Multi-stage Event-triggered Model Predictive Control for Automated Trajectory Drilling

In upstream Oil and Gas operations a well is drilled following a planned trajectory. The trajectory is designed to avoid hard formations and other wells while minimizing drilling time. The uncertainty of the environment, e.g. unknown rock hardness, effects negatively the efficiency of operation: drilling time increases due to frequent corrective control actions that must be taken to counteract disturbances and risk increases since process constraints may be violated. This paper proposes an event-triggered multi-stage model predictive control that aims at tackling both challenges. The event-triggering strategy tries to minimize the number of control actions sent to the actuators, while the multi-stage strategy improves constraints satisfaction despite uncertainties. The method is tested in simulation where unknown changes in rock hardness are considered. In comparison to a standard model predictive control approach, we show that using the combined event-triggered and multi-stage approach we improve constraints satisfaction and decrease the number of control actions. Copyright (C) 2020 The Authors.