Abstract

Abstract Rod pump monitoring and optimization has traditionally relied on polished rod load and position data. We set out to prove that tubing pressure monitoring is an effective alternative optimization tool to traditional rod pump diagnostic tools. Pressure monitoring devices, based on an internet of things (IoT) architecture were installed on the flow tee of pumpjacks in a variety of fields. Each device continuously captured, stored, and delivered high-quality, time-synchronized, per-second pressure measurements to a cloud-based data service. Over time, with firmware upgrades to the device, higher frequency sampling was implemented. At a sample rate of 13.3 Hz, a clear, stroke-by-stroke view of changes associated with the movement of the bottomhole pump emerges. A method for estimating efficiency and diagnosing bottomhole pump conditions was developed utilizing only the velocity profile of the polished rod, bottom hole pump plunger diameter and polished rod diameter. Through observation of pressure data and correlating it to available field data, an efficiency calculation method was developed. The velocity profile of the pump jack, the polished rod diameter, and the bottom hole pump diameter are used to generate an expected pressure profile for a 100% efficient pump. Deviations from the expected pressure profile are used to estimate pump efficiency and diagnose problematic pump conditions. The volumetric efficiency of eight wells was estimated and compared to the volumetric efficiency calculated from test data. The sample size was not adequate to validate the method, but the results gave initial indications that showed the method has promise. Current rod pump monitoring solutions can be cost prohibitive when evaluated for aging wells, which make up most of the North American production. Using accurate, high frequency pressure data to evaluate rod pumping performance looks to be a promising low-cost alternative to conventional rod pump monitoring methods.

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