Skip to Main content Skip to Navigation
Conference papers

Optimized Electrification of Subsea Oil & Gas Infrastructures Based in Genetic Algorithm

Abstract : Offshore field development relies on multiple optimization techniques targeting a feasible and cost-effective production solution yet are focused on the field itself. While so, advancements in offshore engineering bring increasingly complex subsea infrastructures to depths in the excess of 3,500 m. Many offshore production topsides which currently rely on costly and harmful onboard thermal-based power generation are turning to high voltage power-from-shore electrification solutions to cope with the challenges being brought by subsea infrastructures. An optimal electrification of these subsea templates is a challenge on its own as the seafloor morphology and well distribution is far from consistent. This paper presents a combined k-means and genetic-algorithm optimization to assess how the combined deployment of high voltage umbilical, wellheads and subsea substations can be optimized for the lowest cost possible. Results show a significant improvement in optimization of the total umbilical length as well as the substation positioning on the seabed.
Document type :
Conference papers
Complete list of metadata

Cited literature [19 references]  Display  Hide  Download
Contributor : Hal Ifip <>
Submitted on : Tuesday, September 24, 2019 - 9:56:06 AM
Last modification on : Tuesday, June 29, 2021 - 12:20:09 PM
Long-term archiving on: : Sunday, February 9, 2020 - 2:27:15 PM


 Restricted access
To satisfy the distribution rights of the publisher, the document is embargoed until : 2022-01-01

Please log in to resquest access to the document


Distributed under a Creative Commons Attribution 4.0 International License



Tiago Antunes, Rui Castro, P. Santos, A. Pires, Matthias Foehr. Optimized Electrification of Subsea Oil & Gas Infrastructures Based in Genetic Algorithm. 10th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), May 2019, Costa de Caparica, Portugal. pp.214-223, ⟨10.1007/978-3-030-17771-3_18⟩. ⟨hal-02295230⟩



Record views