An Automatic History Matching Module with Distributed and Parallel Computing

Abstract

The data assimilation process of adjusting variables in a reservoir simulation model to honor observations of field data is known as history matching and has been extensively studied for a few decades. However, limited success has been achieved due to the high complexity of the problem and the large computational effort required in the real fields. Successful applications of the ensemble Kalman filter (EnKF) to reservoir history matching have been reported in various publications. The EnKF is a sequential method: once new data are available, only these data are used to update all the unknown reservoir properties while previous geological information is unused directly. In this method, multiple reservoir models rather than one single model are implemented, and each model is called a member. Conventionally, the impact of each member on the updating is equally treated. Another approach is the weighted EnKF. During the updating, the method weighs the contribution of each member through the comparison between the simulation response and the measurements. Better matching performance has been found in the weighted EnKF than in the conventional EnKF. To improve computational efficiency, two-level high-performance computing for reservoir history matching process is implemented in this research, distributing ensemble members simultaneously while simulating each member in a parallel style.

An automatic history-matching module based on the weighted EnKF and high-performance computing is developed and validated through a synthetic case operating from primary, waterflooding to flooding of water alternating with gas. The study shows that the weighted EnKF improves the matching results, and the high-performance computing process significantly reduces the history matching execution time.     

基于多次数据吸收集合平滑算法的自动油藏历史拟合研究

针对常见历史拟合方法存在计算量大、油藏参数更新异常、油藏模型修正失真等问题.采用集合平滑算法,通过引入集合卡尔曼滤波算法(EnKF)中多次迭代思路,对相同数据重复吸收,推导出多次数据吸收集合平滑算法(ES-MDA)的核心公式,并编写了自动油藏历史拟合软件.以北海布伦特油田海相砂岩油藏为例,将基于ES-MDA算法的油藏自...     

EnKF整合三维地震数据和动态数据的应用

主要介绍集合卡尔曼滤波EnKF在更新油藏储层静态参数方面的应用。根据集合卡尔曼滤波产生的必要条件,介绍了集合卡尔曼滤波整合动态数据和三维地震数据的基本原理。通过实例分析,验证了集合卡尔曼滤波在整合动态数据和三维地震数据更新油藏参数方面的有效性,更新后的油藏模型能够较好地反映储层非均质性,并且与三维地震数据有较好的一致性。还比较了利用三维地震数据和四维地震数据进行更新油藏模型的差别。通过bKF方法将地震数据和动态数据结合起来描述油藏特征,能够很好地拟合观测数据,并获得较好的模型。     

基于单井敏感性局域化EnKF的油藏辅助历史拟合方法

常用的油藏自动历史拟合算法多数存在梯度计算不准确、产生伪相关性等问题,导致参数修正错误、模型反演失真。通过建立一种基于单井动态敏感性的局域化集合卡尔曼滤波（FMM-CL-EnKF）历史拟合方法,解决了传统距离截断方法处理伪相关性时与实际地层状况不匹配的问题。基于程函方程,根据地质模型静态参数场信息,快速追踪压力波从井点到地层网格的传播时间确定各单井动态最大敏感性区域,从而构建局域化矩阵。同时,结合集合卡尔曼滤波（EnKF）方法,实现数据同化方法梯度的矫正,减弱伪相关,通过逐步拟合生产动态达到更新油藏模型和获取最优估计的目的。概念算例和矿场算例的计算结果表明,FMM-CL-EnKF方法在模型集合生产动态拟合效果及反演模型参数场准确性等方面均优于标准EnKF方法。     

单一模型EnKF法更新油藏模型的探讨

近年来，人们开始利用集合卡尔曼滤波（EnKF）进行自动历史拟合，更新油藏模型。实验证明EnKF方法是一种有效的方法。EnKF方法要求一组初始实现，但是在实际应用中往往只有一个油藏或地质模型，这使得直接利用EnKF进行历史拟合，更新油藏模型比较困难。为此，提出了一种由一个模型派生出多个模型来满足EnKF基本要求的随机导航点方法，并试验在尽量少的模型条件下，利用EnKF更新油藏模型。模型实验表明，利用随机点抽样派生出多个模型，再利用EnKF可以实现单一模型更新，最终取得的模型与参考模型具有较好的一致性。     

基于流线EnKF油藏自动历史拟合

作为一种油藏参数动态估计的优化算法,将集合卡尔曼滤波EnKF与流线方法相结合,在算法实现过程中,选择具有更高计算精度和更快计算速度的流线模拟器进行预测,将油藏模型自动还原为一系列沿流线的一维模型,使数值弥散和受网格划分的影响达到最小,保持了明显的驱替前缘。采用序贯高斯协模拟方法生成一组地质模型,通过实时观测数据（产量及含水率等）,连续动态更新油藏模型的静态参数（渗透率及孔隙度等）、动态参数（压力及饱和度等）,同时实现流线分布的更新,直观地反映油藏流体在注采井之间的运动轨迹。采用Bayes理论阐述了流线EnKF数学原理,并通过拟合计算一个二维水驱油藏模型,验证了方法的有效性。     

A New Methodology for Assisted History Matching Using Independent Objective Functions

Abstract

History matching is a complex inverse problem for which the degree of difficulty and the computational effort (in terms of number of simulations) increase with the increasing of the number of matching parameters. This article presents a new methodology for assisted history matching based on independent objective functions that decrease the number of simulations. The proposed approach consists of the optimization of several objective functions related to each region of the reservoir to be matched, such as a well or a group of wells. Optimization processes, one for each objective function, are started simultaneously, modifying the same data file, yielding a more efficient process, allowing speedup and preserving the quality of the results. The methodology was successfully applied to an offshore field. The results show that the quality of results is practically the same when compared to the conventional procedures, i.e., matching of the wells individually or combining several wells. The advantage is a significant reduction on the number of simulations, preserving the quality of the results.     

Reconstruction of Porosity Distribution for History Matching Using Genetic Algorithm

In order to test the capability of Genetic Algorithm for solving the optimization problems the authors defined an optimization problem with predefined objective function for reconstruction of an initial porosity distribution. The main objective was to reconstruct a known porosity distribution by using an improved model of a Genetic Algorithm consisting of new genetic operators rather than traditional operators used by previous researchers. The results show that genetic algorithm can be used for finding optimum and repeatable solution in many different porosity distribution scenarios including simple to very complex models.     

基于微地震离散裂缝与自动历史拟合的数值模拟

针对复杂缝网精细刻画、表征复杂,数值模拟历史拟合繁琐、不确定性强,导致非常规储层实现精准数值模拟难度大的问题,采用微地震复杂缝网反演、离散裂缝方法缝网精细刻画、集合卡曼滤波方法(EnKF)自动拟合技术3种手段形成的综合数值模拟技术,对复杂缝网条件下的非常规储层实现精准数值模拟.结果表明:文中提出的复杂缝网反演方法与直接...     

Assisted History Matching Using Streamline Simulation

The quantity and quality of the information obtained from modern reservoir characterization techniques is still not sufficient to perfectly represent the reservoir. Therefore, reservoir models must be calibrated in order to provide a more reliable production forecast. This process is called production history matching. History matching is one of the most time-consuming tasks of a reservoir study due to the complexity of the process, multiple acceptable solutions, and demand for specialist knowledge. Many times this task is still based on a trial and error procedure, which is normally very inefficient because it involves a large number of cycles. This paper shows that it is possible to integrate the experience of the professionals involved in the process with some automatic techniques to accelerate the process and to obtain better solutions. This process is called Assisted History Matching. The use of streamline simulation as a complementary technique is applied to allow a better understanding of fluid flow behavior on the reservoir, mapping heterogeneities location, and then choosing adequate geological parameters, such as permeability and porosity, according to the identified flow patterns. Reservoir parameters are modified along blocks mapped by the streamlines. Automatic procedures are then applied along with parallel computing to find the best combination of the selected parameters. The methodology was applied to a complex real field where satisfactory results were obtained.     

自动历史拟合计算油水相渗关系新方法

利用岩心压汞资料求出了孔隙结构分形维数；在此基础上，通过耦合孔隙结构分形维数建立闻新的水驱油数学模型，采用历史拟合方法整理水驱油试验数据，以求得油水相对渗透率曲线，并与原有数学模型和计算方法进行了对比分析。     

Streamline-Based History Matching Constrained to Reservoir Geostatistics Using Gradual Deformation Technique

Abstract

A new and general procedure for history matching that uses streamline simulation and a gradual deformation technique has been proposed. Streamline trajectories define the major flow paths and help the algorithm to modify the reservoir model only in the regions that cause the mismatch between simulation results and field observations. The use of a gradual deformation technique enables the algorithm to remain constrained to reservoir geostatistics. It also reduces the number of independent variables in the optimization problem. In our algorithm, effective conductivities are defined along each streamline. The effective streamline conductivities are then adjusted using the values of measured and computed breakthrough times of individual streamlines. Then an intermediate objective function is defined to minimize the difference between adjusted (desired) and computed effective streamline conductivities. The algorithm continues until a satisfactory match is obtained. In order to examine the quality of our history matching procedure, it is applied to a synthetic reservoir.     

蜡油自动反冲洗过滤器运行问题与对策

详细介绍了延迟焦化装置蜡油自动反冲洗过滤器（简称反冲洗过滤器）的性能及运行状况,针对生产中反冲洗过滤器出现的滤芯断裂、“O”圈失效、端头密封泄露等问题进行了分析,并根据实际情况进行了改造。实践证明．反冲洗过滤器端头泄露是造成过滤器运行效果差的主要原因．在“O”圈密封不能满足运行条件的情况下焊死端头是解决泄露问题的关键。     

海上油田橇装式滤器装置自动控制系统设计

采用西门子可编程序控制器实现了海上油田橇装式滤器装置全自动控制的设计,提高了自动化程度,避免了原滤器切换需要人工干预带来的不便。     

异常高压气藏气井产量递减自动拟合研究

在LM产量递减自动拟合方法的基础上,结合回归分析建立了异常高压气藏气井的产量递减自动拟合数学模型。运用该方法不需要进行图版拟合就可以确定出异常高压气藏的渗透率、孔隙度、有效厚度和地质储量。为了改善模型的预测精度,采用了去掉不稳定生产数据后,再用自动拟合方法来反求地层参数。为了便于模型在实际应用中得到正确的结果,提出了检验计算结果正确与否的检验标准。     

复杂裂缝性油藏历史拟合中的特殊做法

克拉玛依油田八区 上二叠统下乌尔禾组油藏是一个具有边底水的特低渗透裂缝性巨厚砾岩油藏,在油藏数值模拟研究过程中,针对油藏的具体特点,对“非油层”出油问题、注入水漏失问题、水淹水窜井问题、地层水侵入问题以及不同水驱油模式问题采取了一些特殊做法,对400多口井、23年的生产历史进行了精细拟合,单井的压力、含水率拟合符合率达85%以上。获得了很好的拟合结果,为类似油藏的数值模拟提供了可供借鉴的经验,这些做法可推广应用于其它低渗透裂缝性油藏。     

多参数约束聚合物驱历史拟合方法

聚合物驱数值模拟需要对大量物理化学现象进行描述,与水驱相比存在很强的特殊性。参考和借鉴水驱数值模拟历史拟合相关方法和聚合物驱油机理研究成果,筛选出聚合物的吸附量、残余阻力系数、聚合物溶液相对黏度、不可及孔隙体积、传导系数、有效地层系数和表皮系数等7个影响聚驱效果的主要特征参数;在对这些参数开展较为详细的敏感性分析基础上,以多种现场实测资料作为约束条件,建立了一套较为系统、有效的多参数约束聚合物驱历史拟合方法。大庆某典型实际区块油藏数值模拟表明,聚合物驱历史拟合精度明显提高,单井含水拟合符合率达到75%。研究结果证明了该聚合物驱历史拟合方法的可行性和有效性。图4表1参13     

油藏数值模拟自动历史拟合方法——以Nelson油田为例

针对北海中部Nelson油田,研究油藏数值模拟自动历史拟合方法。完整的油藏自动历史拟合工作流程包括选择要调整的油藏变量、选择参数调整方法、自动历史拟合、数据分析、组合最优结果得到最优的油藏模型集5个步骤。以净毛比、水平渗透率、垂直渗透率为调整参数,采用全局单变量法、区域多变量法、局部多变量法等3种油藏参数调整方法,并结合生产数据和时移地震数据,对Nelson油田进行自动历史拟合。结果表明,局部参数调整方法减少了模拟中模型的数目和计算时间,提高了模拟精度,使得油藏中油水产量拟合误差大大降低,在Nelson油田应用效果最好。全局单变量法适合于历史拟合参数相互独立的情况;对于井网密度大且井间关联性强、历史拟合参数相互影响的油藏,最好选用区域多变量法进行参数调整;对于油藏历史拟合参数相互影响但每个选定调整区域相互独立的油藏,局部多变量法更加适用。