Automated ESP-Lifted Well Startup Using Model Predictive Control: Introduction of the Algorithm and Field Tests Results

Abstract

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.