocity profile of the investigated site. The model used for the interpretation is 1D, hence results obtained wherever lateral variations are present cannot be considered reliable. In this paper, we study four synthetic models, all with a lateral heterogeneity. When we process the entire corresponding seismograms with traditional f‐k approach, the resulting 1D profiles are representative of the subsurface properties averaged over the whole length of the receivers lines. These results show that classical analysis disregards evidences of sharp lateral velocity changes even when they show up in the raw seismograms. In our research, we implement and test over the same synthetic models, a novel robust automated method to check the appropriateness of 1D model assumption and locate the discontinuities. This new approach is a development of the recent multi‐offset phase analysis with the following further advantages: it does not need previous noise evaluation and more than one shot. Only once the discontinuities are clearly identified, we confidently perform classical f‐k dispersion curve extraction and inversion separately on both sides of the discontinuity. Thus the final results, obtained by putting side by side the 1D profiles, are correct 2D reconstructions of the discontinuous S‐wave distributions obtained without any additional ad‐hoc hypotheses.     

On the effective inversion by imposing <Emphasis Type="Italic">a priori</Emphasis> information for retrieval of land surface parameters

The anisotropy of the land surface can be best described by the bidirectional reflectance distribution function (BRDF). As the field of multiangular remote sensing advances, it is increasingly probable that BRDF models can be inverted to estimate the important biological or climatological parameters of the earth surface such as leaf area index and albedo. The state-of-the-art of BRDF is the use of the linear kernel-driven models, mathematically described as the linear combination of the isotropic kernel, volume scattering kernel and geometric optics kernel. The computational stability is characterized by the algebraic operator spectrum of the kernel-matrix and the observation errors. Therefore, the retrieval of the model coefficients is of great importance for computation of the land surface albedos. We first consider the smoothing solution method of the kernel-driven BRDF models for retrieval of land surface albedos. This is known as an ill-posed inverse problem. The ill-posedness arises from that the linear kernel driven BRDF model is usually underdetermined if there are too few looks or poor directional ranges, or the observations are highly dependent. For example, a single angular observation may lead to an under-determined system whose solution is infinite (the null space of the kernel operator contains nonzero vectors) or no solution (the rank of the coefficient matrix is not equal to the augmented matrix). Therefore, some smoothing or regularization technique should be applied to suppress the ill-posedness. So far, least squares error methods with a priori knowledge, QR decomposition method for inversion of the BRDF model and regularization theories for ill-posed inversion were developed. In this paper, we emphasize on imposing a priori information in different spaces. We first propose a general a priori imposed regularization model problem, and then address two forms of regularization scheme. The first one is a regularized singular value decomposition method, and then we propose a retrieval method in I ¹ space. We show that the proposed method is suitable for solving land surface parameter retrieval problem if the sampling data are poor. Numerical experiments are also given to show the efficiency of the proposed methods. Supported by National Natural Science Foundation of China (Grant Nos. 10501051, 10871191), and Key Project of Chinese National Programs for Fundamental Research and Development (Grant Nos. 2007CB714400, 2005CB422104)     

A non-linear regularized constrained impedance inversion

Inversion for seismic impedance is an inherently complicated problem. It is ill‐posed and band‐limited. Thus the inversion results are non‐unique and the process is unstable. Combining regularization with constraints using sonic and density log data can help to reduce these problems. To achieve this, we developed an inversion method by constructing a new objective function, including edge‐preserving regularization and a soft constraint based on a Markov random field. The method includes the selection of proper initial values of the regularization parameters by a statistical method, and it adaptively adjusts the regularization parameters by the maximum likelihood method in a fast simulated‐annealing procedure to improve the inversion result and the convergence speed. Moreover, the method uses two kinds of regularization parameter: a ‘weighting factor’λ and a ‘scaling parameter’δ. We tested the method on both synthetic and field data examples. Tests on 2D synthetic data indicate that the inversion results, especially the aspects of the discontinuity, are significantly different for different regularization functions. The initial values of the regularization parameters are either too large or too small to avoid either an unstable or an over‐smoothed result, and they affect the convergence speed. When selecting the initial values of λ, the type of the regularization function should be considered. The results obtained by constant regularization parameters are smoother than those obtained by adaptively adjusting the regularization parameters. The inversion results of the field data provide more detailed information about the layers, and they match the impedance curves calculated from the well logs at the three wells, over most portions of the curves.     

基于混叠震源和频率组编码的频率域自适应全波形反演(英文)

全波形反演是一种高精度的地震成像方法,可以对地下介质物性参数模型进行准确的重构。然而在实际应用中,尤其是在三维复杂介质反演中,计算成本太大是该方法的一个重要缺陷。将混叠震源技术引入到频率域全波形反演中可以大幅度地降低计算成本,提高反演效率。但是使用震源编码技术也带来了两个问题:一方面,参与编码的各个震源之间会产生"串扰噪声",导致反演结果中出现假象;另一方面,基于震源编码的频率域全波形反演方法周围噪声较为敏感,使该方法对含噪数据反演质量较差。本文引入一种频率组编码方法来压制"串扰噪声",并基于震源编码技术提出一种频率域自适应全波形反演方法,通过一个与频率相关的自适应选择机制,将常规频率域全波形反演方法和基于震源编码的全波形反演方法联合起来,在保证反演质量的同时也最大程度地提高了反演效率。     

频率域全波形反演中关于复频率的研究

Laplace-Fourier域全波形反演可以利用简单的初始模型,从缺失低频信息的地震数据中得到长波长速度模型.Laplace-Fourier域全波形反演等价于本文的复频率全波形反演,但二者的实现方式不同,因此研究复频率全波形反演,可以为二者的对比研究并发展更有效的方法奠定重要基础.本文首先比较用线性增加模型作为初始模型时几个包含不同高低频成分的频率组的反演效果,再比较结合复频率之后各个频率组的反演效果,从简单模型和复杂模型的测试中都可以看出这种复频率+频率反演的方式对反演效果有明显改善.     

Sharp spatially constrained inversion with applications to transient electromagnetic data

Time‐domain electromagnetic data are conveniently inverted by using smoothly varying 1D models with fixed vertical discretization. The vertical smoothness of the obtained models stems from the application of Occam‐type regularization constraints, which are meant to address the ill‐posedness of the problem. An important side effect of such regularization, however, is that horizontal layer boundaries can no longer be accurately reproduced as the model is required to be smooth. This issue can be overcome by inverting for fewer layers with variable thicknesses; nevertheless, to decide on a particular and constant number of layers for the parameterization of a large survey inversion can be equally problematic. Here, we present a focusing regularization technique to obtain the best of both methodologies. The new focusing approach allows for accurate reconstruction of resistivity distributions using a fixed vertical discretization while preserving the capability to reproduce horizontal boundaries. The formulation is flexible and can be coupled with traditional lateral/spatial smoothness constraints in order to resolve interfaces in stratified soils with no additional hypothesis about the number of layers. The method relies on minimizing the number of layers of non‐vanishing resistivity gradient, instead of minimizing the norm of the model variation itself. This approach ensures that the results are consistent with the measured data while favouring, at the same time, the retrieval of horizontal abrupt changes. In addition, the focusing regularization can also be applied in the horizontal direction in order to promote the reconstruction of lateral boundaries such as faults. We present the theoretical framework of our regularization methodology and illustrate its capabilities by means of both synthetic and field data sets. We further demonstrate how the concept has been integrated in our existing spatially constrained inversion formalism and show its application to large‐scale time‐domain electromagnetic data inversions.     

1D joint multi‐offset inversion of time‐domain marine controlled source electromagnetic data

The accurate estimation of sub‐seafloor resistivity features from marine controlled source electromagnetic data using inverse modelling is hindered due to the limitations of the inversion routines. The most commonly used one‐dimensional inversion techniques for resolving subsurface resistivity structures are gradient‐based methods, namely Occam and Marquardt. The first approach relies on the smoothness of the model and is recommended when there are no sharp resistivity boundaries. The Marquardt routine is relevant for many electromagnetic applications with sharp resistivity contrasts but subject to the appropriate choice of a starting model. In this paper, we explore the ability of different 1D inversion schemes to derive sub‐seafloor resistivity structures from time domain marine controlled source electromagnetic data measured along an 8‐km‐long profile in the German North Sea. Seismic reflection data reveal a dipping shallow amplitude anomaly that was the target of the controleld source electromagnetic survey. We tested four inversion schemes to find suitable starting models for the final Marquardt inversion. In this respect, as a first scenario, Occam inversion results are considered a starting model for the subsequent Marquardt inversion (Occam–Marquardt). As a second scenario, we employ a global method called Differential Evolution Adaptive Metropolis and sequentially incorporate it with Marquardt inversion. The third approach corresponds to Marquardt inversion introducing lateral constraints. Finally, we include the lateral constraints in Differential Evolution Adaptive Metropolis optimization, and the results are sequentially utilized by Marquardt inversion. Occam–Marquardt may provide accurate estimation of the subsurface features, but it is dependent on the appropriate conversion of different multi‐layered Occam model to an acceptable starting model for Marquardt inversion, which is not straightforward. Employing parameter spaces, the Differential Evolution Adaptive Metropolis approach can be pertinent to determine Marquardt a priori information; nevertheless, the uncertainties in Differential Evolution Adaptive Metropolis optimization will introduce some inaccuracies in Marquardt inversion results. Laterally constrained Marquardt may be promising to resolve sub‐seafloor features, but it is not stable if there are significant lateral changes of the sub‐seafloor structure due to the dependence of the method to the starting model. Including the lateral constraints in Differential Evolution Adaptive Metropolis approach allows for faster convergence of the routine with consistent results, furnishing more accurate estimation of a priori models for the subsequent Marquardt inversion.     

简化混合域全波形反演多GPU加速策略

全波形反演利用地震记录中的振幅、走时和相位等信息,通过拟合实际地震记录和计算波场来定量提取地下介质的弹性参数,进而为勘探地震成像、速度建模以及大尺度构造演化分析等提供可靠依据.但全波形反演计算量巨大,特别是应用于三维大区块叠前数据时,生产成本仍然很高.本文介绍并比较了时间域和频率域的全波形反演方法,综合两者的优点,最终采用混合域的反演算法,并且在此基础上做了进一步的简化以提高计算效率.针对全波形反演方法应用于大规模叠前数据时易陷入局部极小值的问题,我们提出对模型数据进行分割,同时在数个小模型内进行梯度搜索,然后对比各个局域的梯度,最终找出合适的全局下降方向,以克服局部极小的隐患.该方法能够充分利用GPU的硬件特性.在GPU环境下实现本文所提出的简化混合域全波形反演算法.数值计算实例体现出新方法具有良好的计算效率、反演精度和算法可扩展性.     

变密度声波方程多参数全波形反演策略

多参数全波形反演中各参数之间的相互耦合增加了反演的非线性程度.通过分析各参数之间的相互影响,提出合理的多参数反演策略是解决该问题的有效途径.本文从变密度声波方程出发,首先研究了密度在速度反演中的重要作用,然后分析了速度对密度反演的影响程度,进而提出了一种有利于速度、密度分步联合反演的策略.第一步,利用给定的初始模型对速度、密度进行同时反演,得到比较可靠的速度反演结果;第二步,利用第一步反演得到的速度和给定的初始密度作为初始模型,继续进行双参数同时反演,这样可以同时得到比较可靠的速度、密度反演结果.为了进一步提高反演精度,将第二步反演得到的速度、密度作为初始模型,再进行下一轮双参数联合反演.二维理论模型实验结果充分说明了本文提出的这种反演策略的有效性.     

Quasi-2D hybrid joint inversion of seismic and geoelectric data

Many joint inversion schemes use 1D forward modelling in the integrated interpretation of various geophysical data. In extending the joint inversion approach to the investigation of 2D structures, the discretization of the model parameters and the appropriate choice of the forward‐modelling procedure play a very important role. In this paper, a hybrid seismic–geoelectric joint inversion method is proposed for the investigation of 2D near‐surface geological structures. The electric and seismic models are coupled together through the use of common boundaries between the adjacent layers. Assuming a 2D model composed of homogeneous layers with curved boundaries, a fast ray‐tracing algorithm is used for the calculation of refraction seismic traveltime data. In the geoelectric forward modelling, a locally 1D approximation is used. The boundary surfaces are written in the form of series expansion; the inversion algorithms are formulated for the expansion coefficients and the petrophysical parameters as unknowns. Two versions of the inversion method are proposed: in versions A and B, interval‐wise constant functions and Chebyshev polynomials are, respectively, used as basis functions of the series expansion. The versions are tested by means of synthetic and in situ measured data. The tests show that both methods are stable and accurate.     

Applying essentially non‐oscillatory interpolation to controlled‐source electromagnetic modelling*

Modelling and inversion of controlled‐source electromagnetic (CSEM) fields requires accurate interpolation of modelled results near strong resistivity contrasts. There, simple linear interpolation may produce large errors, whereas higher‐order interpolation may lead to oscillatory behaviour in the interpolated result. We propose to use the essentially non‐oscillatory, piecewise polynomial interpolation scheme designed for piecewise smooth functions that contains discontinuities in the function itself or in its first or higher derivatives. The scheme uses a non‐linear adaptive algorithm to select a set of interpolation points that represent the smoothest part of the function among the sets of neighbouring points. We present numerical examples to demonstrate the usefulness of the scheme. The first example shows that the essentially non‐oscillatory interpolation (ENO) scheme better captures an isolated discontinuity. In the second example, we consider the case of sampling the electric field computed by a finite‐volume CSEM code at a receiver location. In this example, the ENO interpolation performs quite well. However, the overall error is dominated by the discretization error. The other examples consider the comparison between sampling with essentially non‐oscillatory interpolation and existing interpolation schemes. In these examples, essentially non‐oscillatory interpolation provides more accurate results than standard interpolation, especially near discontinuities.     

Regularized inversion of amplitude-versus-incidence angle (AVA) based on a piecewise-smooth model

Different from the stacked seismic data, pre-stack data includes abundant information about shear wave and density. Through inversing the shear wave and density information from the pre-stack data, we can determine oil-bearing properties from different incident angles. The state-of-the-art inversion methods obtain either low vertical resolution or lateral discontinuities. However, the practical reservoir generally has sharp discontinuities between different layers in vertically direction and is horizontally smooth. Towards obtaining the practical model, we present an inversion method based on the regularized amplitude-versus-incidence angle (AVA) data to estimate the piecewise-smooth model from pre-stack seismic data. This method considers subsurface stratum as a combination of two parts: a piecewise smooth part and a constant part. To fix the ill-posedness in the inversion, we adopt four terms to define the AVA inversion misfit function: the data misfit itself, a total variation regularization term acting as a sparsing operator for the piecewise constant part, a Tikhonov regularization term acting as a smoothing operator for the smooth part, and the last term to smoothly incorporate a priori information for constraining the magnitude of the estimated model. The proposed method not only can incorporate structure information and a priori model constraint, but also is able to derive into a convex objective function that can be easily minimized using iterative approach. Compared with inversion results of TV and Tikhonov regularization methods, the inverted P-wave velocity, S-wave velocity and density of the proposed method can better delineate the piecewise-smooth characteristic of strata.     

基于交叉梯度约束的地震初至纵波与瑞雷面波联合反演

本文提出了一种初至纵波(P波)与瑞雷面波的交叉梯度联合反演策略.通过对初至P波进行全波形反演可以获得近地表P波速度结构;通过对仅含瑞雷面波信息的地震数据转换到频率-波数域进行加窗振幅波形反演(Windowed-Amplitude Waveform Inversion,w-AWI)可获得近地表横波(S波)速度结构.在二者反演的目标函数中均加入P波速度和S波速度的交叉梯度作为正则化约束项,使得在反演过程中P波速度和S波速度相互制约,相互约束,从而实现对地震初至P波与瑞雷面波的联合反演.数值模拟结果表明交叉梯度联合反演可以提高S波速度反演分辨率,而P波速度反演结果并没有得到提高.实际资料的反演结果表明,交叉梯度联合反演能够获得更加可信的近地表速度结构.     

Suppressing non‐Gaussian noises with scaled receiver wavefield for reverse‐time migration: comparison of different approaches

Numerical implementation of the gradient of the cost function in a gradient‐based full‐ waveform inversion (FWI) is essentially a migration operator used in wave equation migration. In FWI, minimizing different data residual norms results in different weighting strategies of data residuals at receiver locations prior to back‐propagation into the medium. In this paper, we propose different scaling methods to the receiver wavefield and compare their performances. Using time‐domain reverse‐time migration (RTM), we show that compared to conventional algorithms, this type of scaling is able to significantly suppress non‐Gaussian noise, i.e., outliers. Our tests also show that scaling by its absolute norm produces better results than other approaches.     

基于Born敏感核函数的速度、密度双参数全波形反演

速度、密度之间的相互耦合使得密度在多参数全波形反演中较难获得.本文将截断高斯-牛顿法用于声介质速度、密度双参数全波形反演,通过考虑近似Hessian矩阵中反映速度、密度相互作用的非主对角块元素,有效解决了多参数全波形反演中速度、密度之间的耦合问题,在不采用反演策略的情况下,仍能够获得精度较高的速度、密度反演结果.常规的截断牛顿类全波形反演通常利用一阶伴随状态法求取目标函数对模型参数的梯度,利用二阶伴随状态法或有限差分法求解Hessian-向量乘,在每一步内循环迭代过程中需要额外求解两次正演问题,计算量较大.本文基于Born近似,将梯度计算中的核函数-向量乘表示为具有明确物理意义的向量-标量乘的累加运算,同时将Hessian-向量乘转化为两次核函数-向量乘,无需额外求解正演问题,有效降低了计算量.数值实验证明了本文提出的方法的有效性.     

基于改进全变差正则化的GPR多尺度全波形双参数同步反演

针对探地雷达（GPR）双参数全波形反演中电导率反演精度差、双参数存在串扰现象、反演计算量大、易陷入局部极值等问题.作者将具有多参数调节功能的L-BFGS算法引入到GPR时间域全波形反演中,它避免了对Hessian矩阵的直接存储与精确求解,减小了存储量和计算量.结合参数调节因子的选取,有效减小了同步反演时介电常数与电导率的串扰影响,在不降低介电常数反演精度的前提下,提高电导率参数的反演精度.通过在反演目标函数中加载改进全变差正则化方法,提高了反演的稳定性,使目标体边缘轮廓更加清晰.首先以简单模型为例,对比了单尺度反演与多尺度串行反演策略的优劣,说明多尺度串行反演有利于逐步搜索全局最优解;而开展参数调节因子的选取实验,说明合适的参数调节因子可以有效改善介质电导率的反演精度;测试了不同正则化的反演效果,表明改进全变差正则化能提高反演稳定性,显著降低模型重构误差.最后,分别对含噪合成数据和实测数据进行了反演测试,说明本文提出的多尺度、双参数反演具有较强的鲁棒性,能提供更丰富的信息约束,重构图像界面清晰、反演效果好.     

Piecewise‐continuous velocity inversion

We suggest a new method to determine the piecewise‐continuous vertical distribution of instantaneous velocities within sediment layers, using different order time‐domain effective velocities on their top and bottom points. We demonstrate our method using a synthetic model that consists of different compacted sediment layers characterized by monotonously increasing velocity, combined with hard rock layers, such as salt or basalt, characterized by constant fast velocities, and low velocity layers, such as gas pockets. We first show that, by using only the root‐mean‐square velocities and the corresponding vertical travel times (computed from the original instantaneous velocity in depth) as input for a Dix‐type inversion, many different vertical distributions of the instantaneous velocities can be obtained (inverted). Some geological constraints, such as limiting the values of the inverted vertical velocity gradients, should be applied in order to obtain more geologically plausible velocity profiles. In order to limit the non‐uniqueness of the inverted velocities, additional information should be added. We have derived three different inversion solutions that yield the correct instantaneous velocity, avoiding any a priori geological constraints. The additional data at the interface points contain either the average velocities (or depths) or the fourth‐order average velocities, or both. Practically, average velocities can be obtained from nearby wells, whereas the fourth‐order average velocity can be estimated from the quartic moveout term during velocity analysis. Along with the three different types of input, we consider two types of vertical velocity models within each interval: distribution with a constant velocity gradient and an exponential asymptotically bounded velocity model, which is in particular important for modelling thick layers. It has been shown that, in the case of thin intervals, both models lead to similar results. The method allows us to establish the instantaneous velocities at the top and bottom interfaces, where the velocity profile inside the intervals is given by either the linear or the exponential asymptotically bounded velocity models. Since the velocity parameters of each interval are independently inverted, discontinuities of the instantaneous velocity at the interfaces occur naturally. The improved accuracy of the inverted instantaneous velocities is particularly important for accurate time‐to‐depth conversion.