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.     

最小二乘逆时偏移中黏弹性和各向异性的校正:以渤海湾地区地震数据为例

地下介质中存在黏弹性和各向异性,在应用最小二乘逆时偏移时,如果没有对黏弹性和各向异性的影响进行校正,在观测数据和模拟数据的匹配过程中就会发生错误,最终使得最小二乘逆时偏移无法得到准确的成像结果.因此,本论文首先对最小二乘逆时偏移的黏弹性和各向异性进行分别校正,然后对两种影响进行同时校正.在实际资料试算部分,通过对渤海湾数据进行测试,分别采用常规声波最小二乘逆时偏移、补偿黏弹性的最小二乘逆时偏移、校正各向异性的最小二乘逆时偏移及同时校正两种性质的最小二乘逆时偏移进行比较测试,证明了在同时校正了黏弹性和各向异性影响之后,最小二乘逆时偏移得到了更高质量的成像结果,具体表现在低频噪音压制、震源效应压制、深部能量改善、分辨率提升、目的层刻画等方面都明显优于其他三种最小二乘逆时偏移的成像结果,同时也证明了同时校正黏弹性和各向异性最小二乘逆时偏移方法的正确性及在实际资料处理中的适用性.     

扩展成像条件下的最小二乘逆时偏移

逆时偏移(RTM)是复杂介质条件下地震成像的重要手段.因受观测系统限制、上覆地层影响以及波场带宽有限等因素的影响,现行的常规RTM所采用的互相关成像条件通常对地下构造进行模糊成像.最小二乘逆时偏移(LSRTM)通过最小化线性Born近似正演数据和采集数据之间的波形差异,采用梯度类反演算法优化反射系数模型,获得的成像结果具有更高的分辨率和更可靠的振幅保真度.然而,基于波形拟合的LSRTM对背景速度模型的依赖性很强.误差太大的速度模型容易产生周波跳跃现象,导致LSRTM难以获得全局最优解.为了克服这一问题,本文基于扩展模型的思想,在线性Born近似下,推导得到RTM扩展成像条件.并基于最小二乘反演理论,提出扩展成像条件下的LSRTM方法.理论模型试算表明,本文方法不仅可以提供分辨率更高、振幅属性更为可靠的成像结果,而且能够在一定程度上消除速度误差对反演成像的影响.     

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.     

基于一阶速度-应力方程的多震源最小二乘逆时偏移

最小二乘逆时偏移(Least-Square Reverse Time Migration,LSRTM)相比于常规偏移具有更高的成像分辨率、振幅保幅性及均衡性等优势,是当前研究的热点之一.然而,目前LSRTM算法大多是基于二阶常密度标量声波方程建立的,忽略了密度变化对振幅的影响,因而基于振幅匹配策略的常规LSRTM很难在变密度介质下取得保真的成像结果.一阶速度-应力方程能够很好地处理变密度介质,但简单地将一阶速度-应力方程应用到LSRTM中缺乏理论基础.为此,本文从LSRTM的正问题入手,提出了基于交错网格的一阶速度-应力方程LSRTM理论方法.首先将一阶波动方程线性化,建立了一阶方程LSRTM的目标泛函,随后推导其伴随方程,并借助伴随状态法给出了迭代更新流程,最终建立了基于一阶速度-应力方程LSRTM的理论框架.进一步,通过在相位编码LSRTM中引入随机最优化思想,极大地减小了计算量、提高了计算效率.最后,通过模型试算验证了本算法的正确性和有效性.     

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.     

去均值归一化互相关最小二乘逆时偏移及其应用

最小二乘逆时偏移相对于常规逆时偏移具有更高的成像分辨率、振幅保幅性及均衡性等优势,在一定程度上可满足岩性油气藏勘探的需求,是目前研究的热点之一.然而由于实际地下介质的黏滞性和变密度,以及无法准确地估计震源子波等,基于振幅匹配的常规最小二乘逆时偏移算法很难在实际资料处理中取得好的效果.此外,实际数据常包含大量噪声,进一步限制了常规算法的应用.为此,本文通过修改目标泛函,提出了去均值归一化的互相关最小二乘逆时偏移算法,并给出了陆上资料的应用实例.研究表明,归一化策略减弱了算法对子波能量的苛求;互相关算法强调相位匹配,进一步弱化了子波的影响,提升了算法的稳定性和可靠性;去均值思想在处理低信噪比资料方面有较大优势.理论模型和陆上实际资料处理都验证了本算法的有效性和对复杂模型的适应性.     

基于一阶速度-应力方程的VTI介质最小二乘逆时偏移

地下地层普遍存在各向异性,忽略介质各向异性会导致速度估计不准确,成像精度下降.基于二阶声波方程的最小二乘逆时偏移忽略了介质各向异性及密度变化的影响,致使模拟地震数据与实际观测数据不匹配,影响收敛速度和反演成像质量.VTI介质一阶速度-应力方程能较好适应各向异性变密度情况,为此,本文首先从VTI介质一阶速度-应力方程出发,进行波动方程线性化;其次推导了相应的扰动方程和伴随方程,并通过伴随状态法得到梯度更新公式;最终形成基于一阶方程的LSRTM算法理论及实现流程.在实现算法的基础上,通过数值试算及成像结果对比,验证了本文算法在处理变密度和VTI介质时的有效性和优越性.偏移速度以及各向异性Thomsen参数误差的敏感性测试及误差收敛曲线对比结果进一步表明:速度及Thomsen参数对成像结果存在明显影响,其中速度敏感性最强,参数epsilon次之,参数delta的敏感性最弱.     

Least‐squares reverse‐time migration in a matrix‐based formulation

This paper describes least‐squares reverse‐time migration. The method provides the exact adjoint operator pair for solving the linear inverse problem, thereby enhancing the convergence of gradient‐based iterative linear inversion methods. In this formulation, modified source wavelets are used to correct the source signature imprint in the predicted data. Moreover, a roughness constraint is applied to stabilise the inversion and reduce high‐wavenumber artefacts. It is also shown that least‐squares migration implicitly applies a deconvolution imaging condition. Three numerical experiments illustrate that this method is able to produce seismic reflectivity images with higher resolution, more accurate amplitudes, and fewer artefacts than conventional reverse‐time migration. The methodology is currently feasible in 2‐D and can naturally be extended to 3‐D when computational resources become more powerful.     

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.     

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.     

地震数据的反射波动方程最小二乘偏移

基于反射波动方程,本文提出了一种估计地下反射率分布的地震数据最小二乘偏移方法.高频近似下,非齐次的一次反射波动方程的源项是由反射率与入射波场的时间一阶导数相互作用产生的.根据反射波动方程,利用线性最小二乘反演方法由地震反射数据重建出地下产生反射波的反射源,再结合波场正演计算出的地下入射波场,得到地下反射率分布的估计.在地下反射源的线性最小二乘反演重建中,我们采用迭代求解方法,并以地震波的检波器单向地下照明强度作为最小二乘优化问题中Hessian矩阵的近似.     

基于最小二乘逆时偏移的场声反射成像测井模拟?

近年来,声反射成像测井技术（ARILT）在井旁裂缝、孔洞性储层评价中成为研究热点。常规ARILT的探测深度一般在20m以内,且对复杂构造边界刻画能力不足。本文基于测井观测系统及采集参数,将最小二乘逆时偏移（LSRTM）地震成像技术引入ARILT中,以提高井旁区域有效成像范围和成像精度。本文在实现偏移算法及处理流程基础上,将算法用于典型模型和实际资料,重点分析不同频率、深度和偏移方法成像效果的差异。成像结果对比发现:①偏移算法影响ARILT成像精度,LSRTM具有较高分辨率,并能揭示构造体横向变化特征;②激发源频率也影响成像分辨率,提高频率会改善分辨率,但会降低探测深度;③在给定的测井观测参数下,LSRTM能有效探测23m范围内的井旁构造。      

各向异性介质Low-rank有限差分法纯qP波叠前平面波最小二乘逆时偏移

拟声波最小二乘逆时偏移是一种极具潜力的地震波成像工具,但该方法遭受各向异性拟声波近似的限制,TTI介质正演模拟不稳定、反偏移记录中遭受伪横波二次扰动及数值频散假象,另外拟声波最小二乘逆时偏移还面临计算效率低、收敛速度慢、对速度等模型参数依赖性高等问题.为了克服各向异性拟声波最小二乘逆时偏移的缺陷,在反演框架下,本文借助Low-rank有限差分算法首次提出并实现了TTI介质纯qP波线性正演模拟及纯qP波最小二乘逆时偏移;为了进一步提升反演成像效率,同时改善反演成像方法对模型参数误差的依赖性及对地震数据噪声的适应性,通过引入叠前平面波优化策略,发展了TTI介质纯qP波叠前平面波最小二乘逆时偏移成像方法.在编程实现方法的基础上,通过开展模型成像测试,展示了本方法的优势和潜力：一方面加快了反演成像效率,另一方面也提升了方法的抗噪性,同时还降低了方法对模型参数的依赖性.     

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.     

Assumptions and goals for least squares migration

Least squares migration uses the assumption that, if we have an operator that can create data from a reflectivity function, the optimal image will predict the actual recorded data with minimum square error. For this assumption to be true, it is also required that: (a) the prediction operator must be error-free, (b) model elements not seen by the operator should be constrained by other means and (c) data weakly predicted by the operator should make limited contribution to the solution. Under these conditions, least squares migration has the advantage over simple migration of being able to remove interference between different model components. Least squares migration does that by de-convolving or inverting the so-called Hessian operator. The Hessian is the cascade of forward modelling and migration; for each image point, it computes the effects of interference from other image points (point-spread function) given the actual recording geometry and the subsurface velocity model. Because the Hessian contains illumination information (along its diagonal), and information about the model cross-correlation produced by non-orthogonality of basis functions, its inversion produces illumination compensation and increases resolution. In addition, sampling deficiencies in the recording geometry map to the Hessian (both diagonal and non-diagonal elements), so least squares migration has the potential to remove sampling artefacts as well. These (illumination compensation, resolution and mitigating recording deficiencies) are the three main goals of least squares migration, although the first one can be achieved by cheaper techniques. To invert the Hessian, least squares migration relies on the residual errors during iterations. Iterative algorithms, like conjugate gradient and others, use the residuals to calculate the direction and amplitudes (gradient and step size) of the necessary corrections to the reflectivity function or model. Failure of conditions (a), (b) or (c) leads the inversion to calculate incorrect model updates, which translate to noise in the final image. In this paper, we will discuss these conditions for Kirchhoff migration and reverse time migration.     

基于Student′s t分布的不依赖子波最小二乘逆时偏移

最小二乘逆时偏移(Least-Squares Reverse Time Migration,LSRTM)与常规偏移相比具有更高的成像分辨率、振幅保真性及均衡性等优势,是当前研究的热点之一.震源子波的估计直接影响LSRTM结果的好坏,在实际情况下考虑到震源子波的空变特性,其估计十分困难.为了消除子波对LSRTM结果的影响,本文发展了基于卷积目标泛函的不依赖子波LSRTM算法.目标泛函由观测记录卷积模拟记录的参考道以及模拟记录卷积观测记录的参考道组成,由于观测子波和模拟子波在目标泛函的两项中同时存在,从而消除了子波的影响.此外,常用的基于L2范数拟合的LSRTM算法对噪声非常敏感,尤其是当地震数据中含有异常值时,常规LSRTM无法得到满意的结果.Student′s t分布相比L2范数具有更好的稳健性,本文将其推广到不依赖子波LSRTM中,提升了算法的稳健性,最后通过理论模型及实际资料试算验证了算法的有效性和对复杂模型的适应性.     

表面多次波最小二乘逆时偏移成像

使用相同的炮记录,多次波偏移能提供比反射波偏移更广的地下照明和更多的地下覆盖但是同时产生很多的串声噪声.相比传统逆时偏移,最小二乘逆时偏移反演的反射波成像结果具有更高的分辨率和更均衡的振幅.我们主要利用最小二乘逆时偏移压制多次波偏移产生的串声噪声.多次波最小二乘逆时偏移通常需要一定的迭代次数以较好地消除串声噪声.若提前将一阶多次波从所有阶数的多次波中过滤出来,使用相同的迭代次数,一阶多次波的最小二乘逆时偏移能够得到具有更高信噪比的成像剖面,而且能够提供与多次波最小二乘逆时偏移相似的有效地下结构成像.     

地震波干涉偏移及预条件正则化最小二乘偏移成像方法对比

地震波干涉偏移和偏移反演成像是近年来十分活跃的两个研究领域.干涉偏移提供了一个新的地震波数据成像工具,而偏移反演则提供了高逼近度地震成像.二者的共同目的是改善传统直接偏移方法的成像效果,展宽成像区域并提高成像的分辨率.本文研究干涉偏移方法和偏移反演方法对于地震成像效果的影响,探讨二者在提高成像分辨率上的异同.对于偏移反演,通过建立正则化模型,研究了预条件共轭梯度迭代正则化方法及改进措施,并通过绕射点模型数值模拟验证了该方法比直接偏移能够提高振幅的保真度和成像的分辨率.对于干涉偏移和偏移反演这两种方法,对层速度地震模型进行了数值模拟.结果表明干涉偏移和偏移反演成像方法比传统的偏移方法在成像效果上是更加有效的,因而对于实际的地震成像问题很有应用前景.     

Efficient amplitude encoding least‐squares reverse time migration using cosine basis

Least‐squares reverse time migration provides better imaging result than conventional reverse time migration by reducing the migration artefacts, improving the resolution of the image and balancing the amplitudes of the reflectors. However, it is computationally intensive. To reduce its computational cost, we propose an efficient amplitude encoding least‐squares reverse time migration scheme in the time domain. Although the encoding scheme is effective in increasing the computational efficiency, it also introduces the well‐known crosstalk noise in the gradient that degrades the quality of the imaging result. We analyse the cause of the crosstalk noise using an encoding correlation matrix and then develop two numerical schemes to suppress the crosstalk noise during the inversion process. We test the proposed method with synthetic and field data. Numerical examples show that the proposed scheme can provide better imaging result than reverse time migration, and it also generates images comparable with those from common shot least‐squares reverse time migration but with less computational cost.