Performance Evaluation of Different Short Path Algorithms to Improve Oil-Gas Pipelines

Nabeel Naeem Almaalei,Siti Noor

doi:10.14569/ijacsa.2019.0101109

Abstract

The oil-gas pipeline is a complicated and expensive system in terms of construction, control, materials, monitoring, and maintenance which includes economic, social and environmental hazards. As a case study of Iraq, the system of pipelines is above the ground and is liable to disasters that may produce an environmental tragedy as well as the loss of life and money. Hence, this article presents a performance evaluation of different short path algorithms to improve oil-gas pipelines. The chosen algorithms in this paper were Parallel Short Path Algorithm (PSPA), Ant Colony Optimization (ACO) algorithm and Genetic Algorithm (GA). The main performance metric is the cost of the pipelines. Simulation trials were performed using the MATLAB program for the chosen algorithms. The performance comparison showed that the lowest cost of laying oil and gas pipelines was by applying the GA algorithm when the number of wells was set to 50-600. Conversely, the PSPA algorithm showed the best performance in terms of required implementation time for all scenarios. Besides, PSPA appeared to have acceptable performance in terms of the cost of the pipeline when the number of wells was arranged between50-600. Furthermore, PSPA showed the best performance for 700 and 840 wells in terms of the cost of laying the oil and gas pipelines compared to ACO and GA. It should be noted that the ACO algorithm showed medium performance in terms of the cost of laying oil and gas pipelines compared to PSPA and GA.

Highlights

Oil is a crucial source of energy
The Parallel Short Path Algorithm (PSPA) algorithm showed the best performance in terms of required implementation time for all scenarios
It should be noted that the Ant Colony Optimization (ACO) algorithm showed medium performance in terms of the cost of laying oil and gas pipelines compared to PSPA and Genetic Algorithm (GA)

Summary

INTRODUCTION

Oil is a crucial source of energy. It is used in many industries, transportations and electricity supplies. The oil pipelines are used to transport (import and export) petroleum products between different cities around the world with about 17.95 million barrels per day [1] This has led to the development of large and extensive design as well as operations of pipelines which have become more complex in recent years [2]. The optimization network of pipelines for gathering and transporting oil and gas should include the location, parameter, and topology. In prior work [5], the authors used a genetic algorithm to supply the natural gas distribution network, while in the same year, Jiancheng in [6], who was the first researcher to use GA in the oil-gas pipeline network, used ANN to determine the multilevel star network. Fifty-nine percent of the total oil reserves were distributed to other fields including the North Rumaila, South Rumaila, Majnoon, Zubair, River Omar, West Qurna, AlTuba, Al-Sabah, Al-Halafiyya, and Abu-Gharb and AlBazarkan fields [9]

Oil-Gas Pipeline Network

Oil-Gas Parallel Shortest Path Algorithm

Formulation of ACO Algorithm in a Mathematical Model

GA Algorithm

SIMULATION AND RESULTS

CONCLUSIONS