Multipathing in three‐parameter common‐image gathers from reverse‐time migration

Reverse‐time migration gives high‐quality, complete images by using full‐wave extrapolations. It is thus not subject to important limitations of other migrations that are based on high‐frequency or one‐way approximations. The cross‐correlation imaging condition in two‐dimensional pre‐stack reverse‐time migration of common‐source data explicitly sums the product of the (forward‐propagating) source and (backward‐propagating) receiver wavefields over all image times. The primary contribution at any image point travels a minimum‐time path that has only one (specular) reflection, and it usually corresponds to a local maximum amplitude. All other contributions at the same image point are various types of multipaths, including prismatic multi‐arrivals, free‐surface and internal multiples, converted waves, and all crosstalk noise, which are imaged at later times, and potentially create migration artefacts. A solution that facilitates inclusion of correctly imaged, non‐primary arrivals and removal of the related artefacts, is to save the depth versus incident angle slice at each image time (rather than automatically summing them). This results in a three‐parameter (incident angle, depth, and image time) common‐image volume that integrates, into a single unified representation, attributes that were previously computed by separate processes. The volume can be post‐processed by selecting any desired combination of primary and/or multipath data before stacking over image time. Separate images (with or without artifacts) and various projections can then be produced without having to remigrate the data, providing an efficient tool for optimization of migration images. A numerical example for a simple model shows how primary and prismatic multipath contributions merge into a single incident angle versus image time trajectory. A second example, using synthetic data from the Sigsbee2 model, shows that the contributions to subsalt images of primary and multipath (in this case, turning wave) reflections are different. The primary reflections contain most of the information in regions away from the salt, but both primary and multipath data contribute in the subsalt region.     

Linear geophysical inversion via the discrete cosine pseudo‐inverse: application to potential fields

In this paper, we present a methodology to perform geophysical inversion of large‐scale linear systems via a covariance‐free orthogonal transformation: the discrete cosine transform. The methodology consists of compressing the matrix of the linear system as a digital image and using the interesting properties of orthogonal transformations to define an approximation of the Moore–Penrose pseudo‐inverse. This methodology is also highly scalable since the model reduction achieved by these techniques increases with the number of parameters of the linear system involved due to the high correlation needed for these parameters to accomplish very detailed forward predictions and allows for a very fast computation of the inverse problem solution. We show the application of this methodology to a simple synthetic two‐dimensional gravimetric problem for different dimensionalities and different levels of white Gaussian noise and to a synthetic linear system whose system matrix has been generated via geostatistical simulation to produce a random field with a given spatial correlation. The numerical results show that the discrete cosine transform pseudo‐inverse outperforms the classical least‐squares techniques, mainly in the presence of noise, since the solutions that are obtained are more stable and fit the observed data with the lowest root‐mean‐square error. Besides, we show that model reduction is a very effective way of parameter regularisation when the conditioning of the reduced discrete cosine transform matrix is taken into account. We finally show its application to the inversion of a real gravity profile in the Atacama Desert (north Chile) obtaining very successful results in this non‐linear inverse problem. The methodology presented here has a general character and can be applied to solve any linear and non‐linear inverse problems (through linearisation) arising in technology and, particularly, in geophysics, independently of the geophysical model discretisation and dimensionality. Nevertheless, the results shown in this paper are better in the case of ill‐conditioned inverse problems for which the matrix compression is more efficient. In that sense, a natural extension of this methodology would be its application to the set of normal equations.     

Point‐spread functions for interferometric imaging

Interferometric redatuming is a data‐driven method to transform seismic responses with sources at one level and receivers at a deeper level into virtual reflection data with both sources and receivers at the deeper level. Although this method has traditionally been applied by cross‐correlation, accurate redatuming through a heterogeneous overburden requires solving a multidimensional deconvolution problem. Input data can be obtained either by direct observation (for instance in a horizontal borehole), by modelling or by a novel iterative scheme that is currently being developed. The output of interferometric redatuming can be used for imaging below the redatuming level, resulting in a so‐called interferometric image. Internal multiples from above the redatuming level are eliminated during this process. In the past, we introduced point‐spread functions for interferometric redatuming by cross‐correlation. These point‐spread functions quantify distortions in the redatumed data, caused by internal multiple reflections in the overburden. In this paper, we define point‐spread functions for interferometric imaging to quantify these distortions in the image domain. These point‐spread functions are similar to conventional resolution functions for seismic migration but they contain additional information on the internal multiples in the overburden and they are partly data‐driven. We show how these point‐spread functions can be visualized to diagnose image defocusing and artefacts. Finally, we illustrate how point‐spread functions can also be defined for interferometric imaging with passive noise sources in the subsurface or with simultaneous‐source acquisition at the surface.     

System identification of the Vincent Thomas suspension bridge using earthquake records

The Vincent Thomas Bridge in the Los Angeles metropolitan area, is a critical artery for commercial traffic flow in and out of the Los Angeles Harbor, and is at risk in the seismically active Southern California region, particularly because it straddles the Palos Verdes fault zone. A combination of linear and non‐linear system identification techniques is employed to obtain a complete reduced‐order, multi‐input–multi‐output (MIMO) dynamic model of the Vincent Thomas Bridge based on the dynamic response of the structure to the 1987 Whittier and 1994 Northridge earthquakes. Starting with the available acceleration measurements (which consists of 15 accelerometers on the bridge structure and 10 accelerometers at various locations on its base), an efficient least‐squares‐based time‐domain identification procedure is applied to the data set to develop a reduced‐order, equivalent linear, multi‐degree‐of‐freedom model. Although not the main focus of this study, the linear system identification method is also combined with a non‐parametric identification technique, to generate a reduced‐order non‐linear mathematical model suitable for use in subsequent studies to predict, with good fidelity, the total response of the bridge under arbitrary dynamic environments. Results of this study yield measurements of the equivalent linear modal properties (frequencies, mode shapes and non‐proportional damping) as well as quantitative measures of the extent and nature of non‐linear interaction forces arising from strong ground shaking. It is shown that, for the particular subset of observations used in the identification procedure, the apparent non‐linearities in the system restoring forces are quite significant, and they contribute substantially to the improved fidelity of the model. Also shown is the potential of the identification technique under discussion to detect slight changes in the structure's influence coefficients, which may be indicators of damage and degradation in the structure being monitored. Difficulties associated with accurately estimating damping for lightly damped long‐span structures from their earthquake response are discussed. The technical issues raised in this paper indicate the need for added spatial resolution in sensor instrumentation to obtain identified mathematical models of structural systems with the broadest range of validity. Copyright © 2003 John Wiley & Sons, Ltd.     

The common focal point and common reflection surface methodologies: subsets or complements?

The common focal point (CFP) method and the common reflection surface (CRS) stack method are compared. The CRS method is a fast, highly automated procedure that provides high S/N ratio simulation of zero‐offset (ZO) images by combining, per image point, the reflection energy of an arc segment that is tangential to the reflector. It uses smooth parametrized two‐way stacking operators, based on a data‐driven triplet of attributes in 2D (eight parameters in 3D). As a spin‐off, the attributes can be used for several applications, such as the determination of the geometrical spreading factor, multiple prediction, and tomographic inversion into a smooth background velocity model. The CFP method aims at decomposing two‐way seismic reflection data into two full‐aperture one‐way propagation operators. By applying an iterative updating procedure in a half‐migrated domain, it provides non‐smooth focusing operators for prestack imaging using only the energy from one focal point at the reflector. The data‐driven operators inhibit all propagation effects of the overburden. The CFP method provides several spin‐offs, amongst which is the CFP matrix related to one focal point, which displays the reflection amplitudes as measured at the surface for each source–receiver pair. The CFP matrix can be used to determine the specular reflection source–receiver pairs and the Fresnel zone at the surface for reflection in one single focal point. Other spin‐offs are the prediction of internal multiples, the determination of reflectivity effects, velocity‐independent redatuming and tomographic inversion to obtain a velocity–depth model. The CFP method is less fast and less automated than the CRS method. From a pointwise comparison of features it is concluded that one method is not a subset of the other, but that both methods can be regarded as being to some extent complementary.     

Anisotropy signature in reverse‐time migration extended images

Reverse‐time migration can accurately image complex geologic structures in anisotropic media. Extended images at selected locations in the Earth, i.e., at common‐image‐point gathers, carry rich information to characterize the angle‐dependent illumination and to provide measurements for migration velocity analysis. However, characterizing the anisotropy influence on such extended images is a challenge. Extended common‐image‐point gathers are cheap to evaluate since they sample the image at sparse locations indicated by the presence of strong reflectors. Such gathers are also sensitive to velocity error that manifests itself through moveout as a function of space and time lags. Furthermore, inaccurate anisotropy leaves a distinctive signature in common‐image‐point gathers, which can be used to evaluate anisotropy through techniques similar to the ones used in conventional wavefield tomography. It specifically admits a V‐shaped residual moveout with the slope of the “V” flanks depending on the anisotropic parameter η regardless of the complexity of the velocity model. It reflects the fourth‐order nature of the anisotropy influence on moveout as it manifests itself in this distinct signature in extended images after handling the velocity properly in the imaging process. Synthetic and real data observations support this assertion.     

Diffraction‐limited imaging and beyond – the concept of super resolution‡

It is well‐known that experimental or numerical backpropagation of waves generated by a point‐source/‐scatterer will refocus on a diffraction‐limited spot with a size not smaller than half the wavelength. More recently, however, super‐resolution techniques have been introduced that apparently can overcome this fundamental physical limit. This paper provides a framework of understanding and analysing both diffraction‐limited imaging as well as super resolution. The resolution analysis presented in the first part of this paper unifies the different ideas of backpropagation and resolution known from the literature and provides an improved platform to understand the cause of diffraction‐limited imaging. It is demonstrated that the monochromatic resolution function consists of both causal and non‐causal parts even for ideal acquisition geometries. This is caused by the inherent properties of backpropagation not including the evanescent field contributions. As a consequence, only a diffraction‐limited focus can be obtained unless there are ideal acquisition surfaces and an infinite source‐frequency band. In the literature various attempts have been made to obtain images resolved beyond the classical diffraction limit, e.g., super resolution. The main direction of research has been to exploit the evanescent field components. However, this approach is not practical in case of seismic imaging in general since the evanescent waves are so weak – because of attenuation, they are masked by the noise. Alternatively, improvement of the image resolution of point like targets beyond the diffraction limit can apparently be obtained employing concepts adapted from conventional statistical multiple signal classification (MUSIC). The basis of this approach is the decomposition of the measurements into two orthogonal domains: signal and noise (nil) spaces. On comparison with Kirchhoff prestack migration this technique is showed to give superior results for monochromatic data. However, in case of random noise the super‐ resolution power breaks down when employing monochromatic data and a limited acquisition aperture. For such cases it also seems that when the source‐receiver lay out is less correlated, the use of a frequency band may restore the super‐resolution capability of the method.     

一种综合地学数据的矿产资源潜力制图方法

研究适应信息化时代特征的矿产资源潜力制图新技术、新方法对推动矿产资源评价理论与技术的发展具有重要的意义.笔者把GIS技术、图像分类算法和空间统计学理论进行有机集成,在空间统计学的空间结构分析技术和遥感图像纹理分类算法的基础上,提出了一种以综合地学数据（地质、地球物理、地球化学和遥感图像数据等）为基本数据源的矿产资源潜力自动制图方法.该方法的技术流程为：①数据准备,即对地球物理和地球化学勘探数据进行预处理,生成一个物化遥综合图像文件;②图像空间结构性分析和纹理图像生成,以综合地学图像为研究对象,用空间统计学的结构分析技术研究地学数据综合图像的空间结构性,生成纹理图像;③纹理图像多元分类,用实验变差函数纹理分类方法对研究区进行多元分类,生成分类专题图;④分类后处理,用叠置分析修正空间分类结果,生成区域矿产资源潜力分布图.     

Subsurface offset behaviour in velocity analysis with extended reflectivity images

Migration velocity analysis with the constant‐density acoustic wave equation can be accomplished by the focusing of extended migration images, obtained by introducing a subsurface shift in the imaging condition. A reflector in a wrong velocity model will show up as a curve in the extended image. In the correct model, it should collapse to a point. The usual approach to obtain a focused image involves a cost functional that penalizes energy in the extended image at non‐zero shift. Its minimization by a gradient‐based method should then produce the correct velocity model. Here, asymptotic analysis and numerical examples show that this method may be too sensitive to amplitude peaks at large shifts at the wrong depth and to artefacts. A more robust alternative is proposed that can be interpreted as a generalization of stack power and maximizes the energy at zero‐subsurface shift. A real‐data example is included.     

Vertical seismic profiling using a daisy‐chained deployment of fibre‐optic cables in four wells simultaneously – Case study at the Ketzin carbon dioxide storage site

The geological storage of carbon dioxide is considered as one of the measures to reduce greenhouse gas emissions and to mitigate global warming. Operators of storage sites are required to demonstrate safe containment and stable behaviour of the storage complex that is achieved by geophysical and geochemical monitoring, combined with reservoir simulations. For site characterization, as well as for imaging the carbon dioxide plume in the reservoir complex and detecting potential leakage, surface and surface‐borehole time‐lapse seismic monitoring surveys are the most widespread and established tools. At the Ketzin pilot site for carbon dioxide storage, permanently installed fibre‐optic cables, initially deployed for distributed temperature sensing, were used as seismic receiver arrays, demonstrating their ability to provide high‐resolution images of the storage formation. A vertical seismic profiling experiment was acquired using 23 source point locations and the daisy‐chained deployment of a fibre‐optic cable in four wells as a receiver array. The data were used to generate a 3D vertical seismic profiling cube, complementing the large‐scale 3D surface seismic measurements by a high resolution image of the reservoir close to the injection well. Stacking long vibro‐sweeps at each source location resulted in vertical seismic profiling shot gathers characterized by a signal‐to‐noise ratio similar to gathers acquired using geophones. A detailed data analysis shows strong dependency of data quality on borehole conditions with significantly better signal‐to‐noise ratio in regions with good coupling conditions.     

Migration for velocity and attenuation perturbations

Migration maps seismic data to reflectors in the Earth. Reflections are not only caused by small‐scale variations of the velocity and density but also of the quality factor that describes attenuation. We investigated scattering due to velocity and attenuation perturbations by computing the resolution function or point‐spread function in a homogeneous background model. The resolution function is the migration image of seismic reflection data generated by a point scatterer. We found that the resolution function mixes velocity and attenuation parameter perturbations to the extent that they cannot be reconstructed independently. This is true for a typical seismic setting with sources and receivers at the surface and a buried scatterer. As a result, it will be impossible to simultaneously invert for velocity and attenuation perturbations in the scattering approach, also known as the Born approximation. We proceeded to investigate other acquisition geometries that may resolve the ambiguity between velocity and attenuation perturbations. With sources and receivers on a circle around the scatterer, in 2D, the ambiguity disappears. It still shows up in a cross‐well setting, although the mixing of velocity and attenuation parameters is less severe than in the surface‐to‐surface case. We also consider illumination of the target by diving waves in a background model that has velocity increasing linearly with depth. The improvement in illumination is, however, still insufficient to remove the ambiguity.     

Increasing resolution of reverse‐time migration using time‐shift gathers

Reverse‐time migration has become an industry standard for imaging in complex geological areas. We present an approach for increasing its imaging resolution by employing time‐shift gathers. The method consists of two steps: (i) migrating seismic data with the extended imaging condition to get time‐shift gathers and (ii) accumulating the information from time‐shift gathers after they are transformed to zero‐lag time‐shift by a post‐stack depth migration on a finer grid. The final image is generated on a grid, which is denser than that of the original image, thus improving the resolution of the migrated images. Our method is based on the observation that non‐zero‐lag time‐shift images recorded on the regular computing grid contain the information of zero‐lag time‐shift image on a denser grid, and such information can be continued to zero‐lag time‐shift and refocused at the correct locations on the denser grid. The extra computational cost of the proposed method amounts to the computational cost of zero‐offset migration and is almost negligible compared with the cost of pre‐stack shot‐record reverse‐time migration. Numerical tests on synthetic models demonstrate that the method can effectively improve reverse‐time migration resolution. It can also be regarded as an approach to improve the efficiency of reverse‐time migration by performing wavefield extrapolation on a coarse grid and by generating the final image on the desired fine grid.     

Iterative resolution estimation in least‐squares Kirchhoff migration

We apply iterative resolution estimation to least‐squares Kirchhoff migration. Reviewing the theory of iterative optimization uncovers the common origin of different optimization methods. This allows us to reformulate the pseudo‐inverse, model resolution and data resolution operators in terms of effective iterative estimates. When applied to Kirchhoff migration, plots of the diagonal of the model resolution matrix reveal low illumination areas on seismic images and provide information about image uncertainties. Synthetic and real data examples illustrate the proposed technique and confirm the theoretical expectations.     

A Trade-Off Solution between Model Resolution and Covariance in Surface-Wave Inversion

Regularization is necessary for inversion of ill-posed geophysical problems. Appraisal of inverse models is essential for meaningful interpretation of these models. Because uncertainties are associated with regularization parameters, extra conditions are usually required to determine proper parameters for assessing inverse models. Commonly used techniques for assessment of a geophysical inverse model derived (generally iteratively) from a linear system are based on calculating the model resolution and the model covariance matrices. Because the model resolution and the model covariance matrices of the regularized solutions are controlled by the regularization parameter, direct assessment of inverse models using only the covariance matrix may provide incorrect results. To assess an inverted model, we use the concept of a trade-off between model resolution and covariance to find a proper regularization parameter with singular values calculated in the last iteration. We plot the singular values from large to small to form a singular value plot. A proper regularization parameter is normally the first singular value that approaches zero in the plot. With this regularization parameter, we obtain a trade-off solution between model resolution and model covariance in the vicinity of a regularized solution. The unit covariance matrix can then be used to calculate error bars of the inverse model at a resolution level determined by the regularization parameter. We demonstrate this approach with both synthetic and real surface-wave data.     

三峡地区上地壳结构的远震虚震源反射地震成像

远震虚震源反射成像方法利用远震初至波在台网之下地表与地下界面间形成的反射波(PPdp震相)波形资料进行台网地区地震反射结构研究.此方法先用台网各台站的平均初至波形求取震源信号,再用该震源信号与各道地震记录作反褶积从而取得反射剖面.本文介绍了远震虚震源反射成像的基本原理和实现步骤,并以三峡地区的观测资料为例,得到三峡库首区上地壳的反射地震剖面.成像剖面中解释出的四川盆地和秭归盆地的底界面位置和形态与地表地质观测和大地构造背景吻合.为验证虚震源成像的能力,本文使用弹性波正演模拟合成地震数据,经过处理实际资料一样的步骤获得虚震源成像结果.正演模拟表明,叠加多个远震的反射地震剖面可以有效地改善成像的信噪比和连续性;虚震源成像需要选择特定的震源频率范围,以减轻高频噪音以及低频造成的成像问题.在研究上地壳结构时,建议在不适合主动源采集和缺乏低频信号的地区尝试远震虚震源方法.     

Dipping-interface Mapping Using Mode-separated Rayleigh Waves

Multichannel analysis of surface waves (MASW) method is a non-invasive geophysical technique that uses the dispersive characteristic of Rayleigh waves to estimate a vertical shear (S)-wave velocity profile. A pseudo-2D S-wave velocity section is constructed by aligning 1D S-wave velocity profiles at the midpoint of each receiver spread that are contoured using a spatial interpolation scheme. The horizontal resolution of the section is therefore most influenced by the receiver spread length and the source interval. Based on the assumption that a dipping-layer model can be regarded as stepped flat layers, high-resolution linear Radon transform (LRT) has been proposed to image Rayleigh-wave dispersive energy and separate modes of Rayleigh waves from a multichannel record. With the mode-separation technique, therefore, a dispersion curve that possesses satisfactory accuracy can be calculated using a pair of consecutive traces within a mode-separated shot gather. In this study, using synthetic models containing a dipping layer with a slope of 5, 10, 15, 20, or 30 degrees and a real-world example, we assess the ability of using high-resolution LRT to image and separate fundamental-mode Rayleigh waves from raw surface-wave data and accuracy of dispersion curves generated by a pair of consecutive traces within a mode-separated shot gather. Results of synthetic and real-world examples demonstrate that a dipping interface with a slope smaller than 15 degrees can be successfully mapped by separated fundamental waves using high-resolution LRT.     

Geostatistical Borehole Image‐Based Mapping of Karst‐Carbonate Aquifer Pores

Quantification of the character and spatial distribution of porosity in carbonate aquifers is important as input into computer models used in the calculation of intrinsic permeability and for next‐generation, high‐resolution groundwater flow simulations. Digital, optical, borehole‐wall image data from three closely spaced boreholes in the karst‐carbonate Biscayne aquifer in southeastern Florida are used in geostatistical experiments to assess the capabilities of various methods to create realistic two‐dimensional models of vuggy megaporosity and matrix‐porosity distribution in the limestone that composes the aquifer. When the borehole image data alone were used as the model training image, multiple‐point geostatistics failed to detect the known spatial autocorrelation of vuggy megaporosity and matrix porosity among the three boreholes, which were only 10 m apart. Variogram analysis and subsequent Gaussian simulation produced results that showed a realistic conceptualization of horizontal continuity of strata dominated by vuggy megaporosity and matrix porosity among the three boreholes.     

Earthquake response of elastic SDF systems with non‐linear fluid viscous dampers

The steady‐forced and earthquake responses of SDF systems with a non‐linear fluid viscous damper (FVD) are investigated. The energy dissipation capacity of the FVD is characterized by the supplemental damping ratio ζsd and its non‐linearity by a parameter designated α. It is found that the structural response is most effectively investigated in terms of ζ_sd and α because (1) these two parameters are dimensionless and independent, and (2) the structural response varies linearly with the excitation intensity. Damper non‐linearity has essentially no influence on the peak response of systems in the velocity‐sensitive spectral region, but differences up to 14% were observed in the other spectral regions. The structural deformation is reduced by up to 25% when ζ_sd= 5%; and by up to 60% when ζ_sd= 30%. Non‐linear FVDs are advantageous because they achieve essentially the same reduction in system responses but with a significantly reduced damper force. For practical applications, a procedure is presented to estimate the design values of structural deformation and forces for a system with non‐linear FVD directly from the design spectrum. It is demonstrated that the earthquake‐induced force in a non‐linear FVD can be estimated from the damper force in a corresponding system with linear FVD, its peak deformation, and peak relative velocity; however, the relative velocity should not be approximated by the pseudo‐velocity as this approximation introduces a large error in the damper force. Finally, a procedure is presented to determine the non‐linear damper properties necessary to limit the structural deformation to some design value or the structural capacity for a given design spectrum. Copyright © 2002 John Wiley & Sons, Ltd.     

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.