The high consequence Oil and Gas sector demands exceptional mechanical integrity and operational reliability to prevent disastrous failures and ensure business continuity. Unplanned downtime presents significant environmental and financial risks, underscoring an urgent need for digital transformation to enhance safety, efficiency, management, planning, training, and equipment monitoring. In response, this thesis develops a complete architectural framework for digitizing complex industrial assets. The practical implementation involves creating a high-fidelity "Digital Shadow" of a critical gas compression station comprising three turbo-compressor segments. This research extensively analyzes the application of digital twinning for predictive maintenance and remote safety management, while critically examining the future integration to automate complex modeling operations. A detailed approach is unfolded across five phases: Document Analysis, Family Modelling, Laser Scanning, Plant Modelling, and Parameterization. More than 1,300 technical documents were reviewed first. Then came digital reconstruction, LASER scanning, and building of detailed and precise semantic 3D Model in Autodesk Revit. Parametrization followed; custom scripts managed around four thousand distinct parameters. Through this step, each component in digital twin was identified and tied to the physical plant and along with relevant data. What emerged was not just a visual replica, but a unified repository of physical and operational details. One single source now holds both shape and substance of the entire site. The model was proved to be effective on-site, as it was able to locate 1,214 equipment items out of 1,262. In addition, it confirms that the combination of the legacy document analysis and the cutting-edge applications of reality capture is an extremely efficient choice to amalgamate the physical and virtual planes of industrial property.
Il settore dell'Oil & Gas, caratterizzato da scenari ad alto rischio, esige un'integrità meccanica e un'affidabilità operativa eccezionali per prevenire guasti catastrofici e garantire la continuità aziendale. I fermi impianto non pianificati comportano significativi rischi ambientali e finanziari, evidenziando l'urgente necessità di una trasformazione digitale volta a ottimizzare sicurezza, efficienza, gestione, pianificazione, formazione e monitoraggio delle apparecchiature. In risposta a tali esigenze, la presente tesi sviluppa un framework architettonico completo per la digitalizzazione di asset industriali complessi. L'implementazione pratica ha previsto la creazione di un "Digital Shadow" ad alta fedeltà di una stazione di compressione gas critica, composta da tre segmenti di turbocompressori. La ricerca analizza l'applicazione del Digital Twin per la manutenzione predittiva e la gestione della sicurezza da remoto, esaminando criticamente le future integrazioni per l'automazione di operazioni di modellazione complesse. L'approccio metodologico si articola in cinque fasi: analisi documentale, modellazione delle famiglie, scansione laser, modellazione dell'impianto e parametrizzazione. Inizialmente, sono stati esaminati oltre 1.300 documenti tecnici. Successivamente, si è proceduto alla ricostruzione digitale e alla scansione LASER per la creazione di un modello 3D semantico dettagliato in Autodesk Revit. La fase di parametrizzazione, supportata da script personalizzati, ha permesso la gestione di circa 4.000 parametri distinti, collegando ogni componente digitale al corrispondente fisico e ai relativi dati operativi. Il risultato ottenuto non è una mera replica visiva, bensì un repository unificato di dettagli fisici e funzionali: un'unica fonte di verità per l'intero sito. L'efficacia del modello è stata validata sul campo, localizzando con successo 1.214 componenti su 1.262. Lo studio conferma che l'integrazione tra l'analisi della documentazione storica e le tecnologie avanzate di reality capture costituisce una strategia estremamente efficace per la convergenza tra la dimensione fisica e quella virtuale degli asset industriali.
Digital twinning of the oil and gas infrastructure: potential and industrial implementation
Abdeen, Zain Ul
2024/2025
Abstract
The high consequence Oil and Gas sector demands exceptional mechanical integrity and operational reliability to prevent disastrous failures and ensure business continuity. Unplanned downtime presents significant environmental and financial risks, underscoring an urgent need for digital transformation to enhance safety, efficiency, management, planning, training, and equipment monitoring. In response, this thesis develops a complete architectural framework for digitizing complex industrial assets. The practical implementation involves creating a high-fidelity "Digital Shadow" of a critical gas compression station comprising three turbo-compressor segments. This research extensively analyzes the application of digital twinning for predictive maintenance and remote safety management, while critically examining the future integration to automate complex modeling operations. A detailed approach is unfolded across five phases: Document Analysis, Family Modelling, Laser Scanning, Plant Modelling, and Parameterization. More than 1,300 technical documents were reviewed first. Then came digital reconstruction, LASER scanning, and building of detailed and precise semantic 3D Model in Autodesk Revit. Parametrization followed; custom scripts managed around four thousand distinct parameters. Through this step, each component in digital twin was identified and tied to the physical plant and along with relevant data. What emerged was not just a visual replica, but a unified repository of physical and operational details. One single source now holds both shape and substance of the entire site. The model was proved to be effective on-site, as it was able to locate 1,214 equipment items out of 1,262. In addition, it confirms that the combination of the legacy document analysis and the cutting-edge applications of reality capture is an extremely efficient choice to amalgamate the physical and virtual planes of industrial property.| File | Dimensione | Formato | |
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2026_03_Abdeen.pdf
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Descrizione: Thesis Report on Digital Twinning of the Oil and Gas Infrastructure: Potential and Industrial Implementation
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6.8 MB
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https://hdl.handle.net/10589/250482