中英文对照外文翻译文献(文档含英文原文和中文翻译)译文：利用云技术和服务的新兴前沿：资产优化利用摘要投资回报最大化是一个主要的焦点对所有公司。

信息被视为手段这样做。

此信息是用来跟踪性能和提高财务业绩主要通过优化利用公司资产。

能力和速度，这是可能的收集信息并将其分发到当前的技术该组织正在不断增加，事实上，有超过了行业的能力，接受和利用它。

今天，生产运营商被淹没在数据的结果一种改进的监控资产的能力。

智能电机保护和智能仪器和条件监控系统经常提供32多块每个设备的信息都与相关的报警。

通常运营商没有装备来理解或行动在这个信息。

生产企业需要充分利用标的物专门为这个目的，通过定位他们的工程人员区域中心。

这些工程师需要配备足够的知识能够理解和接受适当的行动来处理警报和警报通过这些智能设备。

可用的信息可以是有用的，在寻找方法增加生产，减少计划外的维护和最终减少停机时间。

然而，寻找信息在实时，或在实时获得有用的信息，而不花了显着的非生产时间，使数据有用的是一个巨大的挑战。

本文将介绍云技术作为一种获取可视化和报告的经济方法条件为基础的数据。

然后，它将讨论使用云技术，使工程资源与现场数据可通过网络浏览器访问的安全格式技术。

我们将覆盖资产的方法多个云服务的优化和效益飞行员和项目。

当重工业公司在全球范围看，世界级运营实现整体设备效率（OEE）得分百分之91。

从历史上看，石油和天然气行业的滞后，这得分十分以上（Aberdeen 集团“操作风险管理”十月2011）。

OEE是质量的商，可用性和效率得分。

这些，可用性似乎影响了石油和天然气行业的最大程度。

在石油和天然气的可用性得分的根源更深的研究导致旋转资产作为故障的根本原因，在70%的情况下，失去的生产或计划外停机。

鉴于这一行业的关键资产失败的斗争，但有方法，以帮助推动有效性得分较高，以实现经营效率的目标。

.在未来十年中，海上石油储量的追求将涉及复杂的提取方法和海底提取技术的广泛使用。

提取下一波的储量将需要复杂的设施，在海底，以及更传统的表面生产设施的形式。

面对日益复杂的生产系统，石油和天然气经营公司正在努力成功地经营这些复杂的设施与一个退休池的主题专业知识。

该行业的答复，这一现象是显着的使用智能设备组织的斗争，把数据转换成过程控制系统，成本很高，然后向工程师提出所有的数据，每一次发生的事件。

工程师然后花时间挖掘数据，建立数据表和创建有用的信息，从桩。

由此他们可以开始工作的问题或问题。

不幸的是，这项工作需要的经验，资产和数据。

更换行业和组织的知识是一个挑战，推动生产企业探索定位主题的专业知识，在资源的枢纽，跨多个资产。

挑战来自于2个方面。

首先，生产系统，无论是在表面上，在海底，需要复杂的生产系统和子系统的许多组件。

其结果是，操作这些设施的自动化系统是非常复杂的，往往需要运营商与200000多个标签的数据和由此产生的报警接口。

其次，将标的物专家在区域枢纽创建的安全风险，必须解决的设计自动化系统。

启用24小时的实时数据访问远程定位的主题的专业知识，需要建立在互联网技术的隧道，使监控从远程办公室，平板电脑和移动设备。

一个健全的安全策略是需要这种支持的一部分。

传统的方法继续影响停机时间。

简而言之，如果工程或维护需要建立一个电子表格，查找数据，操纵它，然后通过它来查找真相，在采取行动时损失的时间会导致停机时间的增加。

基于角色的可视化和报告，与非生产性工作的自动化配对，创造一个环境，推动合作和提高性能。

改进的风险为基础的方法，以尽量减少资产故障是一个可能的答案，以推动资产性能。

它不是完整的，除非系统的地方，使总有效率的维护，每个人在企业中扮演着一个维护的一部分，因为每个装备。

实施全面生产性维护开始与授权的集中式主题的专业知识与现场数据，并给他们的手段，以配合实时操作和维护人员。

它包括提供每一个人的工作与资产的确切信息所需的时间所需的作用，以保持资产健康。

高级维修和设施工程人员是最佳的位置，利用数据的基础上，结合历史的情况下，以推动可靠性提高资产。

协作工具驱动共享这反过来又创造了一个环境，经验不足的员工获得从老员工更好的装备的年轻工程师的知识，操作和维修人员的优化与资产为退休工人。

这种组合的数据利用率，资产性能管理和知识共享导致通过全面的经营绩效管理的优化资产。

经营绩效管理的路径是时间和速度。

创建协作区和分析和工作流程自动化系统，可以涉及重大投资。

资源来执行的系统往往是稀缺的，导致在建设的系统，将使一个企业的经营业绩管理的操作障碍。

今天，技术的存在，使工作流自动化和协作使用简单的网络工具。

简单的浏览器访问允许使用智能手机，平板电脑和个人电脑的人员合作。

问题是，企业在他们的防火墙内构建技术，还是利用云计算技术来推动合作作为付费服务？答案需要一个更广泛的数据的使用和数据策略。

要实现可靠和效率指标，利用现有的数据，石油和天然气经营企业必须制定数据策略，解决了一些问题。

是数据所需的合作也受监管或投资者的期望？如果是这样的话，一个企业应该考虑在其企业结构中持有数据，并在基础设施投资，以存储和展示它。

资本预算和它的资源可以限制的能力，以实现所需的合作，建立系统的能力，具有挑战性的可靠性和效率目标的追求。

购买应用程序作为一个基于云的服务，可以加快与一个支付的路径，作为一个模型。

云技术提供了一种车辆来操作和管理数据。

采购软件作为一种服务，使一个组织能够通过更好地利用现有的数据，更快地进入运营卓越的领域。

采购业务管理工具作为一种服务，避免使用资本预算和专门规避资金跨资产问题。

服务是为他们所使用的经营预算。

利用云计算共享操作条件数据创建一个操作改进的环境。

“私有云”利用同样的技术可以部署，如果企业有考虑，需要所有的数据，以保持其企业内（法规遵从，投资者的遵守等）在开发策略，利用数据驱动的学科之间的合作，企业需要开发的数据策略。

一些数据，例如，安全记录，测试记录和记录和记录被调节，并为这些已授权存储。

其他类型的数据有投资者的合规性存储和安全要求。

在投资者或监管数据的情况下，企业仍然希望协同工具，但可能需要在其公司的结构中的数据，再看图5，协同工具和仪表板也可在传统的资本项目，购买软件和应用程序的开发经营范围内的企业数据结构。

本文的下一部分将解决传统的基础设施的方法和云计算方法，用于在一个组织中的有效性的例子。

云技术可以在标准的服务器体系结构中使用数据和操作的数据和自动化的非生产性的工作，利用数据。

虚拟机管理程序环境允许多个应用程序运行在数据中心的传统集群技术。

应用程序存在，允许数据的积累，从不同的来源与联邦，然后利用创建基于角色的可视化和自动化的手动任务（如生产分配，以及测试验证，监管系统测试文件等）。

图6演示了一个在操作公司的防火墙中使用云技术的测试验证。

图7然后演示了一个操作符的角色视图。

技术有助于显着减少非生产性的操作，同时提出的数据，在一种方式，推动人员集中的领域，他们可以影响业务，以提高效率。

图10和9显示了工作流自动化的一个实例，并将所得的仪表板呈现给含有丰富信息的人员，以帮助提高个人在资产上工作的有效性。

自动化系统既需要大量的资本投资，也需要持续的运营费用，以维持基础设施建设。

在许多情况下，合作是需要的，但确保投资是困难的，因为组织障碍，跨资产的资本项目或根本原因是不存在的资源。

利用云计算的基础，应用程序可以建立在云基础设施，并提供服务。

在这种方式的合作是可能的经营预算的限制，使用一个基金，建立模型。

在大多数情况下，所需的工具的成本效益的好处是显着低于传统的系统建设的成本。

下面的例子是一个达拉斯的抽水系统的制造商在泥浆处理系统和压裂系统，用于钻井的非常规的威尔斯将被用来说明。

我们会打电话给XYZ公司。

客户XYZ 送卡车进入现场，他们提供的服务，石油和天然气企业开发油气田的土地为基础的操作。

抽水系统具有高度的局部自动化，但泵操作人员不具备作出决定时，停止抽水和执行维护。

例如，卡车需要定期保养，一些过滤器需要更换，如每八个小时。

结合需要进行定期维护与客户寻找经营者的肩膀上，偶尔的错误是与阀门定位和/或运行的卡车，直到它打破了试图取悦一个焦虑的客户。

这大大的维护成本，停机时间是一个大问题。

英文原文：AN EMERGING FRONTIER, ASSETOPTIMIZATION UTILIZING CLOUDTECHNOLOGY AND SERVICESEric Fidler Sr. Member Richard and Paes Sr. MemberAbstract –Maximizing return on investment is a major focus for all corporations. Information is seen as the means by which to do so. This information is used to track performance and to improve the financial results primarily by optimizing the use of company assets. The ability and speed with which it is possible to gather information and distribute it with current technology to the organization is constantly increasing and, in fact, has surpassed the ability of industry to accept and utilize it. Today, production operators are overwhelmed with data as a result of an improved ability to monitor assets. Intelligent motor protection and intelligent instrumentation and condition monitoring systems often provide more than 32 pieces of information per device all with related alarms. Often operators are notequipped to understand or act on this information. Production companies need to leverage subject matter expertise for this purpose by locating their engineering staff in regional hubs. These engineers need to be equipped with sufficient knowledge to be able to interpret and take appropriate action to deal with warnings and alarms generated by these intelligent devices. The information available can be useful in finding ways to increase production, reduce unplanned maintenance and ultimately reduce down time. However, finding the information in real time, or getting useful information in real time without significant non-productive time spent making the data useful is a big challenge. This paper will introduce Cloud Technology as an economical method of gaining visualization and reporting to condition based data. It will then discuss the use of Cloud Technology to empower engineering resources with live data available in a secure format accessible through web browser technology. We shall cover the approach to asset optimization and the benefits found in several Cloud Services pilots and projects.INTRODUCTIONWhen heavy industry firms are viewed on a global basis, world class operations achieve an Overall Equipment Effectiveness (OEE) Score of 91 percent. Historically, the Oil and Gas industry lags this score by ten points or more (Aberdeen Group “Operational Risk Management”October 2011). OEE is the quotient of quality, availability and efficiency scores. Of these, availability seems to impact the Oil and Gas industry score to the greatest extent. A deeper look into root causes of availability scores in Oil and Gas leads to rotating assets as the root cause of failures in 70% of instances of lost production or unplanned downtime. Given this the industry struggles with failure of critical assets, but there are ways to help drive effectiveness scores higher in order to achieve operational efficiency objectives.Pursuit of offshore reserves in the next decade will involve complex extraction methods and extensive use of subsea extraction technologies.Extraction of the next wave of reserves will require complex facilities both on the ocean floor, as well as in the form of more traditional surface production facilities. Facing the growing complexity of production systems, oil and gas operating companies are struggling to successfully operate these complex facilities with a retiring pool of subject matter expertise.The industry’s reply to this phenomena is significant use of intelligent devices each delivering useful data. Intelligent breakers, protective relays, measurement relays, process instrumentation and condition monitoring systems to gather useful information. With sophisticated motor controllers such as adjustable speed drives (ASD) which have literally hundreds of parameters available to be monitored, it is easy to see that the amount of information which can be captured is staggering. In fact, managing and interpretation of this information database now becomes the issue. Organizations struggle to bring the data into process control systems at great cost and then present all of the data to engineers each time an event occurs. Engineers then spend time mining the data, building spreadsheets and creating useful information out of the pile. From this they can then start to work on the problem or problems. Unfortunately, this work requires experience with the asset and with the data.Replacing industry and organizational knowledge is a challenge driving production companies to explore locating subject matter expertise in hubs where resources are leveraged across several assets. The challenge comes about in two areas. First, the production systems – both on the surface and on the sea floor –require complex production systems and subsystems with many components. As a result, the automation systems that operate these facilities are extremely complex, often requiring operators to interface with more than 200,000 tags of data and resulting alarms.Second, placing subject matter experts in regional hubs creates security risks that must be addressed in the design of automation systems. Enabling 24-hourlive-data access for remotely located subject matter expertise requires establishing tunnels in internet technology to empower monitoring from remote offices, tablet PCs and mobile devices. A sound security strategy is required as a part of this enablement.OPERATIONS PERFORMANCE MANAGEMENT FOR IMPROVED RELIABILITYTraditional methods continue to impact downtime. In short, if engineering or maintenance has to build a spreadsheet, hunt down data, manipulate it, and then sort through it to find the truth, the time lost in taking action will lead to increased downtime. Role-based visualization and reporting, paired with the automation of non-productive work, creates an environment that drives collaboration and improves performance.Improved visibility with a risk based approach to minimize asset failure is a possible answer to drive asset performance. It is not complete unless the systems put in place empower Total Productive Maintenance where each person in the enterprise plays a part in maintenance as each is equipped to do. Implementing Total Productive Maintenance begins with empowering centralized subject matter expertise with live data and giving them the means to collaborate with operations and maintenance personnel in real time. It involves providing each individual working with the asset the exact information required for their role in the time required to keep the asset healthy. Senior maintenance and facilities engineering personnel are best positioned to utilize data –condition-based combined with historical –to drive reliability improvement in the asset. Collaboration tools drive the knowledge sharing that in turn create an environment where less experience employees gain from the knowledge of the older employees better equipping the younger engineers, operations and maintenance personnel to optimally engage with the asset as older workers retire. This combination of data utilization, asset performance management and knowledge sharing leads to anoptimized asset through total Operations Performance Management.The path to Operations Performance Management is one of time and pace. Creating collaborative zones and systems for analytics and work flow automation can involve significant IT investment. Resources to execute the systems are often scarce leading to barriers in building the systems that would enable an enterprise to move to Performance Management of operations. Today, technology exists to empower workflow automation and collaboration using simple Web tools. Simple browser access allows personnel collaboration using smart phones, tablet PCs and personal computers. The question is, does an enterprise build the technology within their firewalls or does it take advantage of cloud computing technology to drive collaboration as a paid service?The answer requires a broader view of data usage and data strategies. To achieve reliability and efficiency targets leveraging available data, Oil and Gas operating companies must develop data strategies that address a number of considerations. Is the data required for collaboration also governed by regulatory or investor expectations? If that is the case, an enterprise should likely consider holding the data within their corporate structure and investing in infrastructure to store and present it. Capital budgets and IT resources can limit the ability to build the systems required to achieve the desired collaboration –challenging the pursuit of reliability and efficiency targets. Purchasing the applications as a cloud- based service can speed up the path to collaboration with a pay-as-you-go model.Cloud technology provides a vehicle to manipulate and manage data. Purchasing software as a service enables an organization to move faster into the realm of operational excellence through better utilization of existing data. Purchasing operations management tools as a service avoids using capital budgets and specifically circumvents issues of funding across assets. Services are paid for as they are used with operating budgets. Utilizing cloudcomputing to share operating conditional data creates an environment for operational improvement. ‘Private clouds’leveraging the same technologies can be deployed if an enterprise has considerations that require all of the data to remain within their enterprise (regulatory compliance, investor compliance, etc.)In developing strategies that utilize data to drive collaboration between disciplines, an enterprise needs to develop a data strategy. Some of the data such as, safety records, testing records and flow records are regulated and as such have mandated storage. Other types of data have investor compliance storage and security requirements. In the case of investor or regulatory data an enterprise still desires collaborative tools but likely needs to hold the data within its company structure. Looking at Figure 5 again, collaborative tools and dash boarding are also available in traditional methods of a capital project, purchased software and application development operating within the enterprise data structures. The next two sections of this paper will address examples of a traditional infrastructure approach and a cloud computing approach used to drive effectiveness in an organization.Cloud technology enables the manipulation of data and automation of non-productive tasks within standard server architectures owned and operated by the enterprise utilizing the data. Hypervisor environments allow multiple applications to run on traditional cluster technology in data centers. Applications exist which permit the accumulation of data from disparate sources with federation then utilized to create role based visualization and automation of manual tasks (e.g. production allocation, well test verification, regulatory system testing documentation etc.). Figure 6 demonstrates a Well Test validation accomplished utilizing cloud technology within an operating company’s firewall. Figure 7 then demonstrates the role view for an operator resulting. Technology helps to significantly reduce non-productive operations while presenting the data in a way that drives personnel to focus on areaswhere they can impact the business to improve efficiencies. Figures 9 and 10 show an example of workflow automation and the resulting dashboard presented to personnel containing role-rich information designed to help improve the effectiveness of the individuals working on the asset. Automation systems can require both significant capital investments to build as well as ongoing operating expenses to maintain the infrastructure. In many cases, collaboration is desired, but securing the investment is difficult due to organizational barriers in funding capital projects across assets or simply because the resources do not exist.Leveraging cloud computing foundations, applications can be built within the cloud infrastructure and provided as a service. Collaborating in this fashion is possible within constraints of operating budgets using a fund-as-built model. In most cases, the cost of the tools required to gain efficiency benefits are significantly lower than the cost of building traditional systems.The following example of a Dallas-based manufacturer of pumping systems used in mud-handling systems and fracturing systems for drilling of non-conventional wells will be used to illustrate. We will call the company XYZ. Customers of XYZ send trucks into the field where they provide services to oil and gas enterprises developing oil and gas fields in land- based operations. The pumping systems have a high degree of local automation, but pump operations personnel are not equipped to make decisions regarding when to stop pumping and perform maintenance. For example, the trucks require regular maintenance, and some of the filters require replacement as often as every eight hours. Combine the need for regular maintenance with customers looking over the operator’s shoulders, and occasional mistakes are made with valve positioning and/or running the truck until it breaks in an attempt to please an anxious customer. This drives significant maintenance costs, and downtime is a big problem.。