Longer laterals, better perforations and larger frac jobs have all enabled increased production capabilities. However, production optimization practices, which were developed decades ago, are still in use today, and severely limit the ability to aggressively draw wells down. The data provided in the most common fluid level processes does not meet the challenges generated by fluctuating well dynamics and conditions. The irregularity and inconsistency of current fluid level measurement systems and downhole cards provide an incomplete snapshot of the well conditions when a more complete solution is needed for optimization. Moreover, pump-off controller technology cannot discern gas interference from pumped-off scenarios resulting in unplanned shutdown and lost production.

A growing number of wells being produced on sucker rod pump are offering high PIP and high fluid levels above pump, yet production is being limited due to gas interference caused by reservoir dynamics. Pumping through these ever-changing scenarios more aggressively is often the solution, yet this change in optimization practices cannot take place without ensuring the system is not overloaded and rod buckling is not taking place. To have this conversation, casing gas rates, accurate PIP and fluid levels must be acquired and automatically analyzed at a much higher frequency. With a permanent, automated fluid level system, reservoir and fluid data is continuously attained.

Paired with properly tuned algorithms and current optimization practices, these data points give a clearer and more complete story of what rod pumped wells experience continuously throughout the day. Additionally, more information about the reservoir is produced than previously available.

This paper offers insight on current shortcomings in optimization logic for highly dynamic unconventional wells and introduces a proposed methodology to improve runtimes in high gas interference and high fluid level scenarios while extending the life of the installation and equipment. Results showing the methodology's effectiveness at improving production and enhancing drawdown over time are presented.

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