Offshore Oilfield Inspection Planning With Drone Routing Optimization

Abstract

Offshore oilfield inspections play a crucial role in environmental conservation and resource management. However, these inspections traditionally depend on manual approaches, which are not only inefficient but also incur high costs. In response to this challenge, this study introduces an innovative drone-based approach to optimize offshore oilfield inspections, focusing specifically on minimizing the total flight duration through effective routing optimization. Based on this approach, we develop a novel and mathematical model that accounts for drone power limitations and inspection time windows. To solve this model efficiently, we propose a refined differential evolution algorithm. This algorithm incorporates both a roulette decoding method and a variable neighborhood search strategy, each contributing uniquely to enhance the solution quality. Experimental results demonstrate that our method markedly reduces the total flight duration of drones, substantially outperforming traditional approaches that do not incorporate routing optimization. This reduction in flight duration leads to more efficient and cost-effective drone operations for offshore oilfield inspections.

Keywords

• Offshore oilfield inspection
• drone routing optimization
• differential evolution
• variable neighborhood search