Real-time Rate of Penetration Optimization of an Autonomous Lab-Scale Rig using a Scheduled-Gain PID Controller and Mechanical Specific Energy
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2018 Automation in the oil & gas industry has become a golden goal for major operators, increasing R&D expenditures, and automation related projects are increasingly more common. A miniaturized autonomous drilling machine was built with the objective of performing optimal operations regarding the rate of penetration and energy efficiency the lab-scale rig employs control algorithms, and innovative instrumentation solutions, leading to a large amount of data to be analyzed in real-time to accurately control important drilling parameters such as weight on the bit (WOB) and rotary speed. An scheduled-gain PID Controller was designed and implemented in a micro-controller to accurately adjust the amount of weight on the bit (WOB) and avoid disturbances. High-frequency data was acquired using LabVIEW and analyzed in realtime through the MATLAB programming environment. The data was then passed to MATLAB, where the automated algorithm analysis is performed. The results of the analysis are used in a closed-loop control algorithm to optimize the rate of penetration, energy efficiency and mitigate drilling failures. The algorithm uses real-time instrumentation data to implement an automated step-test and optimize drilling parameters on the fly. Increasing the average rate of penetration and reducing vibration-induced borehole irregularities.
