Piping system development in oil and gas field based on Dijkstra's algorithm and genetic algorithm

Gunawan, Allessandro Setyo Anggito Utomo, Altabibi Naufal Syafaq

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Modelling of pipeline routes in the oil and gas industry is necessary to examine in this decade. The complexity of the pipeline design in the oil and gas business increases operational costs over time. In addition to operational costs, the problem with pipe design is that humans cannot calculate with certainty the physical limitations that occur in the pipeline. Therefore, produce a level of certainty in the pipeline design is fallacious. The use of Genetic Algorithms (GA) and Dijkstra's Algorithm (DA) as artificial intelligence produce easy calculation and prediction of pipelines to the optimal and accurate stages. The pipeline simulation is based on the pipe's length and the amount of bending as a physical attribute to pressure drop in pipeline. In this study, the algorithm uses 2000 data generation from 100 populations, 80% of the data used for training the algorithm model (1600 experiments), and 20% (400 experiments) of data used for control-the experiment conducted in a 1: 5000 (65 x 60 grid) environment. The research used a map of the distribution of oil and gas pipelines in Nigeria around the regions of Benin, Warri, Owerri, Aba, and Harcourt. Pipeline optimization from genetic algorithm modelling and Dijkstra's Algorithm increased prediction efficiency by 4.9%.

Original languageEnglish
Title of host publication5th International Tropical Renewable Energy Conference, i-TREC 2020
EditorsRidho Irwansyah, Muhammad Arif Budiyanto
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735441286
DOIs
Publication statusPublished - 23 Sept 2021
Event5th International Tropical Renewable Energy Conference, i-TREC 2020 - Depok, Indonesia
Duration: 29 Oct 202030 Oct 2020

Publication series

NameAIP Conference Proceedings
Volume2376
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference5th International Tropical Renewable Energy Conference, i-TREC 2020
Country/TerritoryIndonesia
CityDepok
Period29/10/2030/10/20

Keywords

  • Algorithm
  • Artificial intelligence
  • Optimization
  • Pipeline routes
  • Prediction

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