利用状态监测软件优化海水处理操作

A. Wilcox, R. Mikkelsen, Pei Ling Esther Lian
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引用次数: 0

摘要

为了最大限度地提高提高采收率(EOR)工艺的价值,一款状态监测软件程序旨在优化海水处理系统的性能和维护工作。通过收集来自平台或船舶上的传感器、仪器和控制器的数字输入,您可以监控系统行为,并利用应用专业知识和数据科学来描述操作条件,从而使作业者能够降低运营成本并最大限度地提高产量。将无与伦比的工艺专业知识与数据科学和软件开发团队相结合,产生了海水处理(SWT)过程的全系统视图。利用SWT操作的当前和历史数据,将其导入物联网平台,并利用定制软件程序,提供系统性能的全面可视化和系统内关键组件的状态监控。一个例子是监测硫酸盐去除装置(SRU)并预测膜的污染类型。通过这种增强的性能和预测分析视图,您可以减少对海上监督和故障排除工作的需求,并可以防止重复故障和意外停机。以SRU为例,海水处理软件程序可以早期检测膜污染,使作业者能够主动实施污染缓解方案。通过早期发现污垢,操作人员可以优化就地清洗(CIP)顺序,及时执行CIP和化学药剂,以延长膜的使用寿命,防止不必要的停机,防止永久性膜损坏。通过历史数据可以观察到,运营商每年可以在膜寿命、减少停机时间和防止生产损失方面节省大量资金。通过使用优化的化学注入程序来管理和防止系统中的生物生长/结垢形成,还可以节省额外的成本。为了满足作业者优化海水处理和其他上层工艺设备的需求,一套特定工艺的软件应用程序可以完全集成到一个数字平台中,提供一个框架,可以根据客户的需求轻松定制,包括必要的附加功能。结合全面的井流处理技术,对流体行为的深入了解和数字化的可靠记录,现在可以发现和解决操作问题。这与典型的远程监控计划不同,因为它应用经过验证的机器学习和预测分析框架,从捕获的数据中检测模式和痕迹,以便尽早发现未来的问题,并提供主动建议,以防止中断运营。
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Optimizing Seawater Treatment Operations with Condition Monitoring Software
In an effort to maximize the value of the Enhanced Oil Recovery(EOR) process, a condition monitoring software program aims to optimize Seawater Treatment system performance and maintenance efforts. By collecting digital inputs from sensors, instruments and controllers on the platform or vessel, you can monitor system behavior and use application expertise and data science to characterize the operational conditions which enable operators to reduce their operating costs and maximize production. Combining unparalleled process expertise with data science and software development team, a system-wide view of the Seawater Treatment (SWT) process is produced. Using current and historical data from SWT operations, ingesting into an IOT platform and, utilizing custom software program, provide full visualization of the system performance and condition monitoring of critical components within the system. One example is monitoring the sulphate removal unit (SRU) and predicting fouling types of the membranes. With this enhanced view of performance and predictive analysis, you can reduce the need for offshore supervision and troubleshooting efforts and can prevent repeat failures and unplanned downtime. Using the SRU as an example, the Seawater Treatment software program enables early stage detection of membrane fouling which allows the operator to proactively implement a fouling mitigation program. By detecting the fouling early, the operator can optimize the cleaning in place (CIP) sequences, perform timely CIP and chemical dosing to extend the life of the membranes and prevent unnecessary downtime and prevent permanent membrane damage. It has been observed through historical data that operators can save a significant amount of money per year on membrane life, downtime reduction and production penalty prevention. There are additional potential savings by using an optimized chemical injection program to manage and prevent biogrowth/scale formation in the system. To address the operator's need of optimizing Seawater Treatment and other topside process equipment, a suite of process specific software applications can be fully integrated into a digital platform, providing a framework that easily can be tailored to customer's needs to include additional features if required. Combining a comprehensive selection of wellstream processing technologies with deep understanding of fluids behavior and proven track record of digitalization, operational issues can now be uncovered and solved. This is different from typical remote monitoring initiatives in that it applies proven machine learning and predictive analytics frameworks to detect patterns and traces from the captured data to provide the earliest possible detection of future issues and provide proactive recommendations to prevent disruption to operations.
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