基于结构中值滤波的CRP道集优化处理技术

共反射点道集中的噪声与剩余时差影响着偏移剖面的质量和叠前反演的精度.本文采用二次多项式拟合地震数据对地层倾向进行估计,并基于结构中值滤波方法对共反射点道集进行优化处理.在计算时窗内,对道集中每一个样点的二次多项式拟合系数进行精确扫描以确定样点所在同相轴方向并在同相轴方向进行中值滤波即结构中值滤波,滤波后道集信噪比得到提高同时保护了地层边缘特征.由于相关性在叠加剖面中要优于存在剩余时差的道集间,因此本文在叠加剖面上通过建立模型道来进行剩余时差校正即通过计算滑动时窗内待校正地震道和模型地震道间的互相关值,以最优化原则逐道估计剩余校正量,得到每个共反射点道集的剩余校正量模型,然后对剩余校正量模型在空间上做平滑处理,最后对共反射点道集进行时差校正.理论模型数据和实际数据的处理结果表明,该方法能够很好地解决道集中的信噪比和剩余时差问题,提高了共反射点道集和叠加剖面的整体质量.     

基于倾角-偏移距域道集的绕射波成像

地震绕射波是地下非连续性地质体的地震响应,绕射波成像对地下断层、尖灭和小尺度绕射体的识别具有重要的意义.在倾角域共成像点道集中,反射波同相轴表现为一条下凸曲线,能量主要集中在菲涅耳带内,绕射波能量则比较发散.由于倾角域菲涅耳带随偏移距变化而存在差异,因此本文提出一种在倾角-偏移距域道集中精确估计菲涅耳带的方法,在各偏移距的倾角域共成像点道集中实现菲涅耳带的精确切除,从而压制反射波.在倾角-偏移距域道集中还可以分别实现绕射波增强,绕射波同相轴相位校正,因此能量弱的绕射波可以清晰地成像.在倾角域共成像点道集中,反射波同相轴的最低点对应于菲涅耳带估计所用的倾角,因此本文提出一种在倾角域共成像点道集中直接自动拾取倾角场的方法.理论与实际资料试算验证了本文绕射波成像方法的有效性.     

基于偏移成像道集的剩余静校正方法

针对陆上地震资料处理的静校正问题,提出了一种基于偏移成像道集的剩余静校正方法.与传统的由动校正后的CMP道集中拾取剩余时差不同,本文基于偏移成像道集求取剩余时差,避免了复杂情况下同相轴归位不准确导致的剩余时差拾取误差.通过生成随炮点和检波点位置变化的偏移道集,实现了由偏移道集中直接拾取炮、检点的地表一致性剩余时差;该炮、检点偏移道集只在指定的局部时窗生成,并不增加大的计算量.二维和三维实际数据测试表明了该方法的有效性和实用性.     

三维VSP数据高效偏移成像的超道集方法

当前的三维VSP地震数据偏移成像实现都是在共炮点道集或共检波点道集中逐个道集循环进行的,计算效率相对较低.根据三维VSP观测系统中炮点和检波点布置的特殊性和地震波场满足线性叠加的特性,本文提出了一种三维VSP数据的高效偏移成像方法,即首先通过对三维VSP共接收点道集进行地震数据的广义合成得到一种超道集,然后在共接收点道集的波场深度外推过程中逐步应用多震源波场对超道集进行偏移成像,即利用一次波场深度外推循环完成对所有共检波点道集数据的偏移成像.通过三维VSP模型数据与实际地震数据的偏移成像试验验证了这种高效的超道集偏移成像方法可取得与常规共检波点道集相当的偏移成像效果,还具有极高的计算效率,其计算量与单个共检波点道集的偏移成像计算量相当.     

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.     

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。      

基于共散射道集的叠前时间偏移/反偏移提高叠前数据质量

为了提高叠前数据质量,将叠前时间偏移/反偏移与共散射点道集相结合,提出了一种新的时间偏移/反偏移方法.利用改进的CRS参数建立精确的速度模型,提高偏移成像质量.将振幅映射到共偏移距顶点来生成共散射点道集,将偏移和中点上的多参数叠加,通过叠加数据,实现了叠前数据增强,道集的数量远高于传统叠前时间偏移的叠加数量.利用基于中点位移、半偏移距和偏移速度的算子进行反偏移处理,能量重新分配回时间域中的每个绕射同相轴,压制噪声,地震资料信噪比和成像精度均得到了提高.提高质量后的叠前数据可用于后续的速度分析、叠加、偏移等常规处理中,效果好于原始CMP道集.模型和实际数据的计算结果均验证了该方法的正确性和有效性,该方法在低信噪比资料的处理中将会有广阔的应用前景.     

逆时偏移中用Poynting矢量高效地提取角道集

逆时偏移在提高复杂介质的成像质量方面表现出了优越的性能,但逆时偏移对速度精度的要求比较高.共成像点道集是一种非常重要的叠前深度偏移输出,它除了能为深度偏移处理提供速度信息外,还能够提供振幅和相位等信息,为后续的属性解释提供依据.本文提出一种在逆时偏移成像过程中提取角度域共成像点道集的方法,该方法采用矢量波动方程进行波场传播,并用能流密度矢量(Poynting vector)计算反射角,最后应用互相关成像条件输出角度域共成像点道集.该方法简单易于实现,且几乎不需要额外的计算量和存储量,非常适合于进行逆时偏移速度分析,同时提出的角道集也能用于进行AVA等分析.最后通过模型算例和实际数据检验了方法的有效性和优越性.     

共反射角叠前偏移成像研究及应用

共偏移距道集已被广泛地应用于地震速度建模及振幅随偏移距变化(AVO)的研究中,但复杂构造及射线多路径产生的共偏移距道集不保幅性等一系列缺陷给AVO研究带来很大的困难.共反射角道集包含有能反映地下速度和岩性变化的信息,更有利于速度模型优化、地震振幅属性分析及地下岩性和断裂的研究.本文通过研究共反射角深度偏移方法和理论,完善了基于目标的共反射角深度偏移技术,提出了获得相对保幅共反射角道集方法.该方法克服了共偏移距域道集在复杂介质中遇到的困难,更能有效地反映波场和地质结构方面的信息.通过理论模型数据进行了试算,并采用实际地震数据对此方法进行了验证,在陡倾角成像方面取得较好效果.     

叠前偏移共成像点道集的对比分析

本文首先对各种不同类型的共成像点道集进行了概述,然后从定义、主要用途、提取方法、剩余曲率关系以及共成像点道集与速度误差间的联系等方面进行具体的比较分析,给出了定量和定性结果,从而对各种共成像点道集的特征有了更深入的认识,可作为进行有效偏移速度分析时的参考依据.最后又基于模型分别提取了偏移距域共成像点道集(ODCIGs)...     

Migration to multiple offset and velocity analysis1

The stacking velocity best characterizes the normal moveout curves in a common-mid-point gather, while the migration velocity characterizes the diffraction curves in a zero-offset section as well as in a common-midpoint gather. For horizontally layered media, the two velocity types coincide due to the conformance of the normal and the image ray. In the case of dipping subsurface structures, stacking velocities depend on the dip of the reflector and relate to normal rays, but with a dip-dependent lateral smear of the reflection point. After dip-moveout correction, the stacking velocities are reduced while the reflection-point smear vanishes, focusing the rays on the common reflection points. For homogeneous media the dip-moveout correction is independent of the actual velocity and can be applied as a dip-moveout correction to multiple offset before velocity analysis. Migration to multiple offset is a prestack, time-migration technique, which presents data sets which mimic high-fold, bin-centre adjusted, common-midpoint gathers. This method is independent of velocity and can migrate any 2D or 3D data set with arbitrary acquisition geometry. The gathers generated can be analysed for normal-moveout velocities using traditional methods such as the interpretation of multivelocity-function stacks. These stacks, however, are equivalent to multi-velocity-function time migrations and the derived velocities are migration velocities.     

Pre-stack Kirchhoff depth migration local space-shift imaging condition: synthetic and data examples

Extracting accurate common image angle gathers from pre-stack depth migrations is important in the generation of any incremental uplift to the amplitude versus angle attributes and seismic inversions that can lead to significant impacts in exploration and development success. The commonly used Kirchhoff migration outputs surface common offset image gathers that require a transformation to angle gathers for amplitude versus angle analysis. The accuracy of this transformation is one of the factors that determine the robustness of the amplitude versus angle measurements. Here, we investigate the possibility of implementing an extended imaging condition, focusing on the space-lag condition, for generating subsurface reflection angle gathers within a Kirchhoff migration. The objective is to determine if exploiting the spatial local shift imaging condition can provide any increase in angle gather fidelity relative to the common offset image gathers. The same restrictions with a ray-based approach will apply using the extended imaging condition as both the offset and extended imaging condition method use travel times derived from solutions to an Eikonal equation. The aims are to offer an alternative ray-based method to generate subsurface angle gathers and to understand the impact on the amplitude versus angle response. To this end, the implementation of the space-shift imaging condition is discussed and results of three different data sets are presented. A layered three-dimensional model and a complex two-dimensional model are used to assess the space shift image gathers output from such a migration scheme and to evaluate the seismic attributes relative to the traditional surface offset common image gathers. The synthetic results show that the extended imaging condition clearly provides an uplift in the measured amplitude versus angle over the surface offset migration. The noise profile post-migration is also improved for the space-lag migration due to the double summation inside the migration. Finally, we show an example of a space-lag gather from deep marine data and compare the resultant angle gathers with those generated from an offset migration and a time-shift imaging condition Kirchhoff migration. The comparison of the real data with a well log shows that the space-lag result is a better match to the well compared to the time-lag extended imaging condition and the common offset Kirchhoff migration. Overall, the results from the synthetics and real data show that a Kirchhoff migration with an extended imaging condition is capable of generating subsurface angle gathers with an incremental improvement in amplitude versus angle fidelity and lower noise but comes at a higher computational cost.     

Common image gather conditioning using cycle generative adversarial networks

Seismically derived amplitude-versus-angle attributes along with well constraints are the base inputs into inverting seismic into subsurface properties. Conditioning the common image gathers is a common workflow in quantitative inversion and leads to a more accurate inversion product due to the removal of post-migration artefacts. Here, we apply a neural network to condition the post-migration gathers. The network is a cycle generative adversarial network, CycleGAN, which was designed for image-to-image translation. This can be considered the same problem as translating an artefact rich seismic gather to an artefact free seismic gather. To assess the feasibility of applying the network to pre-stack conditioning, synthetic data sets were generated to train different networks for different tasks. The networks were trained to remove white noise, residual de-multiples, gather flattening and a combination of the above for conditioning. The results show that a trained network was able remove white noise providing a more robust amplitude-versus-offset calculation. Another network trained using synthetic gathers with and without multiples assisted in multiple removal. However, instability around primary preservation has been observed so the network works better as a residual de-multiple method. For gather conditioning, a network was trained with the unpaired artefact-rich and artefact-free training data where the artefacts included complex moveout, noise and multiples. When applied to the test data sets, the networks cleaned the artefact-rich test data and translated complex moveout into flat gathers whilst preserving the amplitude response. Finally, two networks are applied to real data where a gather based on the well logs is used to quantify the match between the conditioned gathers and the raw gathers. The first network used synthetic data to train the network and, when applied to real data, provided a better tie with the well. The second network was trained with synthetic gathers whose properties were constrained by real seismic gathers from near the well. As anticipated, the network trained on the representative training data outperforms the network trained using the unconstrained data. However, the ability of the first network to condition the gather indicates that a sweep of networks can be trained without the need for real data and applied in a manner analogous to the way parameters are adjusted in traditional geophysical methods. The results show that the different neural networks can offer an alternative or augmentation to the existing geophysical workflow for conditioning pre-stack seismic gathers.     

Investigating a time‐shift extended imaging condition in a Kirchhoff pre‐stack depth migration algorithm

Extracting true amplitude versus angle common image gathers is one of the key objectives in seismic processing and imaging. This is achievable to different degrees using different migration techniques (e.g., Kirchhoff, wavefield extrapolation, and reverse time migration techniques) and is a common tool in exploration, but the costs can vary depending on the selected migration algorithm and the desired accuracy. Here, we investigate the possibility of combining the local‐shift imaging condition, specifically the time‐shift extended imaging condition, for angle gathers with a Kirchhoff migration. The aims are not to replace the more accurate full‐wavefield migration but to offer a cheaper alternative where ray‐based methods are applicable and to use Kirchhoff time‐lag common image gathers to help bridge the gap between the traditional offset common image gathers and reverse time migration angle gathers; finally, given the higher level of summation inside the extended imaging migration, we wish to understand the impact on the amplitude versus angle response. The implementation of the time‐shift imaging condition along with the computational cost is discussed, and results of four different datasets are presented. The four example datasets, two synthetic, one land acquisition, and a marine dataset, have been migrated using a Kirchhoff offset method, a Kirchhoff time‐shift method, and, for comparison, a reverse time migration algorithm. The results show that the time‐shift imaging condition at zero time lag is equivalent to the full offset stack as expected. The output gathers are cleaner and more consistent in the time‐lag‐derived angle gathers, but the conversion from time lag to angle can be considered a post‐processing step. The main difference arises in the amplitude versus offset/angle distribution where the responses are different and dramatically so for the land data. The results from the synthetics and real data show that a Kirchhoff migration with an extended imaging condition is capable of generating subsurface angle gathers. The same disadvantages with a ray‐based approach will apply using the extended imaging condition relative to a wave equation angle gather solution. Nevertheless, using this approach allows one to explore the relationship between the velocity model and focusing of the reflected energy, to use the Radon transformation to remove noise and multiples, and to generate consistent products from a ray‐based migration and a full‐wave equation migration, which can then be interchanged depending on the process under study.     

角度域剩余深度对剩余速度的敏感性分析

本文针对地震勘探深度域偏移速度建模研究,利用角度域共成像点道集(ADCIGS)建立了以剩余速度为自变量,剩余深度为目标函数的关系式,及目标函数的梯度公式.利用导出的两个公式分别对剩余深度与剩余速度的关系进行了定量分析.通过理论分析和模型试算证明初始速度模型的误差具有方向敏感性,即正误差较负误差对速度建模迭代收敛更敏感.利用此结论进行深度域速度建模既可以提高计算效率也可以提高建模精度.     

基于保真振幅单程波方程的叠前AVP成像方法

基于共聚焦点技术的叠前AVP（振幅随射线参数变化）分析与常规叠后反演方法相比优势明显,但传统通过褶积和互相关运算来实现的方法依赖于聚焦算子,而在复杂构造区走时计算困难且子波难以精确提取,从而导致了聚焦算子不准确,而且褶积和互相关运算会影响信噪比和分辨率,基于此,本文提出了基于保真振幅单程波延拓算法的叠前AVP成像方法.该方法利用保真振幅傅里叶有限差分延拓算法实现两步聚焦,分别生成共聚焦点道集和网格点道集,既充分利用了保真振幅延拓算法在振幅保持方面的优势,也可以发挥傅里叶有限差分方法对复杂构造区横向变速适应性强的优势,而且两步聚焦过程都不需要聚焦算子,从而解决了传统方法中走时计算和子波提取的问题.模型试算结果表明了方法的正确性和可行性,而针对实际地震资料的试处理结果与传统方法相比具有更高的信噪比和分辨率,表明了方法的有效性.该方法为复杂构造区油气检测提供了一种新的地球物理依据.     

Image enhancement by multi‐parameter characterization of common image gathers

We present an innovative approach for seismic image enhancement using multi‐parameter angle‐domain characterization of common image gathers. A special subsurface angle‐domain imaging system is used to generate the multi‐parameter common image gathers in a summation‐free image space. The imaged data associated with each common image gathers depth point contain direction‐dependent opening‐angle image contributions from all the available incident and scattered wave‐pairs at this point. Each direction‐dependent opening‐angle data can be differently weighted according to its coherency measure. Once the optimal migration velocity is used, it is assumed that in the actual specular direction, the coherency measure (semblance) along reflection events, from all available opening angles and opening azimuths, is larger than that along non‐specular directions. The computed direction‐dependent semblance attribute is designed to operate as an imaging filter which enhances specular migration contributions and suppresses all others in the final migration image. The ability to analyse the structural properties of the image points by the multi‐parameter common image gather allows us to better handle cases of complicated wave propagation and to improve the image quality at poorly illuminated regions or near complex structures. The proposed method and some of its practical benefits are demonstrated through detailed analysis of synthetic and real data examples.     

用于AVO分析的振幅保真平面波叠前时间偏移

To support amplitude variation with offset （AVO） analysis in complex structure areas, we introduce an amplitude-preserving plane-wave prestack time migration approach based on the double-square-root wave equation in media with little lateral velocity variation. In its implementation, a data mapping algorithm is used to obtain offset-plane-wave data sets from the common-midpoint gathers followed by a non-recursive phase-shift solution with amplitude correction to generate common-image gathers in offset-ray-parameter domain and a structural image. Theoretical model tests and a real data example show that our prestack time migration approach is helpful for AVO analysis in complex geological environments.     

振幅保真的单程波方程偏移理论

本报告综述了近年来发展起来的真振幅单程波方程偏移理论,对各种基于单程波方程的偏移振幅作出了系统的分析介绍.为了得到正确的偏移振幅,叠后偏移之前必须进行球面扩散校正.但是,作为叠后相位移偏移算法的推广,Dubrulle氏的共炮检距偏移除了零炮检距和平层两种特例外,它不能给出正确的偏移振幅.通过分析,我们发现传统的单程波单炮偏移不是保振幅算法.利用真振幅单程波方程分解和校正地表的初值条件,我们可以将常规偏移方法改造为真振幅算法并且证明在高频渐近的意义下,新方法的偏移振幅等价于Kirchhoff反演的结果.进一步研究发现可以利用单平方根算子和双平方根算子输出真振幅共反射角剖面.我们的分析指出,这时正确的成像条件为乘积pUp*D.与真振幅共炮偏移所需的商型成像条件pU/pD相比,共反射角偏移的计算稳定性大为改善并且在实际地震资料处理中有重要的应用.