边际油田高效实时在线油井监测创新方法,提高机组响应时间

D. A. Massewa, Muhammad Rifaat, Ferdyan Ihza Akbar, Rahmanda Fadri, Denny Mulia Akbar, Aris Rachmadani, Ichbal Uswitra, F. Nugraha, Fertian Eka Purnama, Bomantara Zaelani, Ridwan Widijanto
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摘要

以前,Siak区块的油井监测依赖于生产人员安排的巡视,在Lindai油田完成一个周期的所有井需要6个小时。本文介绍了利用数字技术观察井参数,并通过智能手机应用程序或网站发送异常通知。在井口面板上安装智能微控制器,在井口周围的指定位置安装三个传感器,对井参数进行在线智能井监测(IWM)。如果出现异常,将通过全球移动通信系统(GSM)信号向用户的智能手机应用程序或网站发送实时通知。监测的参数包括压力、温度和负荷,因为这些参数对于井问题的初步诊断至关重要。根据读数,生产团队可以快速执行故障排除,以防止生产损失(LPO)。该智能单片机的编程采用C语言作为数据编译器。该方法在产量最高的临台油田的一口井中进行了试验。经过三个月的监测,就数据质量而言,与使用校准测量工具的手动调查相比,该工具显示的值只有5%的差异。此外,可以在线实时监控参数,并在出现任何问题时直接通知用户。此外,该工具还可以通过实时通知,将现场工作人员的响应时间从传统的现场考察后的6小时大大缩短到5分钟。此外,与市场上其他知名的在线监控工具相比,该工具的运营成本便宜82%,因此被认为是经济的。从长远来看,该工具将在Siak区块的所有井中实施,以进行综合实时监测。此外,现场规模实施的影响将会更大,例如通过消除手动井检中的人为错误来提高数据准确性,并通过减少疲劳的可能性来提高工作人员的安全性。利用智能单片机进行在线井监测,有利于油井数量多、覆盖范围广的边缘油田。以前,实时井监测通常被认为是昂贵的投资,很少被优先考虑。然而,通过使用该工具实施物联网(IoT)可以改变边际油田的游戏规则,并通过减少LPO来最大化油井的产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Innovative Method for Efficient Real Time Online Well Monitoring to Enhance Crew Respond Time in Marginal Field
Previously, well monitoring in Siak block relied on production crew scheduled tour that needed six hours to complete one cycle of all wells in Lindai field. This paper describes the utilization of digital technology to observe well parameters while sending notification if there is any anomaly regarding those parameters through smart phone application or website. Smart microcontroller was installed in wellhead panel and three sensors are mounted in desired point around wellhead to perform online Intelligent Well Monitoring (IWM) for well’s parameters. If abnormality occurs, real time notification would be sent to user’s smart phone application or website by using global mobile communication system (GSM) signal. The parameters monitored were pressure, temperature, and load because they are essential to be analyzed as initial diagnosis of well problem. Based on the readings, production team could quickly perform troubleshooting to prevent loss production opportunity (LPO). The programming of this smart microcontroller used C language as data compiler. This method was tested in one of the wells in Lindai field, which has the highest oil production. After three months of surveillance, in terms of data quality, the values shown by this tool had only five percent differences compared to manual survey using calibrated measurement tools. Additionally, the parameters could be monitored online, real time, and gave the notification directly to users should there be any issues. Moreover, this tool could reduce the response time of the field crew significantly from six hours following the conventional field tour to only in five minutes by relying on real time notification. In addition, the operational cost of this tool was 82% cheaper compared to other well-known online monitoring tool available in the market so it is considered economical. In the long term, this tool will be implemented on all wells in Siak block for integrated real time monitoring. Furthermore, the impact of field scale implementation will be much greater such as increasing data accuracy by eliminating human error from manual well checking and improving safety of the crew by reducing the possibility of fatigue. The utilization of smart microcontroller for online well monitoring is beneficial for marginal field with high number of wells and wide field coverage. Earlier, real time well monitoring is usually considered expensive investment that rarely become priority. However, the implementation of IoT (Internet of Things) by using this tool can be the game changer in marginal field and maximize the well’s production by reducing LPO.
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