共反射面元叠加的应用实践

共反射面元（Common Reflection Surface）叠加是一种不依赖于宏观速度模型的零炮检距剖面成像方法,实现共反射面元叠加依赖于3个波场属性参数的确定,它们分别是零偏移距射线的出射角α、Normal波和Normal Incident Point波出射到地表的波前曲率半径RN和RNIP. 在CRS叠加的理论基础上,本文阐述如何在实际数据上实现CRS叠加. 首先,通过简洁的一维相关性分析在常规叠加剖面上找到对应该共反射面元的一组初始波场属性参数(α,RN,RNIP),然后在对应的叠前数据上应用最优化算法对这组参数进行优化处理,相比初始属性参数,优化后的属性参数能够更好地聚集来自地下反射层的能量,最后应用优化后的属性参数实现最优CRS叠加.     

维波场延拓复杂表层模型校正方法及应用

如何正确地消除复杂地表对地震波场的影响，提高地下构造成像的质量一直是中国西部复杂地区地震勘探中存在的难题.本文在三维复杂表层速度模型层析反演\[1\]的基础上，研究了关于复杂地表的静校正问题，提出用三维波动方程在炮集上对地震波场进行正、反向延拓，消除复杂地表对波场的影响，实现三维复杂表层模型校正.理论和实际应用证明，该方法已超越常规静校正的含义，属时变校正方法.用本方法处理复杂地表问题，不但能消除表层对不同深度反射波产生的不同时差影响，提高叠加剖面质量，而且能使校正后的地震波场保持波动特征不发生畸变，可为建立正确的深层速度模型和波动方程叠前深度偏移奠定良好的基础.     

胜利探区基于最优孔径的共反射面元(CRS)叠加的成功应用(英文)

由于CRS叠加考虑了反射层的局部特征和第一菲涅耳带内的全部反射,从而更充分地利用了多次覆盖反射数据的信息。就目前的地震资料处理技术而言,它是最佳的零偏移距成像方式。本论文利用改进型的参数优化技术,得到高质量的CRS运动学参数剖面,并利用参数剖面计算出叠加孔径,实现了基于最优孔径的CRS叠加,使CRS参数的用途得到了充分利用。模型数据和实际资料的试算表明,基于最优孔径的CRS叠加的成像剖面与传统CRS叠加剖面相比,有着较高的信噪比和同相轴的连续性。     

关于共反射面元叠加方法在实际应用中的一些思考

共反射面元（Common Reflection Surface=CRS）叠加是一种特殊的零偏移距成像方法,实践中它具有独立于宏观速度模型和完全数据驱动实现的鲜明特色,CRS叠加理论认为在得到高质量的零偏移距剖面的同时,还可以得到三个有用的波场属性参数剖面反演宏观速度模型,CRS叠加剖面之后的叠后深度偏移质量将超过叠前深度偏移.虽然CRS叠加倡导的成像方式和承诺的上述理想境界带来了全新的启示,但是实践中这些特色同样带来了令人困扰的问题,为此我们提出了倾角分解CRS叠加方法解决这些问题.本文即是作者通过上述实践之后对CRS叠加方法形成的一些思考和总结.     

共反射面元叠加方法综述

在地下介质复杂的情况下,由于常规叠加方法的假设条件不满足,导致叠加效果不甚理想.共反射面元(CRS)叠加是一种完全由数据驱动、不依赖于宏观速度模型的地震成像技术,不仅可以得到高质量的零偏移距剖面,而且可以得到多个有用的波场属性参数剖面,被视为深层和复杂地区地震数据处理的重要发展方向.本文对共反射面元叠加技术的基本原理、...     

部分共反射面元叠加技术在海上数据中的应用

本文对共反射面元(CRS)叠加方法做改进,利用得到的波场参数来提高叠前地震资料的质量.利用CRS波场参数做部分CRS叠加,对菲涅尔带内的多个相邻CMP道集做倾角、曲率等校正后合并为一个道集即CRS超道集,可以补齐缺失地震道,实现叠前数据规则化,并提高信噪比.从而使得叠前道集中的同相轴尤其是来自深层的反射有更好的连续性,有利于识别和追踪.提高质量后的叠前道集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.     

一种基于地震干涉测量的VSP资料波场重构及成像应用

静校正和近地表速度建模是地震资料处理的重要组成部分.在近地表复杂区,静校正问题和近地表速度建模问题表现尤为突出.本文利用地震干涉测量在波场重构方面的优势,给出了一种同时避免静校正和近地表速度建模过程的方法,直接由重构的SWP波场来成像高陡构造.文中首先阐述了地震干涉测量的原理,给出了VSP波场向SWP波场重构的数学表达式;接着,采用几种不同的近地表模型,对比VSP波场向SWP波场重构的效果;最后,建立局部速度模型,直接利用重构的SWP波场进行偏移处理,完成高陡构造成像.模型试验结果表明该方法的可行性,有利于实现复杂地表区深层高陡构造的成像.     

利用CFP技术解决复杂近地表问题综述

复杂近地表条件会降低地震数据的质量,通常采用基于地表一致性的时移静校正消除其影响.但静校正与速度是密不可分的,而确定复杂近地表速度是非常困难的.基于CFP技术处理复杂近地表问题时避免了对速度的直接操作,使得静校正和速度的确定相互独立.首先根据叠前数据估算出波场的传播算子,然后依据等时原理在DTS模板中进行算子更新,再用这些更新的算子重建基准面和实现近地表单程时间成像.获得正确的算子振幅也是重建基准面的关键.     

黄土塬地区井控约束长波长静校正技术研究及应用

鄂南黄土塬区由于巨厚黄土层,经过一次静校正(层析静校正)、剩余静校正处理,仍然存在较严重的静校正问题,处理成果存在与地表高程相关的假构造,影响了地震资料的解释.因此,文中提出了一种井控约束长波长静校正技术,来解决剩余的静校正量.通过研究,分析了剩余长波长静校正问题和地表高程的相关性,根据这两者的相关性和井数据,拟合得到井控长波长静校正量函数,计算全区长波长静校正量.对该方法在黄土塬区进行应用,井控约束长波长静校正技术处理后,剖面上的假构造得到消除,较好的解决了黄土覆盖区严重的静校正问题.     

倾角分解共反射面元叠加方法

共反射面元（Common Reflection Surface）叠加是一种独立于宏观速度模型的零偏移距剖面成像方法,传统的CRS叠加实现是以数据驱动的方式对属性参数进行自动搜索并对其进行优化合成相应的CRS叠加算子,通过该算子进行叠加能够得到信噪比和连续性更高的零偏移距剖面.但是数据驱动的实现方式带来了不可避免的“倾角歧视现象”,它造成了弱有效反射信号损失和运动学特征失真的问题.本文提出的倾角分解CRS叠加方法成功解决了上述问题,使CRS叠加方法更具实用价值.     

Common reflection surface stack using dip decomposition for rugged surface topography

We present an extension of the Common Reflection Surface （CRS） stack that provides support for an arbitrary top surface topography. CRS stacking can be applied to the original prestack data without the need for any elevation statics. The CRS-stacked zero- offset section can be corrected （redatumed） to a given planar level by kinematic wave field attributes. The seismic processing results indicate that the CRS stacked section for rugged surface topography is better than the conventional stacked section for S/N ratio and better continuity of reflection events. Considering the multiple paths of zero-offset rays, the method deals with reflection information coming from different dips and performs the stack using the method of dip decomposition, which improves the kinematic and dynamic character of CRS stacked sections.     

Directional statics in common reflection surface stack for rugged surface topography

Seismic data acquired along rugged topographic surfaces present well‐known problems in seismic imaging. In conventional seismic data processing, datum statics are approximated by the surface consistence assumption, which states that all seismic rays travel vertically in the top layer. Hence, the datum static for each single trace is constant. In case this assumption does not apply, non‐constant statics are required. The common reflection surface (CRS) stack for rugged surface topography provides the capability to deal with this non‐vertical static issue. It handles the surface elevation as a coordinate component and treats the elevation variation in the sense of directional datuming. In this paper I apply the CRS stack method to a synthetic data set that simulates the acquisition along an irregular surface topography. After the CRS stack, by means of the wavefield attributes, a simple algorithm for redatuming the CRS stack section to an arbitrarily chosen planar surface is performed. The redatumed section simulates a stack section whose acquisition surface is the chosen planar surface.     

CRS-stack-based seismic imaging considering top-surface topography

In this case study we consider the seismic processing of a challenging land data set from the Arabian Peninsula. It suffers from rough top‐surface topography, a strongly varying weathering layer, and complex near‐surface geology. We aim at establishing a new seismic imaging workflow, well‐suited to these specific problems of land data processing. This workflow is based on the common‐reflection‐surface stack for topography, a generalized high‐density velocity analysis and stacking process. It is applied in a non‐interactive manner and provides an entire set of physically interpretable stacking parameters that include and complement the conventional stacking velocity. The implementation introduced combines two different approaches to topography handling to minimize the computational effort: after initial values of the stacking parameters are determined for a smoothly curved floating datum using conventional elevation statics, the final stack and also the related residual static correction are applied to the original prestack data, considering the true source and receiver elevations without the assumption of nearly vertical rays. Finally, we extrapolate all results to a chosen planar reference level using the stacking parameters. This redatuming procedure removes the influence of the rough measurement surface and provides standardized input for interpretation, tomographic velocity model determination, and post‐stack depth migration. The methodology of the residual static correction employed and the details of its application to this data example are discussed in a separate paper in this issue. In view of the complex near‐surface conditions, the imaging workflow that is conducted, i.e. stack – residual static correction – redatuming – tomographic inversion – prestack and post‐stack depth migration, leads to a significant improvement in resolution, signal‐to‐noise ratio and reflector continuity.     

CRS-stack-based residual static correction

In the case of onshore data sets, the acquired reflection events can be strongly impaired due to rough top‐surface topography and inhomogeneities in the uppermost low‐velocity layer, the so‐called weathering layer. Without accounting for these influences, the poor data quality will make data processing very difficult. Usually, the correction for the top‐surface topography is not perfect. The residuals from this correction and the influence of the weathering layers lead to small distortions along the reflection events. We integrated a residual static correction method into our data‐driven common‐reflection‐surface‐stack‐based imaging workflow to further eliminate such distortions. The moveout‐corrected traces and the stacked pilot trace are cross‐correlated to determine a final estimate of the surface‐consistent residual statics in an iterative manner. As the handling of top‐surface topography within the common‐reflection‐surface stack is discussed in a separate paper in this special issue, the corresponding residual static correction will be explained in more detail. For this purpose, the results obtained with a data set from the Arabian Peninsula will be presented.     

CRS strategies for solving severe static and imaging issues in seismic data from Saudi Arabia

Static shifts from near‐surface inhomogeneities very often represent the key problem in the processing of seismic data from arid regions. In this case study, the deep bottom fill of a wadi strongly degrades the image quality of a 2D seismic data set. The resulting static and dynamic problems are solved by both conventional and common‐reflection‐surface (CRS) processing. A straightforward approach derives conventional refraction statics from picked first breaks and then goes through several iterations of manual velocity picking and residual statics calculation. The surface‐induced static and dynamic inhomogeneities, however, are not completely solved by these conventional methods. In CRS processing, the local adaptation of the CRS stacking parameters results in very detailed dynamic corrections. They resolve the local inhomogeneities that were not detected by manual picking of stacking velocities and largely compensate for the surface‐induced deterioration in the stack. The subsequent CRS residual statics calculations benefit greatly from the large CRS stacking fold which increases the numbers of estimates for single static shifts. This improves the surface‐consistent averaging of static shifts and the convergence of the static solution which removes the remaining static shifts in the 2D seismic data. The large CRS stacking fold also increases the signal‐to‐noise ratio in the final CRS stack.     

Wavefield continuation datuming using a near surface model

When topography and low velocity zone differences vary greatly, conventional vertical static time shifts will cause wavefield distortion and influence wave equation seismic imaging for seismic data acquired on a complex near surface. In this paper, we propose an approach to datum correction that combines a joint tomography inversion with wavefield continuation to solve the static problem for seismic data on rugged acquisition topography. First, the near surface model is obtained by refracted wave tomography inversion. Second, the wavefield of sources and receivers are continued downward and upward to accomplish datum correction starting from a flat surface and locating the datum above topography. Based on the reciprocal theorem, Huygens＇ and Fresnel principles, the location of sources and receivers, and regarding the recorded data on the surface as a secondary emission, the sources and receivers are upward-continued to the datum above topography respectively. Thus, the datum correction using joint tomography inversion and wavefield continuation with the condition of a complex near surface is accomplished.     

复杂地表条件下高斯波束叠前深度偏移(英文)

在复杂地表条件的区域,地震数据的采集和处理是一项极大的挑战。虽然可以通过静校正来消除起伏地表的影响,然而当地表高程以及近地表速度剧烈变化时,简单的垂直时移对地震波场造成的畸变会严重降低偏移成像的质量。基于射线的偏移方法可以直接在起伏地表面进行波场的延拓成像,是解决上述问题的有效手段。本文针对复杂地表条件下的高斯波束叠前深度偏移进行研究,对倾斜叠加公式进行修改,使之包含地表高程以及速度的信息,通过直接在复杂地表面进行平面波的合成,得到了一种具有更高成像精度的改进方法。首先简单介绍常规高斯波束偏移的基本原理和计算流程,并以此为基础,给出复杂地表条件下高斯波束偏移原有的实现方法以及本文的改进方法,最后通过模型和实际资料的试算验证本文方法的有效性。     

Tomographic velocity inversion for ADCIGs in areas with a rugged surface

Pre-stack depth migration velocity analysis is one of the key techniques influencing image quality. As for areas with a rugged surface and complex subsurface, conventional prestack depth migration velocity analysis corrects the rugged surface to a known datum or designed surface velocity model on which to perform migration and update the velocity. We propose a rugged surface tomographic velocity inversion method based on angle-domain common image gathers by which the velocity field can be updated directly from the rugged surface without static correction for pre-stack data and improve inversion precision and efficiency. First, we introduce a method to acquire angle-domain common image gathers (ADCIGs) in rugged surface areas and then perform rugged surface tomographic velocity inversion. Tests with model and field data prove the method to be correct and effective.     

Common-reflection-surface (CRS) stack for common offset

We provide a data-driven macro-model-independent stacking technique that migrates 2D prestack multicoverage data into a common-offset (CO) section. We call this new process the CO common-reflection-surface (CRS) stack. It can be viewed as the generalization of the zero-offset (ZO) CRS stack, by which 2D multicoverage data are stacked into a well-simulated ZO section. The CO CRS stack formula can be tailored to stack P-P, S-S reflections as well as P-S or S-P converted reflections. We point out some potential applications of the five kinematic data-derived attributes obtained by the CO CRS stack for each stack value. These include (i) the determination of the geometrical spreading factor for reflections, which plays an important role in the construction of the true-amplitude CO section, and (ii) the separation of the diffractions from reflection events. As a by-product of formulating the CO CRS stack formula, we have also derived a formula to perform a data-driven prestack time migration.