A digital twin modeling and application for gear rack drilling rigs lifting system.
Digital twin
Drilling and completion engineering
Gear rack drilling rig
Real-time prediction.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
10 Oct 2024
10 Oct 2024
Historique:
received:
22
03
2024
accepted:
23
09
2024
medline:
11
10
2024
pubmed:
11
10
2024
entrez:
10
10
2024
Statut:
epublish
Résumé
A comprehensive digital transformation has been undergone by the oil and gas industry, wherein digital twins are leveraged to enable real-time data analysis, providing predictive and diagnostic engineering insights. The potential for developing intelligent oil and gas fields is substantial with the implementation of digital twins. A digital twin framework for gear rack drilling rigs is proposed, built upon an understanding of the digital twin composition and characteristics of the gear rack drilling rig lifting system. The framework encompasses descriptions of digital twin characteristics specific to drilling rigs, the application environment, and behavioral rules. The modeling approach integrates mechanism modeling, real-time performance response, instantaneous data transmission, and data visualization. To illustrate this framework, exemplary case studies involving the transmission unit and support unit of the lifting system are presented. Mechanism models are constructed to analyze dynamic gear performance and support unit response. Real-time data transmission is facilitated through sensor-based monitoring, enhancing the prediction speed and accuracy of dynamic performance through a synergy of mechanism modeling, machine learning, and real-time data analysis. The digital twin of the lifting system is visualized utilizing the Unity3D platform. Furthermore, functionalities on data acquisition, processing, and visualization across diverse application scenarios are encapsulated into modular components, streamlining the creation of high-fidelity digital twins. The frameworks and modeling methodologies presented herein can serve as a foundational and methodological guide for the exploration and implementation of digital twin technology within the oil and gas industry, ultimately fostering its advancement in this sector.
Identifiants
pubmed: 39390008
doi: 10.1038/s41598-024-73954-z
pii: 10.1038/s41598-024-73954-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
23711Subventions
Organisme : National Outstanding Youth Science Fund Project of National Natural Science Foundation of China
ID : 52204002
Organisme : National Science and Technology Major Project
ID : 2016ZX05038-002-LH001
Informations de copyright
© 2024. The Author(s).
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