Continuous improvement initiatives prompted the deployment of a new way to drill smart wells combining the most recent technologies. The solution consists of a complete closed loop workflow utilizing an intelligent rotary steerable system (RSS) with high-frequency downhole measurements and processing capacity, an in-bit parameter sensing device, and a novel high-speed telemetry system guided by an autonomous drilling platform. Primarily focused on reducing human intervention and improving performance, the leading Key Performance Indicators (KPI) selected to benchmark the performance were drilling time, represented by Rate of Penetration (ROP), and flat time represented by casing running time. All while providing operational consistency and reducing Health Safety and Environment (HSE) risks. The autonomous drilling platform orchestrates the rhythm in which the RSS executes commands to stay on the planned well path. Another workflow links between well placement software and the autonomous drilling platform in case a change in well trajectory is required for well placement purposes. The new pilot workflow triggered a critical well process for the planning and design phase. A comprehensive pre-well modeling exercise was required as it was the first run in the country for most of the featured technologies. The in-depth exercise resulted in a scenario-based decision tree to ensure seamless workflow execution. Three primary functions were planned for automation with varying machine control levels, and limitations posed by the drilling rig. Those functions covered directional steering and trajectory control, vibration mitigation, and hydraulic management. The first section delivered a field record with a 30% faster ROP than the best offset achieving a 7deg /100feet dogleg seamlessly while adapting to formation behavior changes to meet well plan objectives. The section also achieved the fastest casing run time among similar profile wells, breaking the second KPI record. The automation platform provided steering control during the entire section, landing the well perfectly in the target reservoir, making the section best in class in the area. Meanwhile, the hydraulics management function provided a smooth hole profile that helped tripping and casing running time. The vibration modes recorded using in-bit sensors helped analyze and build with a more effective drilling roadmap for modeling/executing future wells with even higher accuracy. With the above performance, it is worth noting that the record section was delivered using one of the historically slowest rigs in North Kuwait. The paper focuses on the details of the automated drilling suite and the internal and external workflows developed with the operator to enable the deployment of such a system and help introduce a more innovative way to drill, resulting in breaking all the records achieved with conventional methods from the first trial. It also discusses the viability of applying such methodology to other projects of varying complexity.

This article describes an automation system for a residues treatment plant based on thermal plasma. A compact PLC was used to activate several subsystems and to control the main reactor inner temperature using Fuzzy logic. A human-machine interface allows the monitoring of the variables and the activations of devices of the system remotely. An OPC communication is used to link the computer and the PLC.