Abstract

The increase in global oil consumption in combination with low to moderate oil prices pushes the demand for cost efficient production in mature oil fields, which often employ any artificial lift system. The reduction of lifting costs by increasing efficiency is essential for extending the mean time between failure (MTBF), the recovery factor of the reservoir and the increase of the economic limit.

These goals can be achieved by applying a novel Finite Elements Method (FEM) for modeling and analyzing the behavior of the sucker rod string and the installed completion. These results are the basis for an optimization of the whole pumping system. Not just the subsurface components are considered, but also the surface pump jack is incorporated as well. The evaluation of the performance of existing units is performed by applying a diagnostic analysis. Also, a predictive analysis to optimize the performance and to design new pumping systems, represent the main targets.

This paper presents the capabilities and the concept employed for analyzing the sucker rod pumping system, based on the results of the sucker rod string FEM – simulation, including surface pump jack features and downhole pump characteristics. The model and the simulation results are verified on the one hand by a comparison with downhole dynamometer measurements, obtained by several self-developed DDS (Downhole Dynamometer Sensor) during field tests and on the other hand by tests at the Pump Testing Facility (PTF) at the Montanuniversität Leoben. The accuracy of the used simulation routine surpasses all currently available commercial software products and also allows the highest flexibility in terms of sucker rod string composition, operation conditions, fluid conditions and the choice of installed equipment.

A comparison conducted on the efficiency and performance of a standard sucker rod pumping system design and an optimized sucker rod pumping system design resulted beside rod string load reductions in the increased energy efficiency of more than 30%.

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