Analytics Solution Helps Identify Rod-Pump Failure at the Wellhead

Industrial-Internet-of-things (IIOT) architecture provides an opportunity to improve asset uptime and maintenance of assets, reduce safety risks, and optimize operational costs. However, to turn data into meaningful insights, the industry must make full benefit of machine-learning (ML) models. This paper presents an analytics solution for identifying rod-pump failure capable of automated dynacard recognition at the wellhead that uses an ensemble of ML models. The proposed solution does not require Internet connectivity to generate alarms and meets confidentiality requirements.

Rod-Pump-Control (RPC) Architecture

Thanks to recent progress in microelectronics, the embedding of ML models in remote places with scarce connectivity, known as edge computing, is possible.