The purpose of the installed Rod Pump Controller system was to demonstrate production optimization and OPEX reduction, with the aid of Machine Learning and AI based application that helped Operators and Petroleum Engineers better manage the wells. Another one was to help customer evaluate the "as-a-Service" payment model to operate the wells. Such payment models are becoming more relevant across the industry, where International or National Oil Companies allows technology vendors to manage the entire Electrical and Automation scope for wellhead monitoring and optimization. Several issues can develop with this application that can create costly repair situations. Traditionally these have been monitored by personnel visiting each unit on a prescribed basis to ensure they are still operating and then making adjustments during the visit. This makes it ideal for monitored control to ensure maximum liquid production and reduced operational costs. Production optimization for rod pumps is best accomplished by regulating the speed of the pumpjack as reservoir levels rise and fall, in order to gain maximum production without over pumping the well and damaging the equipment. Better management of motor speed can also provide power savings for the end user.

Edge computing is the concept of pushing applications, data, and computing power away from centralized points to the logical extremes of a network. In the oil and gas field, this would be the rod pump well sites. Edge analytics is enabled through a combination of Machine Learning and Control Room/Cloud learning for model development. This approach takes advantage of the unlimited processing power and abundance of historical data available in the control/server room. The model is executed in real-time in the Edge minimizing lag and providing real-time feedback and insights to the operations and productions teams.

As part of the project, it was able to demonstrate an end-to-end cyber secure architecture for the rod pump analytics application. The software platform, inclusive of the Edge gateway and the cloud solution, collected all generated dynacards from the RTU and predicted dynacard shape for every stroke. By doing so, the software provided real-time analytics of rod pump performance along with production and energy consumption parameters. Finally, the benefit of the solution are make better production optimization, cost reduction and improve production revenue/uptime, reduce well service down time. Hence all these things will reduce CO2 emission and drive sustainability strategy for customer.

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