Intelligent-Field Management: Monitoring and Optimization of the Greater Ekofisk Area
- Dennis Denney (JPT Senior Technology Editor)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- September 2012
- Document Type
- Journal Paper
- 80 - 83
- 2012. Society of Petroleum Engineers
- 0 in the last 30 days
- 63 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||Free|
|SPE Non-Member Price:||USD 17.00|
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 150424, "Intelligent-Field Management: Real-Time Monitoring and Proactive Optimization of the Greater Ekofisk Area," by Amit Madahar and Alannah McIntosh, Weatherford Production Optimization; Ilnur Mustafin, ConocoPhillips; and Nick McAlonan, SPE, Weatherford Production Optimization, prepared for the 2012 SPE Intelligent Energy International, Utrecht, The Netherlands, 27-29 March. The paper has not been peer reviewed.
An online real-time production-optimization and monitoring system for the greater Ekofisk area (GEA) of Norway was installed in 2006. The system has evolved significantly since installation, with changes driven by multidisciplinary teams in coordination with the operator’s Production Optimization Centre (POC). This online system integrates data from the complete production system—reservoir to export meters. The system enables real-time monitoring of all wells and their associated instrumentation parameters along with field three-phase production allocated to the well level. The system alerts engineers when a well’s performance is outside predefined tolerances, thereby enabling continuous optimization of the combined field network.
The GEA has a high level of activity in terms of well intervention and drilling programs. Therefore, communication about the current operation status across a large multifunctional organization is essential. The GEA has only three fiscal-metering points to measure production. Although sufficient for production allocation at the field level, it results in uncertainty at the platform level. This situation could lead to lost production-enhancement and optimization opportunities.
The POC, subsurface-production-delivery, and reservoir-optimization teams are tasked with assessing real-time data from, nominally, 160 active producers and injectors to minimize losses and maximize field production. An important function of the asset team is to provide daily reports for wells and topside losses. It usually is difficult to compile this information accurately in a short time frame.
Most GEA production wells use gas lift; therefore, it is important to use the finite lift gas efficiently. This optimization process uses an asset-network model. If the asset-network model is not updated frequently and maintained, it will lose its ability to predict well-production rates and pressure drops in the system accurately.
To resolve these problems, the asset uses a multidisciplinary tool called intelligent daily operations. It is used as a real-time-monitoring tool within the POC and is used for daily well-performance monitoring by the production-delivery engineers. This tool facilitates daily well-production variance to detect under-performing wells and flag production-optimization and well-service opportunities. It provides automatic updates to the network model.
The real-time-monitoring tool implements various workflows to enable the different departments to collaborate and share the most-up-to-date information and removes the large amount of manual effort in gathering and analyzing the data, thus allowing engineers to concentrate on increasing production and minimizing losses.
|File Size||5 MB||Number of Pages||4|