岩石物理驱动的相约束叠前地震概率化反演方法

地震岩石物理是连接岩石弹性参数与储层物性参数的桥梁,叠前地震反演是实现地下岩石弹性、物性、岩性及含流体性质定量表征的重要方法.文章构建了碎屑岩地震岩石物理高阶近似模型,推导了利用岩石模量高阶近似(Jacobian、Hessian矩阵)表征的叠前地震AVO反射特征方程,并分析了岩石孔隙度、泥质含量及流体饱和度对AVO反射率的贡献度,探讨了此方程在岩石物性参数直接预测方面的可行性.以此为基础,在待反演模型参数服从混合概率先验模型的前提下,文章提出了基于差分进化-马尔可夫链蒙特卡罗随机模型的相约束叠前地震概率化反演方法,兼具差分进化算法的全局寻优特性和马尔可夫链蒙特卡罗模型的不确定性分析能力;通过多条马尔可夫链的交叉并行,可以同步获得待反演模型参数的多个随机解,进而模拟待反演模型的后验概率密度分布,后验均值作为待反演模型的最优解,方差与置信区间用来评价反演结果的不确定性,实现储层弹性、物性、离散岩相及干岩石骨架等参数的同步预测.通过理论试验和实际资料处理验证了该理论方法的有效性.     

布谷鸟马尔科夫链蒙特卡洛混合高斯地质统计学随机反演

地质统计学随机反演可以获得比常规反演更高分辨率的结果,目前已成为储层高分辨率预测的主流方法.地下不同岩相储层参数存在明显差异,本文在地质统计学反演框架下构建了岩相和储层参数同步反演目标函数,实现不同岩相条件下储层参数分布精细描述.在求解该高维数据多参数同步反演问题时,本文将可以动态调节搜索步长的布谷鸟算法与马尔科夫链蒙特卡洛方法融合,采用多条马尔科夫链进行Levy飞行产生新解的策略扩大解的空间范围,通过适应度最佳选择输出最优解实现全局优化迭代,有效提升了反演方法的稳定性和全局最优性,避免了传统马尔科夫链蒙特卡洛方法因抽样随机性而陷入局部最优的问题.通过含噪声模型和实际数据分析验证了本文方法的有效性.     

基于Metropolis优化的叠前全局迭代地质统计学反演方法

叠前地质统计学反演将随机模拟与叠前反演相结合,不仅可以反演各种储层弹性参数,还提高了反演结果的分辨率.基于联合概率分布的直接序贯协模拟方法可以在原始数据域对数据进行模拟,不需要对数据进行高斯变换,拓展了地质统计学反演的应用范围;而联合概率分布的应用确保了反演参数之间相关性,提高了反演的精度.本文将基于联合概率分布的直接序贯协模拟方法与蒙特卡洛抽样算法相结合,参考全局随机反演策略,提出了基于蒙特卡洛优化算法的全局迭代地质统计学反演方法.为了提高反演的稳定性,我们修改了局部相关系数的计算公式,提出了一种新的基于目标函数的优化局部相关系数计算公式并应用到协模拟之中.模型测试及实际数据应用表明,该方法可以很好的应用于叠前反演之中.     

地震岩相识别概率表征方法

储层岩相分布信息是油藏表征的重要参数,基于地震资料开展储层岩相识别通常具有较强的不确定性.传统方法仅获取唯一确定的岩相分布信息,无法解析反演结果的不确定性,增加了油藏评价的风险.本文引入基于概率统计的多步骤反演方法开展地震岩相识别,通过在其各个环节建立输入与输出参量的统计关系,然后融合各环节概率统计信息构建地震数据与储层岩相的条件概率关系以反演岩相分布概率信息.与传统方法相比,文中方法通过概率统计关系表征了地震岩相识别各个环节中地球物理响应关系的不确定性,并通过融合各环节概率信息实现了不确定性传递的数值模拟,最终反演的岩相概率信息能够客观准确地反映地震岩相识别结果的不确定性,为油藏评价及储层建模提供了重要参考信息.模型数据和实际资料应用验证了方法的有效性.     

NBR油田优质储层叠前叠后联合反演与应用

开展NBR油田地震优质储层预测,可有效支撑低效井区开发和外扩区储量动用,对油田产能建设有重要意义.本文针对地震反演存在叠后反演参数单一、叠前反演多解性强的问题,提出三步流程实现叠前叠后联合反演,达到优质储层定量表征目的.步骤一通过叠后地质统计学反演预测砂泥岩;步骤二开展岩石物理分析,明确了剪切模量为含油砂体敏感弹性参数,再以步骤一反演结果为约束,采用叠前扩展弹性阻抗反演(EEI)预测储层含油性;步骤三仍以步骤一结果为约束,采用高斯配置协模拟测井参数反演预测孔隙度、渗透率.最后按照优质储层物性界限,通过剪切模量、孔隙度和渗透率体得到优质储层三维表征体.上述方法在NBR油田A组油层中优质储层预测符合率达到78.3%,优选甜点区部署水平井效果显著.     

储层弹性与物性参数地震叠前同步反演的确定性优化方法

储层弹性与物性参数可直接应用于储层岩性预测和流体识别,是储层综合评价和油气藏精细描述的基本要素之一.现有的储层弹性与物性参数地震同步反演方法大都基于Gassmann方程,使用地震叠前数据,通过随机优化方法反演储层弹性与物性参数;或基于Wyllie方程,使用地震叠后数据,通过确定性优化方法反演储层弹性与物性参数.本文提出一种基于Gassmann方程、通过确定性优化方法开展储层弹性和物性参数地震叠前反演的方法,该方法利用Gassmann方程建立储层物性参数与叠前地震观测数据之间的联系,在贝叶斯反演框架下以储层弹性与物性参数的联合后验概率为目标函数,通过将目标函数的梯度用泰勒公式展开得到储层弹性与物性参数联合的方程组,其中储层弹性参数对物性参数的梯度用差分形式表示,最后通过共轭梯度算法迭代求解得到储层弹性与物性参数的最优解.理论试算与实际资料反演结果证明了方法的可行性.     

基于概率统计的地震岩相识别不确定性定量评价方法

地震岩相识别能够提供具有不同储层特征的岩相分布信息,对岩相识别的不确定性开展定量评价分析可降低后期油藏建模与储层评价的风险.考虑了地震岩相识别中测井岩相定义、岩石物理建模、井震尺度匹配及地震反演等环节的不确定性对岩相识别的影响,基于概率统计方法,引入熵函数实现了地震岩相识别不确定性定量评价,并结合岩相概率、重建率等多角度综合定量分析不确定性的构成及传递特征,系统地实现了地震岩相识别不确定性评价流程的整体连通.提出了结合属性交绘特征约束反演参数空间,提高地震岩相识别运算效率.模拟数据分析表明利用熵函数可精确实现岩相识别不确定性地定量表征,利用属性交绘特征约束参数空间既大幅度减少运算量,也可降低地震岩相识别的不确定性.     

地质统计学反演中变差函数地质含义及求取方法探讨

地质统计学反演具有较高的空间分辨率,在储层预测中应用广泛,其反演精度受地质框架模型、纵/横向变程和岩性比例等多个因素的影响.反演过程中主要基于地震数据提取平面属性采用试错的方法来求取横向变程,该方法人为因素影响大、随机性强,且未赋予参数明确的地质含义.针对这一问题,本文提出了层序约束下基于地质信息求取横向变程的方法.方法以层序地层格架为约束,以井点信息为出发点,在单井垂向单一正旋回砂体厚度识别的基础上,通过经验公式、拟合公式获取储层地质信息(点坝宽度和点坝长度),并根据数据统计分析结果指导反演横向变程的求取.将该方法应用于渤海W油田北区明化镇组下段II油组地质统计学反演的参数求取中,结果表明:以层序为约束基于储层地质信息所求取横向变程约束下的地质统计学反演结果分辨率高,与井上地质信息吻合性更好,反演结果更能清晰表征储层内部砂体叠置关系及其空间展布特征,有助于提高薄储层表征精度,为开发后期的井位部署和井位调整提供依据.     

基于弹性阻抗的储层物性参数预测方法

储层物性参数是储层描述的重要参数,常规的基于贝叶斯理论的储层物性参数反演方法大多是通过反演获得的弹性参数进一步转换而获得物性参数,本文提出一种基于弹性阻抗数据预测储层物性参数的反演方法.该方法主要通过建立可以表征弹性阻抗与储层物性参数之间关系的统计岩石物理模型,联合蒙特卡罗仿真模拟技术,在贝叶斯理论框架的指导下,应用期望最大化算法估计物性参数的后验概率分布,最终实现储层物性参数反演.经过模型测试和实际资料的处理,其结果表明本文提出的方法具有预测精度高,稳定性强,横向连续性好等优点.     

岩石物理驱动的储层裂缝参数与物性参数概率地震反演方法

长波长假设条件下,各向同性背景地层中发育一组平行排列的垂直裂缝可等效为具有水平对称轴的横向各向同性（HTI）介质.基于不同观测方位的岩石地震响应特征变化,宽方位地震数据不仅可实现裂缝岩石弹性参数与各向异性参数的预测,同时也蕴含着丰富的孔隙度等储层物性参数信息.本文结合实际地震资料提出了贝叶斯框架下岩石物理驱动的储层裂缝参数与物性参数概率地震联合反演方法,首先基于AVAZ反演裂缝岩石的弹性参数与各向异性参数,并在此基础上通过统计岩石物理模型表征孔隙度、裂缝密度等各向异性介质储层参数与裂缝岩石参数的相互关联,并采用马尔科夫链蒙特卡洛（MCMC）抽样方法进行大量样本的随机模拟,使用期望最大化（EM）算法估计后验条件概率分布,最终寻找最大后验条件概率对应的孔隙度、裂缝密度等HTI裂缝介质储层参数即为反演结果.测井及实际地震数据处理表明,该方法能够稳定合理地从方位地震资料中获取裂缝岩石弹性参数与各向异性参数,并提供了一种较为可靠的孔隙度、裂缝密度等裂缝介质储层参数概率地震反演方法.     

基于随机地震反演的Russell流体因子直接估算方法

本文研究了一种基于随机地震反演的Russell流体因子直接估算方法,该方法是一种基于蒙特卡罗的非线性反演,能够有效地融合测井资料中的高频信息,提高反演结果的分辨率.本文应用贝叶斯理论框架,首先通过测井数据计算井位置处的Russell流体因子,利用序贯高斯模拟方法(sequential Gaussian simulation,SGS)得到流体因子的先验信息;然后构建似然函数;最后利用Metropolis抽样算法对后验概率密度进行抽样,得到反演的Russell流体因子.其中对每道数据进行序贯高斯模拟时,采用一种新的逐点模拟方式,具有较高的计算速度.数值试验表明:反演结果与理论模型和实际测井数据吻合较好,具有较高的分辨率,对于判识储层含流体特征具有较好的指示作用.     

基于FFT-MA谱模拟的快速随机反演方法研究

虽然基于地质统计学的随机反演方法能够有效融合测井资料中的高频信息,但计算效率低,占用内存大,限制了它在实际资料中的应用.本文在保留传统随机反演方法优点的基础上,创造性地引入傅里叶滑动平均(Fast Fourier Transform-Moving Average,FFT-MA)谱模拟进行频率域的地质统计模拟,并利用逐步变形算法(Gradual Deformation Method,GDM)确保模拟结果与实际地震数据的匹配,构建了基于FFT-MA谱模拟的新的快速随机反演方法.与常规随机反演相比,新方法不仅分辨率高,而且能够使反演解得到快速收敛,有效提高计算效率,减少内存占用.模型试算获得了与理论模型吻合度较好的高分辨率反演结果.实际资料分析也表明新方法所得到的高分辨率反演结果能够对薄互储层进行良好的展示,为薄储层的识别提供高效可靠的技术支持.     

Geostatistical seismic Amplitude‐versus‐angle inversion

Seismic inversion plays an important role in reservoir modelling and characterisation due to its potential for assessing the spatial distribution of the sub‐surface petro‐elastic properties. Seismic amplitude‐versus‐angle inversion methodologies allow to retrieve P‐wave and S‐wave velocities and density individually allowing a better characterisation of existing litho‐fluid facies. We present an iterative geostatistical seismic amplitude‐versus‐angle inversion algorithm that inverts pre‐stack seismic data, sorted by angle gather, directly for: density; P‐wave; and S‐wave velocity models. The proposed iterative geostatistical inverse procedure is based on the use of stochastic sequential simulation and co‐simulation algorithms as the perturbation technique of the model parametre space; and the use of a genetic algorithm as a global optimiser to make the simulated elastic models converge from iteration to iteration. All the elastic models simulated during the iterative procedure honour the marginal prior distributions of P‐wave velocity, S‐wave velocity and density estimated from the available well‐log data, and the corresponding joint distributions between density versus P‐wave velocity and P‐wave versus S‐wave velocity. We successfully tested and implemented the proposed inversion procedure on a pre‐stack synthetic dataset, built from a real reservoir, and on a real pre‐stack seismic dataset acquired over a deep‐water gas reservoir. In both cases the results show a good convergence between real and synthetic seismic and reliable high‐resolution elastic sub‐surface Earth models.     

Seismic driven probabilistic classification of reservoir facies for static reservoir modelling: a case history in the Barents Sea

In this paper we present a case history of seismic reservoir characterization where we estimate the probability of facies from seismic data and simulate a set of reservoir models honouring seismically‐derived probabilistic information. In appraisal and development phases, seismic data have a key role in reservoir characterization and static reservoir modelling, as in most of the cases seismic data are the only information available far away from the wells. However seismic data do not provide any direct measurements of reservoir properties, which have then to be estimated as a solution of a joint inverse problem. For this reason, we show the application of a complete workflow for static reservoir modelling where seismic data are integrated to derive probability volumes of facies and reservoir properties to condition reservoir geostatistical simulations. The studied case is a clastic reservoir in the Barents Sea, where a complete data set of well logs from five wells and a set of partial‐stacked seismic data are available. The multi‐property workflow is based on seismic inversion, petrophysics and rock physics modelling. In particular, log‐facies are defined on the basis of sedimentological information, petrophysical properties and also their elastic response. The link between petrophysical and elastic attributes is preserved by introducing a rock‐physics model in the inversion methodology. Finally, the uncertainty in the reservoir model is represented by multiple geostatistical realizations. The main result of this workflow is a set of facies realizations and associated rock properties that honour, within a fixed tolerance, seismic and well log data and assess the uncertainty associated with reservoir modelling.     

Synthetic Seismograms and Wide-angle Seismic Attributes from the Gaussian Beam and Reflectivity Methods for Models with Interfaces and Velocity Gradients

— The effects of interfaces and velocity gradients on wide-angle seismic attributes are investigated using synthetic seismograms. The seismic attributes considered include envelope amplitude, pulse instantaneous frequency, and arrival time of selected phases. For models with interfaces and homogeneous layers, head waves can propagate which have lower amplitudes, as well as frequency content, compared to the direct arrivals. For media with interfaces and velocity gradients, higher amplitude diving waves and interference waves can also occur. The Gaussian beam and reflectivity methods are used to compute synthetic seismograms for simple models with interfaces and gradients. From the results of these methods, seismic attributes are obtained and compared. It was found that both methods were able to simulate wide-angle seismic attributes for the simple models considered. The advantage of using the Gaussian beam method for seismic modeling and inversion is that it is fast and also asymptotically valid for laterally varying media.     

Accounting for Aquifer Heterogeneity from Geological Data to Management Tools

A nested workflow of multiple‐point geostatistics (MPG) and sequential Gaussian simulation (SGS) was tested on a study area of 6 km² located about 20 km northwest of Quebec City, Canada. In order to assess its geological and hydrogeological parameter heterogeneity and to provide tools to evaluate uncertainties in aquifer management, direct and indirect field measurements are used as inputs in the geostatistical simulations to reproduce large and small‐scale heterogeneities. To do so, the lithological information is first associated to equivalent hydrogeological facies (hydrofacies) according to hydraulic properties measured at several wells. Then, heterogeneous hydrofacies (HF) realizations are generated using a prior geological model as training image (TI) with the MPG algorithm. The hydraulic conductivity (K) heterogeneity modeling within each HF is finally computed using SGS algorithm. Different K models are integrated in a finite‐element hydrogeological model to calculate multiple transport simulations. Different scenarios exhibit variations in mass transport path and dispersion associated with the large‐ and small‐scale heterogeneity respectively. Three‐dimensional maps showing the probability of overpassing different thresholds are presented as examples of management tools.     

塔河油田卡4段地层相控储层预测

塔河油田石炭系卡4段储层灰岩含量较高,造成地震预测多解性严重,文章提出相控储层预测的思路和研究方法：提出以区域等时地层格架为约束的局部区域和同一沉积体系的准层序级别的砂体等时对比新思路,以Wheeler域年代地层切片技术为手段建立精细等时层序地层格架,进而开展准层序级别的变时窗属性提取分析,采用振幅和伪熵属性表征卡4段沉积微相展布,以Wheeler反变换技术实现了实践意义上的相控储层预测理念,雕刻了有利储层空间形态,为该区岩性圈闭的发现提供了参考.     

Geostatistical facies simulation with geometric patterns of a petroleum reservoir

During exploration and pre-feasibility studies of a typical petroleum project many analyses are required to support decision making. Among them is reservoir lithofacies modeling, preferably using uncertainty assessment, which can be carried out with geostatistical simulation. The resulting multiple equally probable facies models can be used, for instance, in flow simulations. This allows assessing uncertainties in reservoir flow behavior during its production lifetime, which is useful for injector and producer well planning. Flow, among other factors, is controlled by elements that act as flow corridors and barriers. Clean sand channels and shale layers are examples of such reservoir elements that have specific geometries. Besides simulating the necessary facies, it is also important to simulate their shapes. Object-based and process-based simulations excel in geometry reproduction, while variogram-based simulations perform very well at data conditioning. Multiple-point geostatistics (MPS) combines both characteristics, consequently it was employed in this study to produce models of a real-world reservoir that are both data adherent and geologically realistic. This work aims at illustrating how subsurface information typically available in petroleum projects can be used with MPS to generate realistic reservoir models. A workflow using the SNESIM algorithm is demonstrated incorporating various sources of information. Results show that complex structures (e.g. channel networks) emerged from a simple model (e.g. single branch) and the reservoir facies models produced with MPS were judged suitable for geometry-sensitive applications such as flow simulations.