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The APPEA Journal The APPEA Journal Society
Journal of Australian Energy Producers
RESEARCH ARTICLE

Route selection with artificial intelligence: pseudocode and demonstration of a multi-use artificial intelligence algorithm to perform offshore pipeline, cable and umbilical route selection and optimisation

Nigel Lim A and Lucas Lim A *
+ Author Affiliations
- Author Affiliations

A Genesis, Perth, WA, Australia.

* Correspondence to: lucas.lim@genesisenergies.com

The APPEA Journal 62(1) 33-55 https://doi.org/10.1071/AJ21102
Submitted: 20 December 2021  Accepted: 20 January 2022   Published: 13 May 2022

© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of APPEA.

Abstract

Routing pipelines, cables and umbilicals in offshore locations represents a key activity with potential impacts for design, installation and operation. Deficient routing may result in (a) increased offshore construction durations (b) requirements for engineered mitigations from geophysical/geotechnical constraints and (c) unforeseen requirements for intervention during operations. Despite this, offshore route selection is restricted to repetitive, inefficient, and iterative processes between draughters, engineers and asset owners. Now, digital technologies enable optimised solutions for cables and pipelines. This paper presents the development and application of a complex routing algorithm using modern software code frameworks. The algorithm serves as an artificial intelligence platform by replicating engineering expertise. This identifies commonly encountered routing constraints such as geophysical features, seabed gradients, existing offshore facilities. Ideal geometric parameters are then determined to minimise route costs. The algorithm structure will be presented in pseudocode, which will define/describe the digital simulation of route selection within the algorithm. This includes sequences such as (a) processing of offshore geotechnical survey data, (b) recreating offshore locales and routes in a data environment, (c) implementation of geospatial intersection detection, (d) 3-dimensional route length optimisation and (e) automated route selection criteria. This replicates the sequence of manual processes undertaken by engineering experts into a digital realm, thus eliminating time-consumption, repetition and human error. Finally, the algorithm will be demonstrated in offshore case studies with challenging conditions such as highly disturbed seabeds and routing obstacles. Thus, engineers in the future developments can better answer the question ‘What is the best route?’.

Keywords: artificial intelligence, cables, engineering, field development, geohazards, offshore pipelines, pseudocode, routing, subsea, umbilicals.

Nigel Lim is a Senior Engineer with 10 years’ experience in the energy industry. He has been involved in a wide range of project phases from concept studies through to commissioning and start-up, in both Greenfield projects and Brownfield modifications of subsea and offshore facilities. His main experience includes design of subsea production systems and hardware, specialising in Finite Element Analysis (FEA) and construction engineering in offshore assets. In his time with Genesis, Nigel has contributed to major projects in North and Western Australia, including the Prelude FLNG, Prelude Subsea and Bayu Undan while being supplemented by international experience in North Sea and Malaysian projects. His contributions in these projects centres around scoping and implementation of digital techniques to everyday engineering tasks to add value. Through this, he has established himself as a leader to developing digital ways of working and larger digital applications in the industry.

Lucas Lim is a Subsea Engineer with 5 years’ experience in the Subsea Industry, spanning projects in the North West Shelf, Africa and the North Sea. His technical experience in the industry has included the design and analysis of subsea facilities including spools, piping, structures, pipelines and pipeline components. His passion in programming and software skills growth has supplemented his technical knowledge. He uses this combination to add value to his project scopes whilst developing multiple digitalisation platforms.


References

Asad, F (2015). Cost Effective Pipeline Route Selection: An Exact Analytical Solution. Journal of Intelligent Transportation and Urban Planning 3, 116–127.
Cost Effective Pipeline Route Selection: An Exact Analytical Solution.Crossref | GoogleScholarGoogle Scholar |

Darwin, I, and Liawatimena, S (2021). Dynamic Map Pathfinding Using Hierarchical Pathfinding Theta Star Algorithm. Journal of Theoretical and Applied Information Technology 99, 4875–4885.

Kang, JY, and Lee, BS (2017). Optimisation of pipeline route in the presence of obstacles based on a least cost path algorithm and laplacian smoothing. International Journal of Naval Architecture and Ocean Engineering 9, 492–498.
Optimisation of pipeline route in the presence of obstacles based on a least cost path algorithm and laplacian smoothing.Crossref | GoogleScholarGoogle Scholar |

Medvedeva, ON, and Yu Chilikin, A (2021). The Route Selection Method for Natural Gas Pipelines. IOP Conference Series: Materials Science and Engineering 1079, 042073.
The Route Selection Method for Natural Gas Pipelines.Crossref | GoogleScholarGoogle Scholar |

Moreno-Bernal P, Nesmachnow S (2020) A* algorithm for GIS-based pipeline route selection in Veracruz, Mexico. In ‘2020 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)’. pp. 59–64. (IEEE)
| Crossref |

Parums R, Spinoccia M (2018) 50 m Multibeam Dataset of Australia 2018. [Dataset]. Available at http://pid.geoscience.gov.au/dataset/ga/124063

Wang, B, Yuan, M, Yan, Y, Yang, K, Zhang, H, and Liang, Y (2018). Optimal design of an oil pipeline with a large-slope section. Engineering Optimization. , .
Optimal design of an oil pipeline with a large-slope section.Crossref | GoogleScholarGoogle Scholar |

Yildirim, V, Yomralioglu, T, Nisanci, R, Colak, HE, Bediroglu, S, and Saralioglu, E (2016). A spatial multicriteria decision-making method for natural gas transmission pipeline routing. Structure and Infrastructure Engineering 13, 1–14.
A spatial multicriteria decision-making method for natural gas transmission pipeline routing.Crossref | GoogleScholarGoogle Scholar |

Yiu YF, Mahapatra R (2020) Regions Discovery Algorithm for Pathfinding in Grid Based Maps. 2020 Second International Conference on Transdisciplinary AI (TransAI), 2020, pp. 84–87.
| Crossref |