智能油田(中英文)-5(核心部分).docx

I-Field Surveillance Layer Development一号油田监测层的发展Qatif & Haradh Increment-III (Al-Arnaout 2007; Saleri 2006) intelligent field implementation served as a pilot and testing ground for defining, developing and implementing the surveillance layer building components through: Mapping the data flow path from the fields to the desktop Exploiting the interfacing and integration of intelligent field technologies Defining I-Field data acquisition & delivery requirement (data, applications, processes and systems) Assessing existing data acquisition and delivery implementation Assessing existing processes, operations and implementation challenges Defining user requirements (data types, frequency, resolution, support) Defining surveillance required tools & applications盖提夫和哈拉德增量三号（Al-Arnaout 2007; Saleri 2006）智能油田被用作一个试验测试地区来来定义、开发并启用监测层。主要通过：现场的数据流传到办公室利用智能油田技术的接口和集成定义一号油田的数据采集和传输要求(数据、应用程序、流程和系统)评估现有的数据采集和传输实施状况评估现有流程、操作和实施中的挑战定义用户需求(数据类型、频率、分辨率、支持率)定义监视所需的工具和应用程序Surveillance Development Approach监测层的开发方法To develop the “Surveillance Layer”, the I-Field core team was organized into six sub teams to execute each of the corresponding six surveillance layer components. A team Leader and a team leader backup from the core I-Field team were assigned to each execution team. Each execution team was staffed with component area element domain experts representing all concerned organizations from both I-Field and non I-Field team members. Assigned I-Field core team members identified and nominated required expertise from their corresponding organizations. Ownership of each of the surveillance layer components elements are kept with the concerned support organization to ensure on going development, maintenance and support.Rounds of facilitation were conducted with each team to define their area of focus objectives, avoid duplication of efforts and develop short term and long term plans.为了开发“监测层”，一号油田的核心团队被组织成六个子团队来执行相应的六个监测层组。一号油田核心团队的团队领导和团队领导备份被分配到每一个执行团队。每个执行团队配备了各个部分的领域专家，他们代表了一号油田和非一号油田所有的相关组织。分配的核心团队成员由他们相应的组织里的行业专家审核、提名。每个监测层组的所有权由相关支持组织控制，以确保继续发展、维护与支持。每个小队跟着引导来划分他们的重点目标区域，从而避免重复工作，并制定短期和长期计划。Data Acquisition & Delivery Layer数据采集和传输层Qatif and Haradh Increment III projects were instrumental in solidifying the I-Field data acquisition and delivery requirement for Reservoir Management and Production Engineering. The requirement specified the data availability, delivery level and the data types with their associated acquisition frequency and resolution. Additionally, the projects also revealed limitations and challenges in the existing data acquisition and delivery infrastructure and the need for developing an I-Field data acquisition and delivery infrastructure architecture. Thus the I-Field Data Acquisition & Delivery execution team was chartered with the following objectives: Define and document the I-Field data acquisition and delivery requirement Define and document existing fields to regional and corporate database data acquisition and delivery infrastructure and support structure Assess current state of Qatif and Haradh Increment III fields data acquisition and delivery infrastructure and support structure Define an I-Field data acquisition and delivery infrastructure architecture leveraging existing infrastructure investments for upgrading existing fields. Incorporate I-Field architecture, specifications and guidelines into existing company fields engineering standards Continually explore and evaluate available and emerging data acquisition and delivery industry solution to enhance and optimize developed architecture for use in future fields to enhance/maintain exiting fields architecture Perform gap analysis on Haradh and Qatif fields data acquisition and delivery infrastructure against developed architecture Develop scope of work for implementing required upgrade to Qatif and Haradh Increment III fields Define and develop data acquisition and delivery data flow monitoring tools Define and develop KPIs for monitoring the performance of data acquisition and delivery process Develop a road map and execution plan to role out the implementation of the I-Field data acquisition and delivery architecture in all of Saudi Aramco fields对油藏管理和生产工程而言，盖提夫和哈拉德增量三号项目有助于巩固一号油田数据采集和传输要求。该要求划定了数据的有效性，传输水平以及它们相关的采集频率和分辨率的数据类型。此外，该项目还透露出在现有数据采集和传输的基础设施中的限制和挑战，以及开发一个一号油田数据采集和传输基础设施的需要。因此，一号油田数据采集和传输执行队伍被特许设定一下目标：定义并记录一号油田的数据采集和传输要求；定义和记录当下油田到区域、企业的数据库数据采集和传输的基础设施以及支撑结构；评估盖提夫和哈拉德增量三号油田的数据采集和和传输基础设施以及支撑结构的现状；定义一号油田数据采集和传输基础设施的架构，该构架利用现有的基础设施投资来升级目前的区域；将一号油田的结构，规范和准则整合为目前公司油田的工程标准；不断探索和评估有用、新兴的数据采集和传输的行业解决方案，为今后的油田提升和优化目前发展的架构，同时增强和维持目前油田的架构；对哈拉德和盖提夫油田数据采集和传输的基础设施执行差距分析来代替当下已经发展的架构；为盖提夫和哈拉德增量三号油田升级所要求的措施制定工作范围； 定义并制定数据采集和数据流传输的监控工具；为数据采集和传输过程的性能监测定义并制定关键绩效指标；制定一个路线图和执行计划，来实现一号油田数据采集和传输的构架在沙特阿拉伯国家石油公司的所有油田得以实施。Tag Naming Standard & Configuration Management标签命名标准和配置管理In the field, instrumentation and equipment data are referenced or named by their associated tag numbers. The tag numbering follows Saudi Aramco Engineering Standard called Instrumentation Symbols and Identification SAES-J004. This standard is used for the purpose of having a uniform means of designating instrumentation symbols and identification standards used in Saudi Aramco.Field data acquisition and delivery in Saudi Aramco traverses multiple stages of PI Servers before it reaches the corporate database. The first level is the field level, then the area or regional level and last is the central level. At every stage a local standard was applied to name and configure PI tags. Different coding convention was appended to the tags at the various levels, and each organization had its own convention. As a result, different names were used for the same data point at various stages of data collection in PI servers. Figure 3 shows the data path from one field to the corporate database. Furthermore, a configuration management procedure was needed to ensure that required I-Field data are configured in the I-Field real time database. The objectives of the Tag Naming Standard component are: Develop an I-Field unified tag naming standard to be used in all PI systems across Saudi Aramco Integrate the unified tag naming standard into an existing implementation process for use in new fields and new fields development activities Develop a tag configuration management process for the tag names The team developed Tag Naming Standardization and Configuration Management Guidelines. The guidelines are an extension of Saudi Aramco Engineering Standard Instrumentation Symbols and Identification document SAES-J-004. The I-Field Tags Standardization Guidelines are purely for “Data” tag names on the PI servers and are not for use on the physical device tags.在现场，仪器仪表和设备数据根据其相关的标签号来引用或命名。标签编号按照沙特阿拉伯国家石油公司工程标准被称为仪表符号和标识SAES-J004。该标准用于为沙特阿拉伯国家石油公司使用的仪表符号和鉴定标准制定统一的方法。在沙特阿拉伯国家石油公司，现场数据采集和传输需要穿越PI服务器的多个阶段才能到达企业数据库。第一个层次是油田层次，然后是地区或区域层，最后是企业层。在每个阶段应用地方标准来命名和配置PI标签。在不同的层次中不同的编码惯例附在标签上，每个组织都有自己的惯例。其结果是，不同阶段在PI服务器上采集数据时对于相同的数据点采用不同的名称。图3显示了从一个油田到企业数据库的数据路径。此外，还需要一个配置管理程序，已确保所要求的一号油田数据配置在一号油田的实时数据库。标签命名标准的目标是：开发一套一号油田统一的标签命名标准，用于沙特阿拉伯国家石油公司的所有PI系统；在新油田和新油田的的开发活动中，使用统一的标签命名标准；为标签名称制定一个标签配置管理流程；该团队将标签命名标准化并制定了配置管理准则。该准则是沙特阿美公司工程标准仪器仪表符号和识别文档SAES-J-004的扩展。在一号油田标识标准化指南纯粹是为PI服务器上的“数据”标签命名，而不是在物理设备标签中使用。Data Compression, Filtration and Aggregation数据压缩、筛选和整合Automated reservoir surveillance requires the collection of engineering data in very small units of time, sometimes as low as every second. As a result, tens of thousands of bits of data can be collected every hour. There is therefore a need to reduce the size of this data for efficient storage and utilization.The current practice in Saudi Aramco is to compress all data types, based on certain pre-determined criteria, prior to storage in the PI-Server. This process can reduce the data storage requirements by up to 70 percent in some cases. For some applications, such as pressure transient analysis, which requires high frequency data, especially during the early part of the test, this data compression can be very detrimental, and often renders the data useless. Thus, the method used in the data reduction must take into account the end use and purpose of each data stream.To address these concerns, a Data Compression, Filtration and Aggregation execution team was formed to accomplish the following:自动化油藏监测要求在非常小的时间单位内收集工程数据，有时低至每秒。导致每小时可以收集成千上万的数据。因此，为了有效的存储和利用有必要减少这种数据的大小。在沙特阿拉伯国家石油公司目前的做法是，根据一定的预先确定的标准，在存储PI-服务器之前，将所有数据类型压缩。在某些情况下，这个过程可以降低数据存储需求的70%。对于某些应用，诸如压力瞬态分析，需要高频率的数据，特别是在测试的早期阶段，数据压缩是非常有害的，并经常呈现出无用的数据。因此，在数据减少所使用的方法中必须考虑每个数据流的最终用途和目的。为了解决这些问题，组建了一个数据压缩、筛选、整合的执行团队来完成以下目标： Review current practices and develop an I-Field Data Compression, Filtration and Aggregation Guidelines that address the acquisition, sampling, storage and filtration of this high frequency data, in a form that will make it useful for reservoir and production engineering applications. Scout for or develop a solution for data cleanup, including noise and outlier removal, as well as data filtration or reduction prior to use by the engineer in reservoir and production applicationsFollowing several meetings and discussions, during which several domain knowledge experts were invited to share their knowledge and insight with the team members, the team came up with guidelines regarding all data types being recorded and their respective sampling frequencies. The team recommended the use of an application that employs a wavelet algorithm for data cleanup, or reduction prior. The team successfully evaluated an off-the-shelf software package that employs a wavelet algorithm which can be applied at PI server and/or database level. Figure 4, illustrates the results of the wavelet application in reducing the volume of the data without sacrificing the underlying information.审查当前的实践，开发一套一号油田数据压缩、筛选、整合的指导方针,用来解决高频数据的采集、采样、存储和筛选，使其能够用于储层和生产工程应用；为数据清理寻找或开发一个解决方案，包括噪声和离群值的删除,以及在工程师对储层和生产应用数据应用之前，对数据的筛选和减少。经过了几次会议和讨论，在此期间，一些领域专家应邀与团队成员分享他们的知识和见解，针对所有记录的数据类型和各自的采样频率，团队提出了相关的指导方针。该小组建议采用小波算法，该应用可对数据进行清理或减少。团队成功评估了一个现成软件包，该软件包采用小波算法，可在PI服务器和或数据库层次应用。图4展示了在不牺牲底层信息的情况下小波减少数据量的应用结果。Real Time Data Management Layer实时数据管理层The objective of the Real Time Data Management layer is to provide real-time database of high availability and assured quality and develop tools and applications that support the development, enhancement and maintenance of real time data management. The objectives of this layer include: Develop real-time database model and create real time database Establish real-time database security and accessibility rules Configure and connect the database to receive the data from the PI server Develop real-time data monitoring and QC tools Integrate the real-time database model with other existing data models Develop equipment/sensor installation inventory system Develop database performance monitoring system Develop real-time database capacity planning tool Most of these objectives are being met and work is in progress to further the development of this components.实时数据管理层的目的是提供可用性高、质量可靠的实时数据库，开发一套应用工具能够支持实时数据管理的发展、加强和维护。该层的目标包括：开发实时数据库模型和创建实时数据库；建立实时数据库的安全和访问规则；配置和连接数据库来从PI服务器接收数据；开发实时数据监控和质量控制工具；集成实时数据库模型和其他现有的数据模型；开发设备、传感器的安装目录系统；开发数据库性能监测系统；开发实时数据库容量规划工具。这些目标大部分已经实现，这些部分的未来开发工作还正在进行。Visualization Layer可视化层The objective of this component is to address all I-Field visualization requirements:该部分的目标是解决一号油田的所有可视化要求1. Basic Visualization and Alerting Tools1. 本的可视化和提醒工具To provide basic visualization environment capable of monitoring all aspects of the objective function related to the assets (i.e., a well, a field, an operation and the entire asset) in real time to ensure that performance is being met by providing the required alerts, basic trending and analysis tools. This objective was accomplished by the following: Documenting Reservoir Management and Production Engineering basic visualization and alerting requirement Carrying out evaluation on several visualization tools Acquiring and customizing basic visualization & alerting software Devising Key Performance Indicators (KPIs) responsible for tracking and evaluating trends on important parameters提供一个基本可视化环境，能够实时监控与资产（即一口，一个油田，一次操作和整个资产）相关的各个方面，通过提供所需的警报、基本趋势和分析工具来满足性能。这个目标通过以下来完成：记录油藏惯例和生产工程的基本可视化和报警需求；对几个可视化工具进行评估；购买和定制了基本的可视化和报警软件要设计关键绩效指标，负责对重要参数的趋势进行跟踪与评估2. Collaboration Center(s)2. 合作中心To develop collaboration environment that facilitates the integration of people, process and technology with focus on high value reservoir management workflows. As the I-Field implementation unfold, petroleum engineers will be dealing with more and more actionable overall field and reservoir data that require integration, visualization and collaboration between multidisciplinary teams for optimal assessment and decision making. Thus, there is a need for the development and implementation of new business environment that is specifically designed to accommodate current and future reservoir management business processes.Currently work is in progress on developing and implementing two I-Field collaboration centers. The first center is expected to be on-line by en