Performance of an Advanced Intelligent Control Strategy in a Dynamic Positioning (DP) System Applied to a Semisubmersible Drilling Platform

Oil drilling and extraction platforms are currently being used in many offshore areas around the world. Whilst those operating shallow seas secured to seabed, for deeper water operations, Dynamic Positioning (DP) is essential maintain their position within a safe zone. Operating DP requires intelligent reliable control systems. Nearly all accidents have been caused by combination of technical human failures; however, according International Marine Contractors Association (IMCA) Incidents Analysis, thruster system failures leading causes incidents over last ten years. This paper will investigate potential operational improvements accuracy adding Predictive Neural Network (PNN) algorithm allocation along with nonlinear Proportional Integral derivative (PID) motion system. A system’s performance on platform oil gas deep-water fields subject real weather conditions simulated these advanced methods. The techniques developed enhancing safety reliability operations improve positioning accuracy, which may allow faster response critical situation during operations. semisubmersible platform’s simulation results using PNN strategy show improved positioning.