In an Emerson Exchange Americas virtual series presentation, Emerson’s Evan West discusses ways to optimize artificial lift techniques using cloud-based Supervisory Control and Data Acquisition (SCADA) technologies. Here is his presentation abstract:
Tighter CAPEX [capital expenditures] has put more emphasis on a BOE [barrel of oil equivalent] replacement strategy that includes optimizing oil and gas production from your current assets. Join our expert to learn how to achieve production targets and keep production optimized by enhancing your plunger lift and rod pumping operations. Learn how to take a ‘surveillance by exception’ approach to identify critical issues, perform remote actions to optimize and see the future potential of more advanced optimization capabilities on the journey to autonomous production operations.
Evan opened comparing the journey of oil & gas autonomous operations to the journey of autonomous vehicle operations. The goals are to be as safe as possible and optimize performance.
Following this analogy, he shared the five phases on the journey to autonomous production operations:
Evan discussed examples to optimize plunger artificial lift techniques. The journey includes better sensing & remote monitoring, a comprehensive automation strategy, developing actionable data and using advanced analytics. This path enables advancement through the five phases of autonomous operations.
Combining the right remote terminal unit (RTU) plunger application with the right SCADA host enables better remote visibility and two-way control. He shared several examples, one where the data and analytics detected plunger wear by remotely visualizing fluid load increases, casing drawdown decreases to identify the need to replace the worn plunger.
Evan next shared examples of rod pumping optimization. The first example was a case with debris at the top of the pump. The cloud-based SCADA host could detect the issue by alarming on the rod load increase to detect the issue and enable maintenance before equipment damage could occur. The fix could be made remotely to avoid a trip to the well pad.
A second example was being able to remotely identify a stuck valve open condition. A historical trend identified the condition and a remote maintenance tech can increase the downstroke speed to unstick the valve.
Machine learning and artificial intelligence enable movement to phase 4 automation. Based upon an abnormal condition identified, an automated script can be initiative to address the abnormal condition, such as the stuck valve in the last example. Visibility and alarms for remote personnel is still available to monitor the situation and fix.
Visit the Zedi Cloud SCADA Solutions section on Emerson.com for more on these technologies to move down the path towards autonomous operations.