Abstract

Abstract Sucker rod pumping is a common artificial lift method for oil and gas wells in the United States. For decades when using this method, well analysts and production engineers looked at surface and downhole dynamometer cards to diagnose various downhole and surface equipment issues. In more recent years, advantageous rod pump diagnostic software tools have helped train well analysts and production engineers in the analysis of downhole dynamometers cards using comprehensive libraries of known behavior. Unfortunately, the same libraries do not exist for surface dynamometer cards. Without these libraries, diagnostics are based solely on information captured in the downhole dynamometer card. While most data used for analytics and diagnostics can be found in the downhole dynamometer card, a more comprehensive analysis can be done by looking at both the downhole and surface dynamometer cards. Recently, great strides have been made to analyze data and patterns not only found in downhole dynamometer cards, but also surface dynamometer cards. Dynamometer card analysis experts agree that in some cases pump tagging and shallow friction are more visible in the surface dynamometer card than the downhole dynamometer card. Based on these expert opinions, algorithms have been developed that leverage data science tools and statistical methods to better detect both shallow friction and pump tagging problems that are visible in the surface dynamometer card well before they can be seen in the downhole dynamometer card, especially for deep wells. These new algorithms will be additional tools to help well analysts and production engineers more quickly and effectively analyze dynamometer cards and optimize production for the sucker rod pumping system. While current downhole analytical software does provide great benefits to users, adding additional algorithms will provide a more robust and effective dynamometer card analysis.

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