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。     

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.     

利用遗传算法推断地层渗透率分布

对于求解数百个未知渗透率的组合优化问题，用人工操作的历史拟合技术和一般的优化算法是不可行的。近些年形成的遗传算法具有全局收敛性，是一种不同梯度信息的优化方法，特别适用于大型的组合优化问题。本文利用遗传算法进行历史拟合推断渗透率分布获得了成功，简化了历史拟合过程。     

利用广义拉格朗日方法进行有效的历史拟合和最优化生产

介绍了油藏历史拟合及油藏动态注水最优化问题的一种新方法.对于动态注水最优化的问题,解出了使净现值达到最大值时有限制条件的油藏渗流方程的最优解.同样,在历史拟合时,我们通过测量压力和饱和度得到油田的渗透率.两种情况的问题是把找到的与之相关的广义拉格朗日函数的鞍点用公式表示.基于伴随矩阵方程的解,我们把一系列传统的最优控制方法与该方法进行了对比.在例子中使用同样或者少于伴随矩阵的计算量来测验该方法得到近似的结果.新方法的一个优点是不用在每次迭代时都求解渗流方程的精确解.作为最优化收益,渗流方程应该在收敛点处有效.因此,新方法最小值算法的每一次迭代成本均低于伴随矩阵方法.     

油藏数值模拟历史拟合分析方法

油藏数值模拟历史拟合是为了验证和修正数值模拟模型,从而提高数值模拟模型的可靠性以及油田开发指标预测的准确性。目前常用的历史拟合方法缺乏系统性和规范性,从而导致了数值模拟模型的修正具有一定的随机性和随意性。在数值模拟模型建立和初始化检查的基础上,提出了一套系统的历史拟合分析方法。从分析拟合现象入手,根据拟合曲线的形态,将动、静态拟合矛盾分为5种类型,同时指出了3个关键拟合点;然后针对不同类型的拟合矛盾,进行拟合指标的影响因素分析,列出造成拟合矛盾的可能原因;再结合实际区块的动、静态资料及认识,分析数值模拟模型的不确定性,采用排除法,快速找出造成拟合矛盾的具体原因,反复修正数值模拟模型,直到满足历史拟合的精度要求。实例应用结果表明,使用该方法极大地减少了油藏数值模拟的次数,提高了历史拟合的效率和精度,也证明了该方法的实用性和有效性。     

计算机辅助自动历史拟合在油藏数值模拟中的应用

油藏数值模拟的历史拟合既复杂又费时、费力，而且多解。通过对计算机辅助历史拟合技术进行研究，给出了一种较为实用可靠的实现方案：①利用商业化的黑油模型计算结果，构造历史拟合目标函数（也适用于其它模拟器）；②采用Levenberg-Marquardt优化算法求解极小化目标函数，并根据牛顿法、最速下降法、Levenberg-Marquardt算法各自的特点进行灵活的算法切换，提高收敛性和收敛速度；③利用协方差矩阵和均方根梯度，进行参数的不确定度和敏感性分析。数值模拟试验表明，设计的计算机辅助历史拟合方法可行、可靠，能够大大减少人工历史拟合的盲目性和所花费的机时。     

历史拟合的方法原理及其应用

本文以双重介质为例,给出了进行历史拟合的方法和原理,并结合实例讨论了历史拟合在试井分析中的几点应用.同时指出历史拟合是进行早期试井分析唯一有效的诊断工具.     

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.     

油藏数值模拟自动历史拟合方法研究及应用

油藏数值模拟的历史拟合过程中模型参数多、可调整自由度大，目前普遍采用实验校正法进行拟合，主观随意性大且费时多。引入最优化理论建立目标函数，以渗流方程和油藏的边界条件、初始条件为约束条件，将历史拟合转化为非线性规划中求解定义在n维空间的函数极值问题，用改进的共轭梯度法求解，基本解决了收敛问题。拟合过程中调整参数的原则为：不确定优先，敏感优先，先全局后个别，为减少调整参数，用解析函数表达相对渗透率与饱和度的关系，将模拟区域按油藏地质和井网条件划分为若干小区，分区拟合。对某封闭小断块油藏的区块与单井综合含水和地层压力进行自动历史拟合，调整的主要参数是相对渗透率和渗透率，计算了126次，拟合结果与实际动态相符。     

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.     

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.     

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.     

Bayesian Network—A New Probabilistic Method for Petroleum Reservoir Production Prediction and History Matching

Abstract

Most reservoir volume rock properties are stated with some degree of error. The main source of this error can be traced to the estimating procedure of the rock properties throughout the reservoir volume. The main effect of those errors is a resulting uncertainty that will be associated with all reservoir characterization-related works. To treat this uncertainty, we will use a Bayesian network as a new probabilistic reasoning tool in reservoir production prediction and history matching procedures.     

低渗透储层油水相对渗透率最优目标函数处理方法

对于非均质和亲水性强的低渗透岩心,使用常规JBN方法整理非稳态实验数据得到的相对渗透率曲线,存在因计算失效导致的水相相对渗透率曲线出现"驼峰"等异常现象.除了岩样的非均质性、出口端提前见水、驱替速度不合适以及难以测定油水黏度比等实验因素,利用JBN等常规方法处理非稳态水驱油实验资料的局限性是产生相对渗透率曲线异常形态的...     

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。     

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.     

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。     

提高油藏数值模拟历史拟合精度的方法

油藏数值模拟中,通常应用达西定律根据地层系数对流量进行劈分,未考虑低渗透层启动压力梯度的影响,因而其劈分的小层流量与实际生产情况不符,导致历史拟合精度较低.注入、产出剖面是确定小层流量的最佳资料,利用注入、产出剖面测井资料进行小层硫量劈分,拟合效果理应有所改善.给出了利用注入、产出剖面进行流量劈分的方法,对于没有生产测井资料的井,可根据启动压力梯度与渗透率的相关关系采用考虑启动压力的流量劈分模型.以大庆油田杏十～十一区试验区块为例,将注入、产出剖面测井资料及考虑启动压力的流量劈分模型用于油藏数值模拟,历史拟合精度明显提高,区块综合含水符合率提高约7%,单井含水符合率提高约10%.图5表2参15