The increase in use of variable frequency drives (VFDs) in oilfield facilities, especially for some offshore platforms, often leads to a significant percent of VFDs in total load demand. The VFDs provide many advantages for facility operation, but also produce harmonic contents to electrical power systems. Subsea cables are widely used in offshore power distribution systems. There are two typical applications for subsea cables: 1) transmitting power from the power generation to loads on remote platforms (involving line-side harmonics of a VFD); 2) transmitting power from the output of a VFD to remote electrical submersible pump (ESP) systems (involving load-side harmonics of a VFD). The combination of VFDs and subsea cables in power systems could introduce harmonic resonance, which, if not properly mitigated, amplify certain harmonics and cause significant damage to the electrical equipment in the facilities. An investigation was conducted for the two typical applications in offshore oilfield facilities considering harmonic resonance conditions. The first application involved parallel harmonic resonance and line harmonics, which will amplify harmonic currents. The second application involved harmonic resonance and load harmonics, which will amplify harmonic voltages. Computer simulation software programs were used to develop solutions using line-side and load-side harmonic filters to mitigate harmonics and attenuate resonance; these solutions were verified to be effective in case studies
Electrical submersible pumps (ESPs) are closely monitored in surveillance operations because they operate in challenging environments and are subject to stressful events that, if left without intervention, may lead to unplanned shutdowns, decreased run life, or even failures. These events can occur unannounced with different magnitudes of severity due to the large range of operating conditions. Thus, a universally prescriptive response is challenging because each well may require a tailored and dynamic course of action over time. This paper proposes leveraging a powerful multidimensional state engine known as automated events detection (AED), working together with an artificial intelligence agent, to respond to these stressful events and subsequently improve actions using a reinforcement learning (RL) scheme. Motivations of this approach are to move toward more autonomous, self-protecting systems with closed-loop actions and to achieve this at scale across many wells.
The start of an electric submersible pump (ESP) is the most dynamic event in the life of the ESP, and one that has been shown to be the main contributor to the premature failure of the ESP; yet it is clearly unavoidable. This article introduces an algorithm comprising of a model-predictive controller and a moving horizon estimator for automating the well startup. Objectives and constraints related to the startup are considered for the whole well system, including the reservoir, the ESP, the tubing etc. A lumped-parameter model is established to model the fluid dynamics in the system. The estimator recalibrates the model and provides estimates (virtual measurements) in lieu of unavailable physical measurements. The operating sequences for the ESP and choke are then updated step-by-step by the controller, considering the model of the system, the startup objectives and constraints, and the measured feedback information from the wellbore gauges. The startup algorithm was implemented on a field edge device and deployed to a well in the Permian Basin. The algorithm executed two successful startups. A model recalibration was conducted before the second startup which improved the accuracy of setpoint tracking.
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