Efficient oilfield asset management requires the effective use of real-time data, model updates, and optimization of control variables to produce the most favorable choices However, the orchestration of disciplines, workflow tools and available data represents critical issues in the oil industry. In many cases, the engineer may not focus on high-impact tasks nor generate added-value opportunities. Instead, the engineer's attention is diverted to collect, manipulate and create data charts. Data collection and validation, as well as model validation and updates, are repetitive tasks that may be automated under certain conditions to relieve engineers from low- value-added tasks. Real-time production optimization (RTPO) is one component of the Digital Oil Field (DOF) that aims to solve these issues.

This paper focuses on the implementation of an RTPO system in the Okume Complex field in Offshore Equatorial Guinea. Two main challenges in this field include continuously allocating gaslift in frequently changing field conditions while minimizing production losses as well as understanding and maximizing the field production plateau. A commercial tool was used to demonstrate the value of RTPO. The implemented project supports the automation of standard workflows within the asset. The project proved several hypotheses concerning the streamlining of data capture, discipline interaction and model sustainability. Data availability and model readiness resulted as key factors from the fast and proficient implementation of the tool.

The implementation of the project reduced the time requirement for test data gathering, validating, and model updating by more than 70%. The intelligent wells achieved continuous zonal allocation while minimizing the risks of crossflow. According to the results of this work, the asset is now able to adjust gaslift settings on a daily basis for optimizing production between 1.0% and 5.1% daily. This paper presents a summary of the benefits during pilot implementation, current project status, and the next steps.

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