Optimal Path Planning Techniques for Oil and Gas Pipelines

Abstract

Optimal design for pipelines layout is gaining further importance because of the increase in demand on oil and gas products. Due to the crucial importance of pipelines design, the need for optimization of pipelines layout and pipeline networks has acquired the attention of operators and practitioners. Shortest path optimization schemes of pipelines need new assessment to find the optimal solution for real-world topologies. In this paper, three optimal path planning techniques—breadth-first search (BFS), A-star (A*), and artificial potential field (APF)—are compared and introduced to the field of choosing pipelines layout. Although these three techniques are successfully used in other applications, such as robotics and self-driving vehicles, a benchmark study is required to determine the most suitable technique out of these three techniques for pipelines placement application. In this work, a comparison between the three techniques was applied on three types of maps represented different degrees of difficulties, simple, medium, and complex, to choose the optimal technique. Also, these techniques were applied on a real-world problem considering real topologies and complex obstacles. Results of this work show the superiority of the APF algorithm with respect to finding the more realistic, shortest path and taking the lowest computational time. However, the application on real-world problems shows some limitation of this technique due to local minimum problem. The test of the A* algorithm shows moderate computational time and moderate generated path with regard to length. Shortest path planning is usually related to minimizing cost of construction and operation of pipelines. In this work, the objective was to provide practitioners and field engineers with a tool to choose the shortest path for pipelines. Usually, pipelines are designed without considering the shortest path but to prevent geographical obstacles. This work used three path planning techniques, A*, BFS and APF algorithms, to create pipeline paths on various geographical difficulty-level maps. These techniques were appraised in other fields of research but were not compared to solve path planning problems. The results of this work are used to complete the path planning from oil and gas wells to the production and test manifolds and from manifolds to the early production facility (EPF). Further work is currently being done to obtain a software that performs this design and the cost calculations to obtain a realistic pipeline path on all type of maps.