聚合物驱多参数数值模拟自动历史拟合方法

为了解决聚合物驱历史拟合涉及参数多、工作量大、花费时间较长等问题,从聚合物驱数值模拟基本原理出发,在多参数历史拟合影响因素研究的基础上选用应用较为广泛的ENKF方法进行聚合物驱自动历史拟合方法的探索研究,并针对聚合物驱历史拟合参数非线性特征进行改进,采用ESMDA方法研制了自动历史拟合软件,且对实际区块进行了聚合物驱历史拟合。研究结果表明聚合物驱多参数数学模型可以较好地反映油藏中聚合物驱替的基本规律,通过综合调整聚合物的吸附量、黏浓关系、残余阻力系数、不可及孔隙体积等参数,模拟结果与油藏实际动态相符,达到历史拟合的目的。所建立的自动历史拟合的数学模型满足方法要求,所研制的自动历史拟合软件可以降低模型计算结果系统误差。实际测试结果表明：全区含水趋势基本符合历史动态,累积产油量误差为3.8%,单井拟合结果较好,单井拟合符合率为81.2%,满足聚合物驱历史拟合要求。     

数值模拟辅助历史拟合新方法研究及应用

数值模拟历史拟合是数值模拟研究中非常重要的一部分,是不同开发方案或调整方案对比优选、油气产量预测的基础。目前历史拟合工作主要采用传统的人工反复试算方法,既复杂又费时费力,存在多解性。为了提高数值模拟拟合精度及工作效率,通过对计算机辅助历史拟合技术方法进行研究,以Eclipse为模拟器,以集合卡尔曼滤波方法为技术基础,从模型输入数据文件自动获取数据,将敏感性参数作为被估参数,确立目标函数,利用最优化方法实现自动修正可调参数,自主研发了数值模拟自动辅助历史拟合软件。实例应用表明,通过自主研发的辅助历史拟合软件实现了多模型自动历史拟合,采用最优化算法筛选出最优拟合模型,节省了大量人工拟合时间,提高了拟合精度及工作效率。提出的数值模拟辅助历史拟合方法可行可靠,取得了良好的应用效果。     

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。     

基于EnKF的致密气藏离散裂缝模型自动历史拟合

近年来，离散裂缝模型是描述裂缝水淹的常用模拟模型，但由于涉及的地质和流体参数较多，手动修改参数工作量大、效率低，而自动化历史拟合是提高离散裂缝模型拟合精度的有效方法。以四川须家河组致密气藏为例，建立了基于集合卡尔曼滤波(Ensemble Kalman Filter, EnKF)的致密气藏离散裂缝模型自动历史拟合方法。将裂缝划分为大、中、小三个级别，大裂缝采用离散裂缝模型，中、小裂缝采用等效介质模型，运用EnKF方法对须家河组X2区块气水生产数据进行了历史拟合，通过自动调整各砂组水体能量和生产井周围孔渗使得生产井的整体拟合符合率达到86%。基于EnKF的离散裂缝自动历史拟合方法为裂缝性致密气藏数值模拟提供了有效借鉴。     

运用自动历史拟合技术反求地层参数

本文建立了一个带约束条件的非线性目标函数,运用最优化方法使目标函数达到最小,实现自动历史拟合,从而反求得各地层多参数值,并运用作者编制的计算机软件对现场测试资料进行了自动历史拟合计算,求得了各自的地层参数值,此外,对三种不同的优化方法进行了对比,并将本文求得的地层参数值与美国SSI软件解释结果及电测解释结果进行了对比,证实了本文软件求解结果的可靠性.     

油藏自动历史拟合方法研究现状与展望

油藏自动历史拟合的目标是通过优化算法自动匹配各井的开发指标,使数值化的油藏模型(如饱和度和压力分布)符合各个开发时期实际的油藏状态,从而保证油藏数值模拟再现油田开发全过程的正确性,并在此基础上预测将来的开发方案.相对于常规人工拟合,油藏自动历史拟合避免了研究人员生产拟合时的随意性和盲目性,大大减少了工作量.系统地介绍了目前中外自动历史拟合方法的研究现状和进展,总结归纳了确定性、随机性和混合3类优化方法,详细说明了常用算法各自的特点及应用范围,探讨了目前研究存在的不足,最后提出了拟合方法下一步的工作重点和研究方向.     

利用数值模拟反演聚合物驱物理实验的方法

历史拟合是油藏数值模拟技术的重要组成部分,但历史拟合的过程是一个复杂而艰难的过程,尤其是聚合物驱历史拟合。本文提出了一套数值模拟反演方法,其为在进行历史拟合之前先对聚合物驱物理实验进行数值模拟反演,分析聚合物驱的主要影响因素,对后期的历史拟合过程具有很好的指导意义。用该方法对JZ9—3油田胶结岩心实验反演的结果表明,拟合效果较好,再现了物理实验的过程。     

大规模角点网格计算机辅助油藏模拟历史拟合方法研究

开展了大规模角点网格地质建模和油藏数值模拟应用研究,并研制了角点网格完井射孔层位辅助软件工具,解决了地质模型和数值模拟模型之间的衔接问题。提出了一种计算机辅助历史拟合方法,该方法采用油藏数值模拟自动历史拟合的数学模型。利用油藏数值模拟的成熟技术和专家知识,研制了历史拟合影响因素分析和计算机辅助优化拟合软件,根据主控因素,分3个层次,将历史拟合由初步拟合到精细拟合,提高了高含水油田剩余油分布预测数值模拟研究的可靠性和计算效率。该方法应用于苏丹Greater Unity油田的开发调整,取得了很好的效果。     

海上注聚油田历史拟合方法

本文对海上典型油田(锦州9—3油田)的调驱进行历史拟合,形成实用的调驱数值模拟方法。通过研究,形成了前期水驱历史拟合方法、聚合物驱拟合方法、凝胶历史拟合方法,为相似油田的跟踪模拟提供技术支持。     

计算机辅助历史拟合技术构想

从大庆油田开发调整和挖潜需要出发,阐述了计算机辅助历史拟合研究的必要性,并对目前国内外先进的辅助历史拟合软件进行调研,用实际模拟区块实例对国外先进的辅助历史拟合软件的功能进行了消化吸收,探索出了适合大庆油田的计算机辅助历史拟合方法.以此为基础,研究、优选出适合辅助历史拟合问题的高效算法,提出了自主计算机辅助历史拟合技术软件的架构设计、功能及实现技术路线的构想.目前已经用一个简单的JAVA跨平台通讯监控方案可行性验证代码实现了Windows对Linux之间与PBRS模拟软件的数据通讯以及实时监控,说明该构想可行,对提高历史拟合的工作效率,解决制约多学科油藏研究的瓶颈问题具有重要的意义.     

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...     

A framework to integrate history matching and geostatistical modeling using genetic algorithm and direct search methods

History matching is an inverse problem where the reservoir model is modified in order to reproduce field observed data. Traditional history matching processes are executed separately from the geological and geostatistical modeling stage due to the complexity of each area. Changes made directly on the reservoir properties generally yield inconsistent geological models. This work presents a framework to integrate geostatistical modeling and history matching process, where geostatistical images are treated as matching parameters. The traditional optimization methods normally applied in history matching generally use gradient information. The treatment of geostatistical images as matching parameters is difficult for these methods due to the strong non-linearities in the solution space. Therefore, another objective of this work is to investigate the application of two optimization methods: genetic algorithm and direct search method in the proposed framework. In order to accelerate the optimization process, two additional techniques are used: upscaling and distributed computing. Results are presented showing the viability of the genetic algorithm in the type of problem addressed in this work and also that direct search method can be used with some restriction. Finally, the benefits of distributed computing and the consistence of the upscaling process are shown.     

Influence of the objective function in the history matching process

An assisted history matching process always requires two distinct parts: a parameterization to select the uncertain attributes of the model and an automatic procedure that minimizes the distance between the observed production and the simulation model curves. The focus of this work is the second part, where an objective function is necessary to represent mathematically the quality of the model. However, due to the complexity of the models, this function is frequently a combination of several functions that represent the quality of the match in several wells and less attention is given to the influence of the objective function in the optimization process. This paper proposes a study to show the influence of a global objective function on the history matching process using a synthetic reservoir model with 20 uncertain attributes. Results of the quality matching index of eight different global objective functions are compared at the end of the process. The optimized simulation models, generated by the optimization phase with different global objective functions, are compared with the base model and production history.     

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.     

A review of closed-loop reservoir management

The closed-loop reservoir management technique enables a dynamic and real-time optimal production schedule under the existing reservoir conditions to be achieved by adjusting the injection and production strategies. This is one of the most effective ways to exploit limited oil reserves more economically and efficiently. There are two steps in closed-loop reservoir management: automatic history matching and reservoir production optimization. Both of the steps are large-scale complicated optimization problems. This paper gives a general review of the two basic techniques in closed-loop reservoir management; summarizes the applications of gradient-based algorithms, gradient-free algorithms, and artificial intelligence algorithms; analyzes the characteristics and application conditions of these optimization methods; and finally discusses the emphases and directions of future research on both automatic history matching and reservoir production optimization.     

基于地层一致性检验的测井信号地层自动对比算法

本文根据专家经验，利用地层一致性概念对测井信号进行综合分析，研制了一个较实用的测井信号地层自动对比系统，在测井信号对比过程中将局部的相似性和综合的匹配对比有机地结合起来。在地层对比方面，尤其是在正断层识别和断层情况下的地层划分方面有较好的分析结果，从而使得该系统在实践中取得了良好的应用效果。     

基于井间连通性的碳酸盐岩油藏注采关系优化

碳酸盐岩油藏储集层非均质性强,注水开发时注入水易沿高渗通道窜进,导致生产井发生水窜或水淹、含水率上升速度加快、开发效率低。基于井间连通性原理,根据缝洞型碳酸盐岩油藏的地质特征、开发动态等,可定量表征井间的连通性参数传导率和连通体积,构建碳酸盐岩纵向多层油藏井间连通性模型,进而获取油藏各层注水井平面注水劈分系数、注水利用率等。结合自动历史拟合方法和生产优化算法,实现对油水井生产动态的实时优化和预测。现场应用表明,该方法年增油1.1×10⁴ m³,具有较好的增油效果,对同类型油藏的高效开发有重要指导意义。     

油藏动态自动历史拟合的发展与现状

本文论述油藏自动历史拟合发展过程、主要途径及有关概念,提出多参数自适应历史拟合序贯搜索法,并在SUN工作站上开发计算机程序.文末附有软件运行实例.     

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。