Jared Bruns and Abhishek Sharma, Schlumberger
Will Whitley, Oasis Petroleum
Modern sucker rod pump operations rely on pump-off controller’s, surveillance dashboards, and human intervention to maximize production and pump performance. As a result, rod pump operations often suffer from high manual workload, limited diagnostics and dynamic well conditions. For wells fitted with pump-off controllers and variable speed drives, challenges remain around data gathering and evaluation. Bringing well specific insights to action requires continuous physical supervision to ensure well uptime. Edge computing and Internet of things (IoT) technologies offer high frequency data gathering, real-time evaluation and a reliable mechanism to maximize rod pump productivity while automating redundant tasks. Advanced computations, enabled by edge computing, allow for a more comprehensive analysis of pump conditions that compliments and surpasses the capabilities of pump off controller automation. This paper will demonstrate how closed loop algorithms deployed on edge computers work to ensure the best operating conditions, autonomous dynacard evaluation and interventions, and a proactive approach to help manage anomalous, high failure wells.