频率-空间域有限差分法叠前深度偏移

为了处理横向强变速介质中的深度成像问题,本文提出一种基于共炮道集的优化系数的傍轴近似方程叠前深度偏移算子,并在基于反射系数估算的成像条件下,可实现叠前深度偏移成像.该算子具有方程阶数低且能对陡倾角成像的特征,并采用有限差分法波场延拓,能适应速度场的任意变化.当在频率-空间域进行计算时,相对于纯粹的时间-空间域有限差分算法有计算效率高、成像方便的优点.脉冲响应测试和对Marmousi模型进行的叠前深度偏移结果表明,该偏移方法在强横向变速情况下具有非常好的成像效果.     

基于波动方程的广义屏叠前深度偏移

地震波传播算子的计算效率和精度是制约三维叠前深度偏移的关键因素. 广义屏传播算子(GSP, Generalized Screen Propagator)是一种在双域中实现的广角单程波传播算子. 这一方法略去了在非均匀体之间发生的交混回响,但它可以正确处理包括聚焦、衍射、折射和干涉在内的各种多次前向散射现象. 通过背景速度下的相移和扰动速度下的陡倾角校正,广义屏算子能够适应地层速度的强烈横向变化. 这种算子可以直接应用于炮集叠前偏移,通过将广义屏算子作用于双平方根方程,还可以获得一种高效率、高精度的炮检距域叠前深度偏移方法,用于二维共炮检距道集和三维共方位角道集的深度域成像. 本文首先简述了炮检距域广义屏传播算子的理论,进而讨论了共照射角成像(CAI, Common Angle Imaging)条件,由此给出各个不同照射角(炮检距射线参数)下的成像结果,进而得到共照射角像集. 由于照射角和炮检距的对应关系,共照射角像集又为偏移速度分析和AVO(振幅随炮检距变化)分析等提供了有力工具.     

Kirchhoff叠前时间偏移角度道集

提出三维Kirchhoff叠前时间偏移角度域共像点道集的改进算法,克服传统角度求取算法局限,可计算相对倾斜地层法线入射角;与Kirchhoff直射线叠前时间偏移求角度算法相比,本文方法考虑射线弯曲效应,包含层速度,角度范围加大,更接近真实入射角;计算走时采取弯曲射线或者适应线性横向变速介质的非对称走时等算法,角度道集在大角度处得到拉平;采用相对保幅的权因子以及覆盖次数校正技术,有利于叠前AVA反演.模型测试结果表明：叠前时间偏移角度道集,相对CMP、CRP所转化角度道集,更准确反应AVA效应;实际三维数据测试表明本文方法可以提供品质优良的角度道集,适用于AVA分析、反演,提高叠前反演分辨率.     

任意复杂介质中主能量法地震波走时计算

积分法叠前深度偏移及层析成像的核心是复杂介质情况下的地震波走时计算. 复杂构造的高精度地震成像需要有稳健的走时计算方法。本文把 Nichols提出的用地震波主能量计算走时的方法由二维推广到三维,并推导出三维波动方程Helmholtz形式在球坐标系下用因式分解法求解的差分表达式.三维SEG/EAGE盐丘模型的理论走时计算和积分法叠前深度偏移的实践都验证了本文方法的正确性.     

逆时偏移与Kirchhoff偏移的抽道集对比研究

共成像点道集(CIG)可用于速度建模、偏移质量控制以及地下属性解释等。对于复杂碳酸盐岩储层,叠前AVO反演技术在储层识别、裂缝预测和流体检测方面的作用日益显著,叠前反演的精度很大程度上依赖于共成像点道集的AVO特性是否符合地下介质的真实地震响应。因此,叠前偏移不仅要实现反射点的准确归位,还必须得到振幅保真的共成像点道集,从而为AVO/AVA反演提供保幅的共成像点道集输入数据。本文在理论上对真振幅Kirchhoff叠前深度偏移和逆时偏移(RTM)抽道集技术的保幅性进行分析:真振幅Kirchhoff偏移抽道集通过改变加权函数实现振幅保持,仅适用于横向速度变化不大的情况;基于双程波动方程的逆时偏移采用互相关成像条件抽取共成像点道集,成像精确且无倾角限制,相对保幅性优于前者,适应任意复杂速度模型。模型和实例测试结果表明:在简单构造区域,真振幅Kirchhoff保幅叠前深度偏移与保幅逆时偏移抽取的共成像点道集都能起到良好的保幅效果;但在复杂构造区,基于逆时偏移抽取的共成像点道集,保留了全部波场的路径与振幅信息,其保幅性与成像精度优于Kirchhoff保幅叠前深度偏移。因此,针对探区的复杂程度差别及勘探精度的不同要求,应选择不同的抽道集方法,保证振幅精度的同时,兼顾生产效率。      

虚拟偏移距转换波叠前时间保幅偏移的影响因素

虚拟偏移距(POM)偏移方法是基于Kirchhoff积分的叠前时间偏移方法,这种方法具有改善共反射点模糊成像的优势,较少依赖速度模型,具有良好的振幅保持能力,计算成本相对较低,且在横向速度变化不太剧烈的情况下能够取得较好的成像效果,是转换波叠前时间偏移的一种重要方法.因POM方法是通过将地震波旅行时的双平方根(DSR)方程转化为以虚拟偏移距为变量的单平方根双曲线方程,这种方法的虚拟震源与虚拟检波器并非并置在一起,其传播路径符合Snell定律,可抽取真正的共转换散射点(CCSP)道集,该道集不需要倾角时差校正(DMO),形成CCSP道集的过程就等于叠前时间偏移的过程.随着AVO技术的发展,振幅的保真性在偏移过程中越来越重要.本文详细分析了初始速度、虚拟偏移距和偏移孔径对共转换散射点(CCSP)道集的影响.通过转换波POM保幅成像模型试算,结果表明,利用虚拟偏移距进行叠前时间偏移时,选择合适的虚拟偏移距间隔和偏移孔径至关重要.     

面炮成像、控制照明与AVA道集

基于波场延拓的叠前深度偏移是实现复杂构造地质体成像的最可靠方法,但存在着计算量大、对观测系统适应性差等缺点.面炮偏移是波动方程实现精确叠前成像的另一类方法,具有较高的计算效率,不存在偏移孔径问题,而且可以通过控制照明方法,解决平面波在目标区域的能量补偿问题.本文采用面炮成像技术进行叠前深度偏移,通过对面炮震源下行波场的质量控制和优选射线个数和范围,以达到最佳的成像效果.采用控制照明技术,较大地提高了目标地层的成像精度.与此同时,得到振幅随入射角变化(AVA)道集,有利于叠前振幅解释和储层岩性预测.数据实验表明面炮成像技术是一种快速有效的方法,其成像精度与单平方根算子的共炮点道集偏移和双平方根算子的共中心点道集偏移相当,但在计算速度上要快得多,而且易于并行计算.     

基于Chebyshev多项式的非对称走时Kirchhoff叠前时间偏移角道集求取

地震射线走时的求取方法是叠前时间偏移研究的核心问题之一,也是影响计算时间域角道集角度精确性的关键因素之一.本文基于Kirchhoff叠前时间偏移,应用第一类切比雪夫多项式,对弯曲射线对称走时加以改进,引进非对称项,优化后得到切比雪夫非对称走时方程,与高精度走时进行比较和误差分析,再将该走时求取方法应用于时间域角道集的求取中,得到地下较真实的入射角.通过模型计算和实际地震资料处理证明,此种非对称走时及其角道集的求取方法具有精度高、计算量少的优点.     

叠前逆时深度偏移中的激发时间成像条件

与其他偏移方法相比,逆时偏移基于精确的波动方程而不是对其近似,用时间外推来代替深度外推.因此,它具有良好的精度,不受地下构造倾角和介质横向速度变化的限制.激发时间成像条件的求取是叠前逆时偏移的难点之一,本文采用求解程函方程的方法得到地下各点的初至波走时,以此作为叠前逆时偏移的成像条件.基于任意矩形网格和局部平面波前近似的有限差分初至波走时计算方法精度较高并适用于强纵横向变速的复杂介质.试算结果表明,在复杂介质模型中利用叠前逆时深度偏移收到了很好的成像效果.     

Kirchhoff积分叠前时间偏移全方位角度道集生成方法与实现

方位角度域共成像点道集能够客观反映地下介质的速度、各向异性参数异常以及振幅随角度变化（AVA）和裂缝信息。传统Kirchhoff PSTM通常输出偏移距域共成像点道集,对于速度分析、各向异性分析、AVA分析、裂缝识别等均存在诸多不便。本文提出了基于走时梯度的Kirchhoff叠前时间偏移全方位角度集输出方法并提出工业上切实可行的实现方案。通过走时场梯度计算波场传播方向矢量,形成能够反映观测系统参数和波场传播情况的全方位角度域共成像点道集。为了在大规模地震数据Kirchhoff积分叠前时间偏移中输出全方位角度道集,本文给出基于输入道方式的偏移实现方法,采用逐条inline线进行线偏移成像,从而大大降低了全方位角度道集输出对计算机内存的压力,显著提高了Kirchhoff积分时间偏移输出全方位角度道集的可行性。三维盐丘模型测试和海上某区块三维实际资料试验证明了本文方法的正确性。      

基于局部余弦基小波束的观测系统沉降法叠前深度偏移

将局部余弦基小波束波场分解、传播与观测系统沉降法叠前深度偏移相结合,推导了源-检波器观测系统沉降法传播算子.本算法中,先对频率域的共点源和共点检波器道集做局部余弦小波束分解,然后分别沿共小波束源和共小波束检波器在深度方向延拓得到下一层波场.每个深度的波场,都等效于把源和检波器放在该层后所能接收到的地震记录,每点的像值由炮点和检波点重合时的零时刻波场值给出.通过二维SEG/EAGE盐丘模型和Marmousi模型的偏移成像结果验证该方法理论推导的正确性.另外,结果显示该方法继承了小波束域波场延拓在速度扰动较大情况下波传播及成像精度高的优点.     

三维共偏移距叠前地震数据反假频射线束形成偏移成像

对稀疏/非规则采样或者低信噪比数据,射线束提取困难并伴随有假频产生,对叠加剖面和道集造成严重干扰.为了提升射线束偏移在稀疏和低信噪比地震数据采集中的成像效果,本文提出基于三角滤波的局部倾斜叠加波束形成偏移假频压制方法.射线束偏移首先将地震数据划分为超道集,经过部分NMO后转化为以射线束中心定义的共偏移距数据,倾斜叠加和反假频操作均在局部共中心点坐标上实现.时间域倾斜叠加是对地震数据的时移累加操作,三角低通滤波同样可以在时间域完成,在对地震数据进行因果和反因果积分后,亦为地震数据的时移累加.因此,三角低通滤波与倾斜叠加可在时间域结合同时完成,避免了频域滤波的正反傅里叶变换.本文在反假频公式中加入权重系数,用以对反假频的程度进行控制,达到分辨率和噪声压制的最佳折衷.以某海上三维实际数据为例,文中展示了反假频射线束形成对偏移叠加剖面和共成像点偏移距道集中的噪声进行了有效压制.     

Reverse time migration with Gaussian beams using optimized ray tracing systems in transversely isotropic media

Prestack depth migration is a key technology for imaging complex reservoirs in media with strong lateral velocity variations. Prestack migrations are broadly separated into ray-based and wave-equation-based methods. Because of its efficiency and flexibility, ray-based Kirchhoff migration is popular in the industry. However, it has difficulties in dealing with the multi-arrivals, caustics and shadow zones. On the other hand, wave-equation-based methods produce images superior to that of the ray-based methods, but they are expensive numerically, especially methods based on two-way propagators in imaging large regions. Therefore, reverse time migration algorithms with Gaussian beams have recently been proposed to reduce the cost, as they combine the high computational efficiency of Gaussian beam migration and the high accuracy of reverse time migration. However, this method was based on the assumption that the subsurface is isotropic. As the acquired azimuth and maximum offsets increase, taking into account the influence of anisotropy on seismic migration is becoming more and more crucial. Using anisotropic ray tracing systems in terms of phase velocity, we proposed an anisotropic reverse time migration using the Gaussian beams method. We consider the influence of anisotropy on the propagation direction and calculate the amplitude of Gaussian beams with optimized correlation coefficients in dynamic ray tracing, which simplifies the calculations and improves the applicability of the proposed method. Numerical tests on anisotropic models demonstrate the efficiency and accuracy of the proposed method, which can be used to image complex structures in the presence of anisotropy in the overburden.     

Improving the gradient of the image‐domain objective function using quantitative migration for a more robust migration velocity analysis

Migration velocity analysis aims at determining the background velocity model. Classical artefacts, such as migration smiles, are observed on subsurface offset common image gathers, due to spatial and frequency data limitations. We analyse their impact on the differential semblance functional and on its gradient with respect to the model. In particular, the differential semblance functional is not necessarily minimum at the expected value. Tapers are classically applied on common image gathers to partly reduce these artefacts. Here, we first observe that the migrated image can be defined as the first gradient of an objective function formulated in the data‐domain. For an automatic and more robust formulation, we introduce a weight in the original data‐domain objective function. The weight is determined such that the Hessian resembles a Dirac function. In that way, we extend quantitative migration to the subsurface‐offset domain. This is an automatic way to compensate for illumination. We analyse the modified scheme on a very simple 2D case and on a more complex velocity model to show how migration velocity analysis becomes more robust.     

TI介质局部角度域高斯束叠前深度偏移成像

各向异性射线理论基础上的局部角度域叠前深度偏移方法能够为深度域构造成像与基于角道集的层析反演提供有力支撑,但是对于复杂地质构造而言,高斯度叠前深度偏移在不失高效、灵活等特点的情况下,具有明显的精度优势.为此,本文研究局部角度域理论框架下的高斯束叠前深度偏移方法.为提高算法效率与实用性,文中讨论了一种从经典弹性参数表征的各向异性介质运动学和动力学射线方程演变而来的由相速度表征的简便形式,并提出了一种比较经济的各向异性高斯束近似合成方案.结合地震波局部角度域成像原理,讨论一种适合高斯束偏移的角度参数计算方法.国际上通用的理论模型合成数据试验表明：相比局部角度域Kirchhoff叠前深度偏移成像方法,本文方法具有更高的成像精度与抗噪能力,既适用于复杂构造成像,也可为TI介质深度域偏移速度分析与模型建立提供高效的偏移引擎.     

Residual curvature migration velocity analysis for angle domain common imaging gathers

Pre-stack depth migration velocity analysis is one of the keys to influencing the imaging quality of pre-stack migration. In this paper we cover a residual curvature velocity analysis method on angle-domain common image gathers (ADCIGs) which can depict the relationship between incident angle and migration depth at imaging points and update the migration velocity. Differing from offset-domain common image gathers (ODCIGs), ADCIGs are not disturbed by the multi-path problem which contributes to imaging artifacts, thus influencing the velocity analysis. On the basis of horizontal layers, we derive the residual depth equation and also propose a velocity analysis workflow for velocity scanning. The tests to synthetic and field data prove the velocity analysis methods adopted in this paper are robust and valid.     

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.     

Poststack diffraction imaging using reverse‐time migration

We propose a method for imaging small‐scale diffraction objects in complex environments in which Kirchhoff‐based approaches may fail. The proposed method is based on a separation between the specular reflection and diffraction components of the total wavefield in the migrated surface angle domain. Reverse‐time migration was utilized to produce the common image gathers. This approach provides stable and robust results in cases of complex velocity models. The separation is based on the fact that, in surface angle common image gathers, reflection events are focused at positions that correspond to the apparent dip angle of the reflectors, whereas diffracted events are distributed over a wide range of angles. The high‐resolution radon‐based procedure is used to efficiently separate the reflection and diffraction wavefields. In this study, we consider poststack diffraction imaging. The advantages of working in the poststack domain are its numerical efficiency and the reduced computational time. The numerical results show that the proposed method is able to image diffraction objects in complex environments. The application of the method to a real seismic dataset illustrates the capability of the approach to extract diffractions.     

Wave-equation migration velocity analysis. I. Theory

We present a migration velocity analysis (MVA) method based on wavefield extrapolation. Similarly to conventional MVA, our method aims at iteratively improving the quality of the migrated image, as measured by the flatness of angle‐domain common‐image gathers (ADCIGs) over the aperture‐angle axis. However, instead of inverting the depth errors measured in ADCIGs using ray‐based tomography, we invert ‘image perturbations’ using a linearized wave‐equation operator. This operator relates perturbations of the migrated image to perturbations of the migration velocity. We use prestack Stolt residual migration to define the image perturbations that maximize the focusing and flatness of ADCIGs. Our linearized operator relates slowness perturbations to image perturbations, based on a truncation of the Born scattering series to the first‐order term. To avoid divergence of the inversion procedure when the velocity perturbations are too large for Born linearization of the wave equation, we do not invert directly the image perturbations obtained by residual migration, but a linearized version of the image perturbations. The linearized image perturbations are computed by a linearized prestack residual migration operator applied to the background image. We use numerical examples to illustrate how the backprojection of the linearized image perturbations, i.e. the gradient of our objective function, is well behaved, even in cases when backprojection of the original image perturbations would mislead the inversion and take it in the wrong direction. We demonstrate with simple synthetic examples that our method converges even when the initial velocity model is far from correct. In a companion paper, we illustrate the full potential of our method for estimating velocity anomalies under complex salt bodies.