(2024033) Using Intelligent Automation to Autonomously Update Setpoints to Optimize Dynamic Well Conditions for Rod Lift Wells

The ability to have host software autonomously optimize control artificially lifted oil and gas wells has obvious upsides for operators looking for productivity gains both for their workforce and their assets. In recent years, many strides have been made to develop such algorithms to allow operators to maximize performance on their artificially lifted assets. One of the most significant challenges that remains is how to optimize dynamic wells. Although there are many rules-based approaches that optimize based on certain conditions, it is important to recognize how dynamic many artificial lift wells are, especially unconventional wells. Fortunately, as our understanding of autonomous optimization and unconventional wells improves, algorithms and logic have been developed to allow the host software system to optimize wells based on the dynamic changes in the well bore. 
After running autonomous control logic in the Bakken with a sample size of 40+ wells it is demonstrated that the logic updating setpoints such as idle time, pump fillage, and minimum pump strokes can be effectively optimized even with the well’s operation dynamically changing. This is especially important in rod pump wells that are experiencing incomplete fillage due to gas interference as well as fluid pound. Although those conditions have similar characteristics, it is important to utilize different optimization techniques as a well fluctuates in and out of these conditions. Other dynamic conditions such as sudden increases in inflow and wearing equipment are also conditions that can be optimized for as the operations change. This improvement in autonomous control technology has yielded significant benefits such as production increases where there is opportunity for uplift as well as improvement in pump fillage and decreasing the number of incomplete pump strokes daily, which can help reduce failures. This logic can be applied to a vast number of wells with different operating conditions and still autonomously make intelligent changes that dynamically change and improve operations as needed.