Abstract
In production operations, a lot of effort has been devoted to monitoring well head and flow line parameters. Connecting sensors to monitoring systems, collating, and transmitting the data off site for manual or automated review requires infrastructure build out and processes developing to analyze and action the data, consuming additional resources. The concept of edge computing, moving the analysis and decision closer to the well is a challenging problem which requires the addition of controlling elements. The objective is not just to monitor the conditions, but also to take action based upon the observations without unnecessary intervention.
This paper introduces a new method of closed loop production control, integrating production tree master valve, emergency shut down system and choke management into a single automated, autonomous system. By implementing microprocessor control at the wellsite, basic management functions can be automated with sequencing to mitigate risk of procedural errors, improve well integrity, and minimize downtime. The key elements of such a system comprise of master valve actuation, wing valve actuation and production choke actuation linked by a single co-dependent system that can perform condition based monitoring and self-diagnose system issues.
A discussion of the design and function of the method, with due regard to limitations, best practices and workflows will be demonstrated, providing an examination of the results of design experiments. The potential for further implementation is examined as well as highlighting operational differences vs current technology that deliver value to producers and operators.
Expanding the capability of wellsite autonomous control to address operational concerns and reduce operational costs is within the reach of technology that is integrated into monitoring systems, moving the decision point closer to the well. With a proven ability to monitor and action analyses, communicating the results of the action for operational status updates substantially reduces the need for large bandwidth infrastructure and in the right applications, increased well and equipment uptime without risk of costly integrity issues. This enables autonomous systems to be deployed in more remote areas, allowing the same level of assurance in control afforded to more infrastructure rich environments.
