As wells mature or operating conditions shift, subtle signs of performance decline—like rising water cut, fluctuating pressures, or inefficient lift—often go unnoticed until production is impacted. Traditional monitoring methods tend to catch these issues only after they’ve escalated, leading to costly interventions or unplanned downtime.

The Well Health Predictive Alert solution tackles this challenge by continuously analyzing well behavior across parameters such as FBHP, WHP, production rates, downtime frequency, and historical interventions. Powered by machine learning and physics-informed thresholds, it identifies early indicators of problems like liquid loading, scale buildup, or artificial lift instability—often days or weeks before failure.

With alerts prioritized by severity and confidence, engineers can take timely actions such as gas lift adjustments, cleanouts, or scheduled workovers—well before performance drops. The solution enables users to explore well health trends, investigate causes, and act with confidence. This shift from reactive troubleshooting to proactive planning helps maintain production, reduce operational risk, and extend the productive life of each well.