Viscoacoustic least-squares reverse-time migration of different-order free-surface multiples

Multiples have longer propagation paths and smaller reflection angles than primaries for the same source–receiver combination, so they cover a larger illumination area. Therefore, multiples can be used to image shadow zones of primaries. Least-squares reverse-time migration of multiples can produce high-quality images with fewer artefacts, high resolution and balanced amplitudes. However, viscoelasticity exists widely in the earth, especially in the deep-sea environment, and the influence of Q attenuation on multiples is much more serious than primaries due to multiples have longer paths. To compensate for Q attenuation of multiples, Q-compensated least-squares reverse-time migration of different-order multiples is proposed by deriving viscoacoustic Born modelling operators, adjoint operators and demigration operators for different-order multiples. Based on inversion theory, this method compensates for Q attenuation along all the propagation paths of multiples. Examples of a simple four-layer model, a modified attenuating Sigsbee2B model and a field data set suggest that the proposed method can produce better imaging results than Q-compensated least-squares reverse-time migration of primaries and regular least-squares reverse-time migration of multiples.     

基于逆散射成像条件的最小二乘逆时偏移

最小二乘逆时偏移（LSRTM）相对于常规逆时偏移（RTM）具有分辨率更高、振幅更准确、噪音更少等优势,可以对复杂的地质构造进行有效的成像.这种迭代更新反演成像方法十分依赖目标函数的梯度质量和计算效率.当地质模型中存在强反射界面或者记录中存在折射波时,基于常规互相关成像条件（CCC）的最小二乘逆时偏移梯度会包含很强的低频噪音,从而使反演的收敛速度和成像质量降低.为此,本文在最小二乘逆时偏移的梯度中引进了逆散射成像条件来压制这种低频噪音,并以此提出基于逆散射成像条件（ISC）的最小二乘逆时偏移方法.数值模拟结果表明,两者计算耗时基本一致,但逆散射成像条件能高效压制梯度中的低频噪音,从而使反演过程中收敛加速,成像质量得到显著提高.     

Super-resolution least-squares prestack Kirchhoff depth migration using the <Emphasis Type="Italic">L</Emphasis><Subscript>0</Subscript>-norm

Least-squares migration (LSM) is applied to image subsurface structures and lithology by minimizing the objective function of the observed seismic and reverse-time migration residual data of various underground reflectivity models. LSM reduces the migration artifacts, enhances the spatial resolution of the migrated images, and yields a more accurate subsurface reflectivity distribution than that of standard migration. The introduction of regularization constraints effectively improves the stability of the least-squares offset. The commonly used regularization terms are based on the L₂-norm, which smooths the migration results, e.g., by smearing the reflectivities, while providing stability. However, in exploration geophysics, reflection structures based on velocity and density are generally observed to be discontinuous in depth, illustrating sparse reflectance. To obtain a sparse migration profile, we propose the super-resolution least-squares Kirchhoff prestack depth migration by solving the L₀-norm-constrained optimization problem. Additionally, we introduce a two-stage iterative soft and hard thresholding algorithm to retrieve the super-resolution reflectivity distribution. Further, the proposed algorithm is applied to complex synthetic data. Furthermore, the sensitivity of the proposed algorithm to noise and the dominant frequency of the source wavelet was evaluated. Finally, we conclude that the proposed method improves the spatial resolution and achieves impulse-like reflectivity distribution and can be applied to structural interpretations and complex subsurface imaging.     

Time-domain sparsity promoting least-squares reverse time migration with source estimation

Least-squares reverse-time migration is well known for its capability to generate artefact-free true-amplitude subsurface images through fitting observed data in the least-squares sense. However, when applied to realistic imaging problems, this approach is faced with issues related to overfitting and excessive computational costs induced by many wave-equation solves. The fact that the source function is unknown complicates this situation even further. Motivated by recent results in stochastic optimization and transform-domain sparsity promotion, we demonstrate that the computational costs of inversion can be reduced significantly while avoiding imaging artefacts and restoring amplitudes. While powerful, these new approaches do require accurate information on the source-time function, which is often lacking. Without this information, the imaging quality deteriorates rapidly. We address this issue by presenting an approach where the source-time function is estimated on the fly through a technique known as variable projection. Aside from introducing negligible computational overhead, the proposed method is shown to perform well on imaging problems with noisy data and problems that involve complex settings such as salt. In either case, the presented method produces high-resolution high-amplitude fidelity images including an estimate for the source-time function. In addition, due to its use of stochastic optimization, we arrive at these images at roughly one to two times the cost of conventional reverse-time migration involving all data.     

同时震源数据的加权结构增强最小二乘逆时偏移

同时震源（Simultaneous-source,SS）地震采集技术能有效地提高地震数据采集效率,但直接对SS混合数据偏移成像会在最后的成像剖面中引入很强的串扰噪声.将SS数据偏移成像看作一个反演问题,利用最小二乘（Least-squares,LS）求解是压制SS直接成像中串扰噪声的一种有效尝试.构造增强滤波（Structure-enhancing filter,SE）约束的最小二乘逆时偏移（LSRTM）方法可以有效地压制SS数据成像中的串扰噪声,但SE实质为低通滤波,会将成像中的陡倾角等细节信息平滑涂抹,降低成像分辨率.本文在利用SE对LSRTM约束的基础上,提出了基于加权构造增强约束的LSRTM方法（WSE-LSRTM）并应用于SS数据的反演成像中.该方法不仅能够有效地压制串扰噪声（cross-talk）、保留结构信息,而且可以保护成像中的陡倾角结构不被过度平滑而破坏.在对简单模型和复杂Marmousi模型的数值测试中,该方法都取得了良好的效果.     

Least squares reverse-time migration in the pseudodepth domain and reservoir exploration

Least squares reverse-time migration (LSRTM) is an inversion method that removes artificial images and preserves the amplitude of reflectivity sections. LSRTM has been used in reservoir exploration and processing of 4D seismic data. LSRTM is, however, a computationally costly and memory-intensive method. In this study, LSRTM in the pseudodepth domain was combined with the conjugate gradient method to reduce the computational cost while maintaining precision. The velocity field in the depth domain was transformed to the velocity field in the pseudodepth domain; thus, the total number of vertical sampling points was reduced and oversampling was avoided. Synthetic and field data were used to validate the proposed method. LSRTM in the pseudodepth domain in conjunction with the conjugate gradient method shows potential in treating field data.     

TTI介质qP波逆时偏移中伪横波噪声压制方法

在对地下复杂构造介质,特别是盐丘侧翼及岩下区域进行成像时,相对于传统的各向同性逆时偏移和VTI逆时偏移,具有倾斜对称轴的TTI逆时偏移成像效果最优.不仅反射同相轴更加的连续,而且能量得到了更好的聚焦.传统的各向异性介质全弹性波RTM的计算量大且计算效率低.由于目前仍以纵波勘探为主,因此TTI逆时偏移qP波波动方程的选取显得尤为重要.为了提高计算效率,采用将沿着对称轴方向的横波速度设为零的方法,简化得到qP波波动方程.然而,这样会引入一种严重影响成像效果的低速度、低振幅的qSV波人为干扰.本文建立了qP波方程的完全匹配层控制方程,而后借助于辅助波场采用一种高效的压制伪横波噪声传播的方法,通过模型测试验证了该方法的有效性.     

最小二乘傅立叶有限差分偏移

一般偏移算法是用反演算子通过解析方法求解.最小二乘偏移方法采用另一种思路,即采用数值方法,通过解一个线性离散反问题来索求解.这样我们试着寻找一个模型匹配地震数据并能表现出其某些特点来得到偏移图像.最小二乘法能减少偏移赝像,得到更精确的偏移效果.Kirchhoff算子在最小二乘偏移方法中应用较广,但需要较多的迭代次数,而且具有Kirchhoff偏移的缺点.本文把最小二乘方法运用到基于波长延拓的波动方程偏移方法中,为提高最小二乘偏移的效率,可采用效率较高的正传播算子和反传播算子.我们利用效率较高,能适应剧烈横向变速的傅立叶有限差分正传播和反传播算子来做叠后最小二乘偏移.数值实例表明,通过少数的共轭梯度法迭代,就能得到与真实模型差别很微小的偏移效果.对于傅式变换我们采用了数值软件FFTW,其变换速度比常规FFT算法一般要快六倍以上,进一步提高了效率.本文算法很容易在并行机上实现,这些特点在处理大型数据时大有裨益.     

Layer-stripping reverse-time migration1

We present a layer-stripping method of migration for irregularly layered media in which first-order velocity discontinuities separate regions of constant or smoothly varying velocity. We use the reverse-time method to migrate seismic data layer by layer, from the surface downwards. As part of the migration of a given layer, the bottom boundary of the layer is defined based on power in the migrated signal, and a seismic section is collected along it. This new section serves as the boundary condition for migration in the next layer. This procedure is repeated for each layer, with the final image formed from the individual layer images. Layer-stripping migration consists of three steps: (1) layer definition, (2) wavefield extrapolation and imaging, and (3) boundary determination. The migration scheme when used with reverse-time extrapolation is similar to datuming with an imaging condition. The reverse-time method uses an explicit fourth-order time, tenth-order space, finite-difference approximation to the scalar wave equation. The advantages of layer-stripping reverse-time migration are: (1) it preserves the benefits of the reverse-time method by handling strong velocity contrasts between layers and steeply dipping structures; (2) it reduces computer memory and saves computation time in high-velocity layers, and (3) it allows interpretational control of the image. Post-stack layer-stripping reverse-time migration is illustrated with a synthetic CMP data example. Prestack migration is illustrated with a synthetic data set and with a marine seismic reflection profile across the Santa Maria Basin and the Hosgri Fault in central California.     

An approximate least squares reflectivity inversion in the presence of density

Traditional least-squares reverse time migration (LSRTM) often aims to improve the quality of seismic imaging, such as removing the acquisition footprint, suppressing migration artifacts and enhancing resolution. In this paper, we find that the conventional reflectivity defined in the LSRTM is related to the normal-incident reflection coefficient and the background velocity. Compared with the defined reflectivity, our inverted result is relatively “true”. With reflected data, LSRTM is mainly sensitive to impedance perturbations. According to an approximate relationship between them, we reformulate the perturbation related system into a reflection-coefficient related one. Then, we seek the inverted image through linearized iteration. Moreover, with the assumption that the density varies more gradually than the migration velocity, only the knowledge of the latter is required, although the reflected waves are produced at impedance discontinuities. We test our method using the 2D Marmousi synthetic dataset.     

Imaging of elastic seismic data by least-squares reverse time migration with weighted L2-norm multiplicative and modified total-variation regularizations

Least-squares reverse time migration has the potential to yield high-quality images of the Earth. Compared with acoustic methods, elastic least-squares reverse time migration can effectively address mode conversion and provide velocity/impendence and density perturbation models. However, elastic least-squares reverse time migration is an ill-posed problem and suffers from a lack of uniqueness; further, its solution is not stable. We develop two new elastic least-squares reverse time migration methods based on weighted L2-norm multiplicative and modified total-variation regularizations. In the proposed methods, the original minimization problem is divided into two subproblems, and the images and auxiliary variables are updated alternatively. The method with modified total-variation regularization solves the two subproblems, a Tikhonov regularization problem and an L2-total-variation regularization problem, via an efficient inversion workflow and the split-Bregman iterative method, respectively. The method with multiplicative regularization updates the images and auxiliary variables by the efficient inversion workflow and nonlinear conjugate gradient methods in a nested fashion. We validate the proposed methods using synthetic and field seismic data. Numerical results demonstrate that the proposed methods with regularization improve the resolution and fidelity of the migration profiles and exhibit superior anti-noise ability compared with the conventional method. Moreover, the modified-total-variation-based method has marginally higher accuracy than the multiplicative-regularization-based method for noisy data. The computational cost of the proposed two methods is approximately the same as that of the conventional least-squares reverse time migration method because no additional forward computation is required in the inversion of auxiliary variables.     

Imaging of offset VSP data acquired in complex areas with modified reverse-time migration

A modified reverse-time migration algorithm for offset vertical seismic profiling data is proposed. This algorithm performs depth imaging of target areas in the borehole vicinity without taking into account the overburden. Originally recorded seismograms are used; reliable results can be obtained using only the velocity profile obtained along the well. The downgoing wavefield emitted from a surface source is approximated in the target area using the transmitted P-wave, recorded by the receivers deployed in the well. This is achieved through a reverse-time extrapolation of the direct transmitted P-wave into the target area after its separation in offset vertical seismic profiling seismograms generated using a finite-difference scheme for the solution of the scalar wave equation.
The proposed approach produces 'kinematically' reliable images from reflected PP- and PS-waves and, furthermore, can be applied as a salt proximity tool for salt body flank imaging based on the transmitted PS-waves. Our experiments on synthetic data demonstrate that the modified reverse-time migration provides reliable depth images based on offset vertical seismic profiling data even if only the velocity profile obtained along the borehole is used.     

Simultaneous joint migration inversion for high-resolution imaging/inversion of time-lapse seismic datasets

The current time-lapse practice is to exactly repeat well-sampled acquisition geometries to mitigate acquisition effects on the time-lapse differences. In order to relax the rigid requirements on acquisition effects, we propose simultaneous joint migration inversion as an effective time-lapse tool for reservoir monitoring, which combines a joint time-lapse data processing strategy with the joint migration inversion method. Joint migration inversion is a full-wavefield inversion method that explains the measured reflection data using a parameterization in terms of reflectivity and propagation velocity. Both the inversion process inside the imaging/inversion scheme and the extra illumination provided by including multiples in joint migration inversion makes the obtained velocity and reflectivity operator largely independent of the utilized acquisition geometry and, thereby, relaxes the strong requirement of non-repeatability during the monitoring. Because simultaneous joint migration inversion inverts for all datasets simultaneously and utilizes various constraints on the estimated reflectivities and velocity, the obtained time-lapse differences have much higher accuracy compared to inverting each dataset separately. It allows the baseline and monitor parameters to communicate with each other dynamically during inversion via a user-defined spatial weighting operator. In order to get more localized time-lapse velocity differences, we further extend the regular simultaneous joint migration inversion to a robust high-resolution simultaneous joint migration inversion process using the time-lapse reflectivity difference as an extra constraint for the velocity estimation during inversion. This constraint makes a link between the reflectivity- and the velocity difference by exploiting the relationship between them. We demonstrate the feasibility of the proposed method with a highly realistic synthetic model based on the Grane field offshore Norway and a time-lapse field dataset from the Troll Field.     

Extraction of amplitude-preserving angle gathers based on vector wavefield reverse-time migration

Angle-domain common-image gathers (ADCIGs) transformed from the shotdomain common-offset gathers are input to migration velocity analysis (MVA) and prestack inversion. ADCIGs are non-illusion prestack inversion gathers, and thus, accurate. We studied the extraction of elastic-wave ADCIGs based on amplitude-preserving elastic-wave reversetime migration for calculating the incidence angle of P-and S-waves at each image point and for different source locations. The P-and S-waves share the same incident angle, namely the incident angle of the source P-waves. The angle of incidence of the source P-wavefield was the difference between the source P-wave propagation angle and the reflector dips. The propagation angle of the source P-waves was obtained from the polarization vector of the decomposed P-waves. The reflectors’ normal direction angle was obtained using the complex wavenumber of the stacked reverse-time migration (RTM) images. The ADCIGs of P-and S-waves were obtained by rearranging the common-shot migration gathers based on the incident angle. We used a horizontally layered model, the graben medium model, and part of the Marmousi-II elastic model and field data to test the proposed algorithm. The results suggested that the proposed method can efficiently extract the P-and S-wave ADCIGs of the elastic-wave reverse-time migration, the P-and S-wave incident angle, and the angle-gather amplitude fidelity, and improve the MVA and prestack inversion.     

Resistivity inversion of cross-hole and borehole-to-surface EM data using axially symmetric models1

We describe a least-squares inversion approach to estimating the subsurface resistivity structure from cross-hole or borehole-to-surface electromagnetic data. It is assumed that the resistivity distribution is symmetric about the axis of a borehole and that vertical magnetic dipoles are located on the borehole axis. The receivers are placed either in another borehole or on the earth's surface. The inversion scheme uses the finite-element and smoothness-constrained least-squares methods. The computational effort required to obtain partial derivatives is reduced considerably by using the reciprocity principle. Numerical simulations show that the reconstructions are generally in good agreement with the true structures when the assumption of an axisymmetric earth structure holds. An example involving the breakdown of this assumption, which can be obtained by interchanging the source and receiver boreholes, suggests that the inversion result may also be useful for locating a general 3D anomaly although artifacts are present.     

Multisource least-squares reverse-time migration with structure-oriented filtering

The technology of simultaneous-source acquisition of seismic data excited by several sources can significantly improve the data collection efficiency. However, direct imaging of simultaneous-source data or blended data may introduce crosstalk noise and affect the imaging quality. To address this problem, we introduce a structure-oriented filtering operator as preconditioner into the multisource least-squares reverse-time migration (LSRTM). The structure-oriented filtering operator is a nonstationary filter along structural trends that suppresses crosstalk noise while maintaining structural information. The proposed method uses the conjugate-gradient method to minimize the mismatch between predicted and observed data, while effectively attenuating the interference noise caused by exciting several sources simultaneously. Numerical experiments using synthetic data suggest that the proposed method can suppress the crosstalk noise and produce highly accurate images.     

非零偏VSP弹性波叠前逆时深度偏移技术探讨

非零偏VSP地震资料是一种多分量资料,处理非零偏VSP资料,弹性波叠前逆时深度偏移技术无疑是最适合的处理技术.本文从二维各向同性介质的弹性波波动方程出发,研究了对非零偏VSP资料进行叠前逆时深度偏移的偏移算法,讨论了逆时传播过程中的边值问题和数值频散问题及其相应的解决方案;采用求解程函方程计算得到地下各点的地震波初至时间作为成像时间,实现了非零偏VSP资料的叠前逆时深度偏移.最后进行了模型试算和非零偏VSP地震资料的试处理,结果表明该方法不受地层倾角限制,较适用于高陡构造地区或介质横向速度变化较大地区的非零偏VSP地震资料处理.     

Implementation of Elastic Prestack Reverse-Time Migration Using an Efficient Finite-Difference Scheme

Elastic reverse-time migration (RTM) can reflect the underground elastic information more comprehensively than single-component Pwave migration. One of the most important requirements of elastic RTM is to solve wave equations. The imaging accuracy and efficiency of RTM depends heavily on the algorithms used for solving wave equations. In this paper, we propose an efficient staggered-grid finite-difference (SFD) scheme based on a sampling approximation method with adaptive variable difference operator lengths to implement elastic prestack RTM. Numerical dispersion analysis and wavefield extrapolation results show that the sampling approximation SFD scheme has greater accuracy than the conventional Taylor-series expansion SFD scheme. We also test the elastic RTM algorithm on theoretical models and a field data set, respectively. Experiments presented demonstrate that elastic RTM using the proposed SFD scheme can generate better images than that using the Taylor-series expansion SFD scheme, particularly for PS images. FurH. thermore, the application of adaptive variable difference operator lengths can effectively improve the computational efficiency of elastic RTM.     

基于平面波加速的VTI介质最小二乘逆时偏移

地震各向异性集中表现为速度各向异性,势必影响地震波运动学特征.传统声波逆时偏移(RTM)和最小二乘逆时偏移(LSRTM)没有考虑介质各向异性特征,导致反射波不能正确归位、同相轴出现扭曲及寻优速度慢或不收敛等,VTI介质逆时偏移(VTI-RTM)矫正了声波成像的不足,但仍存在低频干扰严重、中深部成像不佳、振幅保持差等缺陷.为此,本文首先实现了VTI介质最小二乘逆时偏移(VTI-LSRTM)方法,为了节省I/O及内存需求并提高效率,进一步引入平面波编码技术,提出了一种基于平面波加速的VTI介质最小二乘逆时偏移(VTI-PLSRTM)策略.在此基础上开展了简单模型及复杂Marmousi模型成像试验,并与标准逆时偏移剖面对比表明:本方法能够校正各向异性造成的相位畸变,且在迭代中自动压制串扰及低频噪声、补偿中深部能量,是一种兼具质量与效率的保幅成像策略;对速度误差的敏感性测试说明该方法需要相对正确的偏移速度及Thomsen参数模型.     

Acquisition design for direct reflectivity and velocity estimation from blended and irregularly sampled data

Blended acquisition along with efficient spatial sampling is capable of providing high-quality seismic data in a cost-effective and productive manner. While deblending and data reconstruction conventionally accompany this way of data acquisition, the recorded data can be processed directly to estimate subsurface properties. We establish a workflow to design survey parameters that account for the source blending as well as the spatial sampling of sources and detectors. The proposed method involves an iterative scheme to derive the survey design leading to optimum reflectivity and velocity estimation via joint migration inversion. In the workflow, we extend the standard implementation of joint migration inversion to cope with the data acquired in a blended fashion along with irregular detector and source geometries. This makes a direct estimation of reflectivity and velocity models feasible without the need of deblending or data reconstruction. During the iterations, the errors in reflectivity and velocity estimates are used to update the survey parameters by integrating a genetic algorithm and a convolutional neural network. Bio-inspired operators enable the simultaneous update of the blending and sampling operators. To relate the choice of survey parameters to the performance of joint migration inversion, we utilize a convolutional neural network. The applied network architecture discards suboptimal solutions among newly generated ones. Conversely, it carries optimal ones to the subsequent step, which improves the efficiency of the proposed approach. The resultant acquisition scenario yields a notable enhancement in both reflectivity and velocity estimation attributable to the choice of survey parameters.