英语翻译Integrating the Intelligent Oilfield 一体化智能油田The Intellig

英语翻译
Integrating the Intelligent Oilfield
一体化智能油田
The Intelligent Oilfield (IOF) is not a one-size-fits-all solution.Part one of this three-part series defines the IOF and looks at the business case for it.
By Jon D.Krome,John R.Matson and Greg Mitchell; IBM Global Business Services
The dynamic and dramatic evolution of the oil industry continues.It was a mere 10 years ago that the industry was feeling bloated with staff as energy demand provided only cautious optimism for the future.Only 20 years ago,personal computers were introduced into the workforce.At that time,the production engineer’s only data source was to be found on an operator’s clipboard or in a stack of old,daily reports found in a file cabinet in someone else’s office.It took weeks to route an Authority For Expenditure (AFE) for any type of well or facility work.Planning,scheduling and implementing a simple workover took weeks to months.
The work and workplace continue to change.Competition for hydrocarbons has driven companies to explore and produce in harsh and remote locations,where even the simplest logistical tasks can be difficult,dangerous and costly.As the environment grows more unforgiving and the challenges more complex,skilled technical resources are becoming scarce.New projects bring more risk,which,in turn,requires a greater quantity and quality of data from which to learn.Importantly,the information and communication technology that supports (and at times drives) the industry has dramatically improved.These factors have set the stage for use of the IOF.
The IOF defined
Frequently captured data,distributed,evaluated and acted upon in real time forms the basis for any IOF approach.Also known by many of its synonyms (the Digital Oilfield,Field of the Future,i-Field,e-Field,Real-time Operations,and Real-time Optimization),the IOF can reduce the uncertainties of the looming “great crew change” and ever-increasing project complexity.And,the IOF holds great promise for a future of higher productivity,increased recovery,lower costs and reduced health,safety and environmental exposure.

一体化智能油田
智能油田不是一个普适的解决方案.这个三部系列的第一部分对智能油田进行了定义并且浏览了与之相关的商务案例.由IBM全球商务服务中心的约翰 D 克罗姆和格雷格 米切尔合著.
石油行业活跃而戏剧性的演变仍然在继续.仅仅十年前,由于未来的能源需求仅为谨慎乐观,这个行业还感觉人员过于臃肿.只是在二十年前,才给员工配备了个人电脑.当时,生产工程师只能在操作员的笔记板或其他人办公室档案柜里的一堆老旧日报中去找数据.任何类型油井或设施工程的费用开支授权都要花费几个星期走程序.规划、安排和执行一个简单的油井维修就要花费数周或数月.
工作和工作场所继续发生变化.对碳氢化合物的竞争已经促使各公司到艰苦和偏僻的地区去钻探和开采,在这些地区即便是最简单的后勤任务也变得非常困难、危险和代价高昂.随着环境越来越严苛以及挑战越来越复杂,熟练的技术人员正逐渐变得稀缺起来.新项目带来更多的风险,从而相应需要更多数量更高质量的数据以供了解.非常重要的是,支持（有时是驱动）这一行业的信息和通讯技术已经极大改善了.这些因素为使用智能油田打下了基础.
智能油田定义的频繁获取数据,实时传输、评估和采取措施构成了所有智能油田方法的基础.智能油田有许多同义词（数码油田、未来油田、i-field、e-field、实时操作系统、实时优化系统）,它能减少隐隐约约的“员工巨变”和持续增长的项目复杂性带来的不确定性.同时,智能油田是将来更高的生产力、增长的回采率、更低的成本和更少的健康、安全和环境风险的重要希望所在.