Stereotomography: a semi-automatic approach for velocity macromodel estimation

Most methods for velocity macromodel estimation require considerable operator input, mainly concerning the regularization and the picking of events in the data set or in the migrated images. For both these aspects, slope tomography methods offer interesting solutions. They consider locally coherent events characterized by their slopes in the data cube. Picking is then much easier and consequently denser than in standard traveltime tomography. Stereotomography is the latest slope tomography method. In recent years it has been improved significantly, both from an algorithmic point of view and in terms of practical use. Robust and fast procedures are now available for 2D stereotomographic picking and optimization. Concerning the picking, we propose simple criteria for the selection of relevant data among the automatically picked events. This enables an accurate smooth velocity macromodel to be estimated quite rapidly and with very limited operator intervention. We demonstrate the method using a 2D line extracted from the Oseberg NH8906 data set.     

地震立体层析成像的实现方法及效果分析

立体层析成像是一种新的地震反射波层析成像方法, 能为叠前深度偏移提供较为精确的宏观速度模型。本文研究了立体层析成像的实现方法, 包括斜率与走时数据的拾取、离散速度模型构建和初始化、射线参数的确定、斜率和走时及射线计算以及反演问题解法等, 建立立体层析成像的算法流程。并通过对Marmousi模型试验, 对立体层析成像运行所需的主要参数, 如初始速度模型、拾取数据量、离散网格尺寸、速度平滑权重等进行测试和分析, 总结这些不同参数对立体层析反演结果的影响规律, 用以指导生产实践。     

利用全方位P波属性进行裂缝检测的地震方法

胜利油田存在着一种特殊的裂隙性油气藏,即泥岩裂隙油气藏。由于该类裂隙储层的孔隙度很小,岩石物性参数变化不灵敏,并表现出很强的各向异性,因此,其勘探难度很大。到目前为止,国内外还没有一套成熟的地质、物探、测井及钻井等资料综合分析的裂隙方位、分布、密度的识别方法。本文在研究国外裂缝检测方法的基础上,提出了波阻抗随方位变化(IPVA)的新方法,结合罗家地区的泥岩裂隙地震地质特征,研究了利用多方位 P 波资料检测定向垂直裂缝的地震采集、处理和识别方法,对不同共中心点 CMP 位置的全方位 P 波资料在速度随方位变化(VVA)及振幅随方位角变化(RVA)研究的基础上,进行波阻抗随方位变化(IPVA)的研究,用于识别裂缝的分布、走向及密度。经罗家地区实际资料的应用,见到了初步的效果,证明该方法是潜力较大的高角度裂隙的定量检测方法。     

Improving reservoir thickness prediction using seismic attributes and attributes fusion

Usage of any single attribute would introduce unacceptable uncertainty due to limited reservoir thickness and distribution, and strong lateral variations in lithological traps. In this paper, a wide range of prestack and post-stack seismic attributes is utilized to identify a range of properties of turbidity channel sandstone reservoir in Block L118 of J Oilfield, China. In order to better characterize the turbidity channel and lower the uncertainty, we applied multi-attribute fusion to weight a variety of seismic attributes in terms of their relevance to the identification of turbidity channel reservoir. Turbidity channel boundary is clearly present in the new attribute and the reservoir thickness prediction is improved. Additionally, fluid potential of reservoir was predicted using this fused attribute with a high value anomaly indicating high fluid potential. The multi-attribute fusion is a valid approach for the fine prediction of lithologic reservoirs, reducing the risks typically associated with exploration.     

基于流体替换技术的地震AVO属性气藏识别(英文)

传统上,油藏地球物理工程师是基于测井数据进行流体替换,计算油藏饱和不同流体时的弹性参数,并通过地震正演模拟分析油藏饱和不同流体时的地震响应,从而进行油气藏识别研究。该研究方案为油藏研究提供了重要的弹性参数和地震响应信息,但这些信息仅限于井眼位置。对于实际油藏条件,地下储层参数都是随位置变化而变化的,如孔隙度、泥质含量和油藏厚度等,因此基于传统流体替换方案得到的流体变化地震响应信息对于油气藏识别具有很大的局限性。研究通过设定联系油藏弹性参数与孔隙度、矿物组分等参数的岩石物理模型,并基于三层地质模型,进行地震正演模拟与AVO属性计算。得到油藏孔隙度、泥质含量和储层厚度变化时地震AVO属性,并建立了饱和水储层和含气储层对应AVO属性(包括梯度与截距)之间的定量关系。建立的AVO属性之间的线性关系可以实现基于地震AVO属性直接进行流体替换。最后,应用建立的流体替换前后AVO属性之间线性方程,对模拟地震数据直接进行流体替换,并通过流体替换前后AVO属性交汇图分析实现了气藏识别。     

基于波射线路径偏移压制多次波

波射线路径压制多次波的反射波成像是在偏移过程去除多次波同时仅对反射波成像.通过在共炮道集和共检波点道集分别计算炮点射线的入射角和检波点射线的出射角计算射线的路径.从炮点入射的射线与从检波点出射的射线的交点形成的走时,若等于观测走时,可以判断此条射线是反射波;反之,若不相等,则是多次波.数值实验表明此方法可以有效地去掉由于多次波能量产生的假成像点和压制多次波,因此界面可以正确归位,同时去掉由于多次波引起的假成像位置.     

地震属性技术的研究和应用

地震属性的研究大致从上个世纪60年代开始,经历了几个阶段的发展后得到了广泛的应用.由于地震属性的解释可获得许多有关地层、断层、裂缝、岩性和相的变化的重要特征信息,我们结合地震属性特征参数的意义,从实际应用出发,把地震属性分为了振幅、频（能）谱、相位、复地震道、层序、相关六大类,并根据在地层、断裂、岩性等方面的实际应用进行了详细描述,讨论了属性分析技术原理中应注意的几个环节.最后通过对断裂、河道、火成岩、古潜山等几个实例的详细描述,证明了相干、阻抗、振幅等地震属性的应用效果,说明了地震属性在实际应用中的作用.     

地震几何属性的快速算法实现

地震几何属性被广泛用于提取地震数据中的几何结构特征,从而辅助解释相关的地质沉积和构造过程.本文提出基于多种递归滤波和构造导向滤波的地震几何属性快速算法,能显著提高地震相干和体曲率的计算效率和分辨率.递归滤波的计算效率远高于传统的加权求和计算,且其计算成本与平均窗口的大小无关;同时,利用高维滤波的可分离特性可以将其分解为多个一维滤波来进一步提升计算效率并有利于多线程并行运算.此外,使用构造导向滤波实现相干计算,可以有效地消除倾斜构造对结果的影响而无需传统方法中耗时的插值运算.三维实际地震数据的应用结果表明,本文提出的快速算法能将传统的相干和曲率属性计算速度提高10~30倍且对断层的刻画更加完整和连续.

     

The distinctive attributes of debris torrents

Abstract

The term debris torrent was introduced in North America's Pacific Northwest region to describe coarse-grained, rapid channelized flows rich in organic debris. Environmental conditions favouring their occurrence and distinctive criteria for recognition of debris torrents are discussed. A classification of gravitational and fluvial sediment transporting processes is presented as a framework for papers presented at the Debris Torrent Workshop 6a held in Vancouver in August, 1987.     

Texture attributes for detection of salt

Within areas of salt tectonics, seismic imaging requires extensive updating of the velocity model. This includes defining the boundaries of salt structures which are often characterized by changes in texture of the seismic signal rather than reflectivity. The main characteristics of texture inside salt structures are identified. Three groups of texture attributes are studied: gray-level co-occurrence matrix (GLCM) attributes, frequency-based attributes, and dip and similarity attributes. Various combinations of the selected attributes are tested in a supervised Bayesian classification method. Experimental results show that the classification performance improves by combining at least two texture attribute groups. The classifier computes an estimate of the pixelwise probability of salt. It can then be applied to compute the probability of salt on different seismic sections. Classification results were found more robust based on timeslices. The result from classification, the salt probability image, is then input to a segmentation algorithm that produces a smooth border delimiting the extent of the salt. The segmented salt contours corresponded fairly well to the contours provided by an interpreter.     

数据自相关多次波偏移成像

在常规偏移方法中一般都需要压制地震数据中的多次波,仅利用一次波信息成像,把自由表面反射的多次波视为噪声,但是在多次波中也包含着地下结构信息,应该将其充分利用到成像中来.事实上,已经有不少成像方法试图利用多次波信息,但是大部分方法都需要对多次波进行预测.本文提出了基于傅里叶有限差分偏移算子的数据自相关偏移方法.在这种偏移方法中,对含有一次波和多次波的地震数据,分别进行下行和上行延拓,然后直接利用常规的互相关成像条件成像.由于波场延拓采用了傅里叶有限差分算子,其计算效率高,能够很好地对复杂介质中的地震数据进行延拓.在数值试验中,使用了一个含散射点的三层模型和Marmousi模型.合成数据测试结果表明,这种方法可以对更大范围的地下构造成像,比常规的只利用一次波的傅里叶有限差分法照明度更好,并且在浅层可以提供更高的分辨率.我们提出的数据自相关策略易于实现且避免了繁杂的多次波预测,这对于复杂地下构造成像可能有着重大意义.     

格子法在起伏地表叠前逆时深度偏移中的应用

基于全程波波动方程的逆时偏移(Reverse Time Migration)可以对回转波、多次反射波成像,不受横向速度变化影响,没有倾角限制,随着计算机软硬件技术的进步,再次成为偏移方法研究热点.本文将格子法用于叠前逆时深度偏移成像.格子法作为波场延拓方法,处理起伏地表边界条件容易,可用于含起伏地表边界条件的逆时波场延拓;可利用变尺度非规则对计算域进行离散,因此可根据速度模型调整网格尺度来降低存储量,放大时间步长,降低计算量.采用光滑的曲人工边界,也可避免常规的PML吸收边界存在的角点区域需特别处理的麻烦.本方法通过事先计算和存储边界单元的局部几何参数,与直边界PML方法相比不增加任何计算量.格子法还具有容易实现并行计算的特点,非常适用于叠前逆时偏移.本文给出了二维问题算例.     

Bed load transport by bed form migration

A theoretically-based methodology is presented for the determination of bed load transport from high-resolution measurements of bed surface elevations for steady-state or developing dunes. The methodology is based on the general form of the Exner equation for sediment continuity and requires information on the distribution of sediment volume concentration as well as the migration velocity of bed layers. In order to determine layer speeds, a new method based on cross-correlation analysis of elevation slices is proposed. The methodology is tested using artificially-created data as well as data from a physical model and from a flume study of developing bed forms. The analyses show the applicability of the method to determine bed load transport without the need to introduce assumptions about the form of the migrating surface. It is shown that predicted transport rates match measured or theoretical transport rates for steadily moving bed forms of an arbitrary shape. The method can also be used to predict transport rates over deforming bed forms, with the reasons for potential deviations between predicted and measured or theoretical transport rates for deforming bed forms identified and discussed. It is further shown that a simplified bulk-surface approach, that is relatively straightforward to apply and in which it is assumed that bed-layer velocity is constant with depth, gives results that are comparable to analyses based on determined bed-layer velocity variation with depth.     

Fast velocity analysis by wave path migration

Iterative migration velocity analysis is computationally expensive, where most of the computation time is used for generating prestack depth images. By using a reduced form of Kirchhoff migration, denoted as wave path migration, we can significantly speed up the depth imaging process and reduce the entire velocity analysis expense accordingly. Our results with 2D synthetic and field data show that wave path migration velocity analysis can efficiently improve the velocity model and the wave path migration velocity analysis updated velocity correlates well with that from the Kirchhoff migration velocity analysis. The central processing unit comparison shows that, for a 2D synthetic and field data set, wave path migration velocity analysis is six times faster than Kirchhoff migration velocity analysis. This efficiency should be even greater for 3D data.     

复杂气藏AVO属性交会含气性检测应用研究

乌审召地区沉积相带复杂多变、储层非均质性强、气层AVO响应多变,含气储层预测难度大.本文在精细岩石物理分析的基础上,选取具有明确岩石物理含义且对气层敏感的AVO属性,针对不同AVO分类井进行AVO正演建模和流体替代分析,研究该区AVO气层响应特征及属性交会规律,并确定了以NI和PR属性交会为核心的AVO气层检测方法及流程,为探索解决该区含气性预测难题提供了有价值的思路.利用这套方法,对该区储层进行了含气性检测,取得了良好效果.     

Mapping of moveout attributes using local slopes

Decomposing seismic data in local slopes is the basic idea behind velocity‐independent imaging. Using accurate moveout approximations enables computing moveout attributes such as normal moveout velocity and nonhyperbolic parameters as functions of zero‐offset travel time. Mapping of moveout attributes is performed from the pre‐stack seismic data domain into the time‐migrated image domain. The different moveout attributes have different accuracy for a given moveout approximation that depends on the corresponding order of travel‐time derivative. The most accurate attribute is the zero‐offset travel time, and the nonhyperbolic parameter has the worst accuracy, regardless of the moveout approximation. Typically, the mapping of moveout attributes is performed using a point‐to‐point procedure, whereas the generalized moveout approximation requires two point‐to‐point mappings. Testing the attribute mapping on the different models shows that the accuracy of mapped attributes is model dependent, whereas the generalized moveout approximation gives practically exact results.     

Experimental study of fly-ash migration by using magnetic method

Several studies have shown that magnetic measurements can be used in assessing soil contamination due to atmospheric deposition of pollutants. Reliable spatial mapping of magnetic susceptibility of soils assumes high temporal stability of deposited particles, accumulated in top-soil horizons. One of the main methodological concerns is whether the migration of deposited anthropogenic ferrimagnetic particles may bias the measured values. Measurements carried out on high-porosity (sandy) soils, or on soils with a very variable water regime may yield inconsistent values of top-soil magnetic susceptibility as the indicator of contamination. This study focuses on the laboratory examination of migration of fly ashes from a coal-burning power plant in sands of different porosity and under a simulated rain regime. Columns of sand of different grain sizes, placed in plastic cylinders, were contaminated on the surface by the fly ash. The vertical migration of magnetic particles was monitored using measurements of magnetic susceptibility with an SM400 Kappameter. Calibration measurements in the water environment showed an erroneous performance and resulted in the technical improvement of the used susceptibility meter (Model 2009). Our results show that the vertical distribution of flyash particles deposited on fine sand is very stable even after repeated rain simulation. The peak value of magnetic susceptibility is located in a stable position a few millimeters under the surface. Hence, standard top-soil magnetic mapping is in such a case reliable and fully representative. Contrary to that, in case of coarse sand, the peak value of magnetic susceptibility migrates by more than 10 cm. The results will be further used for numerical modeling of contaminant transport in porous media.     

Reservoir prediction using multi-wave seismic attributes

The main problems in seismic attribute technology are the redundancy of data and the uncertainty of attributes, and these problems become much more serious in multi-wave seismic exploration. Data redundancy will increase the burden on interpreters, occupy large computer memory, take much more computing time, conceal the effective information, and especially cause the "curse of dimension". Uncertainty of attributes will reduce the accuracy of rebuilding the relationship between attributes and geological significance. In order to solve these problems, we study methods of principal component analysis (PCA), independent component analysis (ICA) for attribute optimization and support vector machine (SVM) for reservoir prediction. We propose a flow chart of multi-wave seismic attribute process and further apply it to multi-wave seismic reservoir prediction. The processing results of real seismic data demonstrate that reservoir prediction based on combination of PP- and PS-wave attributes, compared with that based on traditional PP-wave attributes, can improve the prediction accuracy.     

Seismic facies analysis through musical attributes

Seismic facies analysis is a well‐established technique in the workflow followed by seismic interpreters. Typically, huge volumes of seismic data are scanned to derive maps of interesting features and find particular patterns, correlating them with the subsurface lithology and the lateral changes in the reservoir. In this paper, we show how seismic facies analysis can be accomplished in an effective and complementary way to the usual one. Our idea is to translate the seismic data in the musical domain through a process called sonification, mainly based on a very accurate time–frequency analysis of the original seismic signals. From these sonified seismic data, we extract several original musical attributes for seismic facies analysis, and we show that they can capture and explain underlying stratigraphic and structural features. Moreover, we introduce a complete workflow for seismic facies analysis starting exclusively from musical attributes, based on state‐of‐the‐art machine learning computational techniques applied to the classification of the aforementioned musical attributes. We apply this workflow to two case studies: a sub‐salt two‐dimensional seismic section and a three‐dimensional seismic cube. Seismic facies analysis through musical attributes proves to be very useful in enhancing the interpretation of complicated structural features and in anticipating the presence of hydrocarbon‐bearing layers.