OnPing Plunger, powered by Pak AI, is helping operators increase revenue from plunger lift wells. Today PakEnergy announced the optimization system. The solution also assists operators in reducing lifting costs across their wells. Operators with already optimized wells have seen revenue gains of 3.5% to 7%. Meanwhile, wells using conservative settings have achieved improvements as high as 30%. These results demonstrate the potential of AI-driven production optimization across different well conditions.
The solution aims to bring advanced plunger lift decisions to more wells. It also helps operators avoid adding extra staff to manage optimization tasks. As a result, production teams can address more wells with existing resources.
“Every operator we talk to has more wells than well experts to watch them,” said Ryan Lailey, Chief Product Officer at PakEnergy. “The wells that need attention most are the ones nobody has looked at in a year. OnPing Plunger finds them, fixes them, and keeps them tuned within the limits you already set.”
AI-Based Plunger Lift Optimization
support of aging gas wells, and plunger lift continues to be one of the most economical methods of support. But operational knowledge is often specialized and performance depends on it. Most operators cannot afford experienced specialists on every producing well. This means that some wells are set once and left to run without routine adjustments. This approach can, over time, limit production opportunities. It may also increase the lift cost when the operating conditions change.
OnPing Plunger solves this challenge through continuous well performance analysis. The Pak AI considers the best historical production runs from each well. Then the system compares the current performance with the expected results. In addition, Pak AI is able to change operating setpoints within certain automation and safety limits. It can also flag wells that require human review. This enables operators to focus their expertise where it can have the greatest operational impact.
Pak AI Supports Production Optimization
- The system uses several features to improve plunger lift performance. These functions allow operators to monitor wells and respond to changing production conditions.
- Pak AI setpoint optimization – controls differential in tubing, afterflow timing and pressure thresholds.
- Pak AI drift detection – Detects wells with abnormal operating patterns.
- Three modes of operation – giving operators varying levels of control over system recommendations.
The Off mode finds optimization chances but does not make any alterations. Through this mode, the users are able to examine potential optimization opportunities.
When the Manual mode is used, recommendations for making changes are provided. Then, the operators can make the appropriate choices in regard to the suggested changes.
Using the Auto mode, the adjustments are made under the conditions set by the user. In this way, the system can respond but still take into account the requirements from the operator. Apart from this, OnPing Plunger works well in any automation environment. It remains SCADA-independent in cases where the needed requirements are met.
Expanding Digital Control Across Gas Wells
Legacy equipment can create additional challenges for operators seeking digital optimization. PakEnergy addresses this issue through its Lumberjack digital controller. The controller brings legacy non-digital systems into the scope of the optimization approach. Therefore, operators can extend digital production management across more wells.
By combining Pak AI with existing automation infrastructure, PakEnergy aims to improve production efficiency. The company also seeks to reduce manual monitoring requirements for plunger lift operations.
Overall, OnPing Plunger gives operators another way to manage gas well performance. The system combines historical well data, real-time performance analysis, and governed automation. The approach can help operators identify missed production opportunities. It can also support more consistent plunger lift optimization across their well portfolios.
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News Source PRNewswire.com
