AI4ESP Solution
Autonomous Well Surveillance for ESP Pumps using AI
Siemens A14ESP is a system for the continuous monitoring of ESPs operating across a field. AI4ESP uses machine learning algorithms to train the normal/expected behavior of the ESP system and then identifies, and reports, any anomalies (Variation from expected performance behaviors) to the operator. This can help prevent premature system failure and associated deferment in production.
- Leverage anomalies to reduce ESP downtime and maximize production
By detecting anomalies and possible failure patterns early, decisions can be made on how to best mitigate expensive unplanned pump failures
- Move to ESP management by exception
Leverage AI4ESP to monitor your entire fleet of ESPs and only involve staff in an exception-based situation, freeing staff to do higher value work instead of manually monitoring ESP’s
- Improve understanding of the factors affecting ESP run life
By classifying anomalies and failures, operators gain insights into both ESP run life and well function, enabling better-informed decisions on day-to-day ESP and well operations
- Identify possible changes in in spares and procurement strategy
By identifying root cause ESP failure modes, operators can may modify spares strategy
AI4ESP Solution
Siemens A14ESP is a system for the continuous monitoring of ESPs operating across a field. AI4ESP uses machine learning algorithms to train the normal/expected behavior of the ESP system and then identifies, and reports, any anomalies (Variation from expected performance behaviors) to the operator. This can help prevent premature system failure and associated deferment in production.Oil & Gas producers depend on the efficient operation of their ESP systems – imperative to optimizing production, increasing run time and preventing premature system failure. ESP failure is an expensive event when considering the cost of system replacement and the much higher cost of deferred production resulting from the system failure.
ESPs have traditionally relied on the “pumper” and his ability to manage the ESP – generally based on personal experience and almost always reactive. Digital support and operating systems have become the focus of new development and anomaly detection can create a digital map of the ESP fleet, with smart pumps at the heart of the operation – regardless of vendor or application.
The Siemens AI4ESP solution ingests real time system data and ML algorithms seek variances from the expected behaviors of key parameters. Anomalies are flagged and alerts are sent to the operators before a performance/failure event occurs. Anomalies deliver a proactive window of opportunity for the operator/Engineer to plan next steps and mitigate against potential failure – be that changes in operating techniques, workover planning, improved procurement or other.
