Real-Time Drilling Performance Optimization Using Automated Penetration Rate Algorithms with Vibration Control - Dan Sui (Fuels, 2025)
Automation has transformed process optimization across industries by enhancing efficiency, safety, and reliability while minimizing human intervention. This paper presents a model-based optimization strategy tailored for automated drilling operations, focusing on maximizing performance while maintaining operational safety. The approach employs real-time control of key parameters, such as applied force and rotational speed, through a robust closed-loop control system. An adaptive detection algorithm is incorporated to dynamically adjust operational parameters when encountering changing conditions. This real-time adaptability ensures efficient performance under diverse scenarios while mitigating risks. In the simulation, the data used for modeling drillstring dynamics are sourced from a publicly available benchmarking dataset, which provides a reliable basis for evaluation. From the simulation results, it is clear that the drilling optimization framework is capable of achieving high performance with lower energy consumption while maintaining effective vibration mitigation and prevention. This balance is essential for ensuring operational efficiency and tool longevity in dynamic environments. The findings highlight the potential of this framework to enhance automated systems in energy, construction, and other sectors requiring precise control of dynamic mechanical processes.