Process Safety Management in Oil and Gas Operating Units Through Digital Twin Platform: A Digital Approach for Safety Control and Process Intervention
Управление безопасностью технологических процессов в эксплуатационных подразделениях нефтегазовой отрасли с помощью платформы «цифровой двойник»: цифровой подход к контролю безопасности и вмешательству в процессы
2023-10-17
SCID: 54.1/s9p94cvd
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3D engineering model middlewareDigital TwinFPSO (Floating Production Storage & Offloading)OCR and Regular Expressions for risk analysis extractionprocess safety management
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Abstract (AI)
Abstract Operational safety holds significant importance in the oil and gas industry, given the complex and high-risk nature of its operations. Considering this complex challenge, this paper describes the development of an application through a cloud-based platform that integrates the operation and maintenance phases of industrial plants through a Digital Twin for the management of risk in Oil and Gas operating units. The platform integrates project data as well as process documentation on the digital twin database, providing a systematic overview of risk analysis, safety control, and management of the operating units. By creating an integrated database, operators can access information, models, and processes, and perform simulations through web access and mobile. For the Process Safety application on an FPSO (Floating Production Storage & Offloading), information from risk analyses was extracted through OCR, Regular Expressions, and then contextualized and linked to the 3D model. To implement the solution, it was created an integrated system based on protocols for consuming and updating data, documents, and models involved. This includes a middleware for 3D engineering models and a document integrator for risk analysis processes, along with a dynamic visual representation of the sequencing of actions when process intervention is required. The solution presented in this paper offers valuable recommendations and evidence to support interventions and audits. Furthermore, it centralizes access to engineering information, significantly reducing industry professionals’ time spent searching and validating data across different operating systems, leading to a reduction of up to 75%. The system also generates simulated dynamic visual representation in the digital environment to showcase the sequencing of actions required during interventions in the process. This approach has led to an expected improvement in the recordable incident rate and a significant reduction in the time required to plan shutdowns and turnarounds. Overall, the platform's efficacy is demonstrated through its ability to streamline processes and enhance safety protocols.
Key Findings
1
Approach is expected to improve the recordable incident rate and significantly reduce time required to plan shutdowns and turnarounds.
2
Centralizing engineering information reduced professionals' time spent searching and validating data across systems by up to 75%.
3
Developed a cloud-based Digital Twin platform integrating operation and maintenance phases for risk management in oil and gas operating units.
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For an FPSO case, risk analysis information was extracted using OCR and regular expressions, then contextualized and linked to the 3D model.
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Implemented middleware for 3D engineering models and a document integrator for risk analysis, plus protocols for consuming and updating data and models.
6
Operators can access models, information, and perform simulations via web and mobile, enabled by an integrated database.
7
Platform integrates project data and process documentation into a Digital Twin database, providing systematic overview of risk analysis, safety control, and management.
8
Platform produces dynamic visual representations of action sequencing for process interventions and simulated dynamics for intervention planning.
Research Object
Cloud-based Digital Twin platform for process safety management in Oil and Gas operating units (including FPSO)
Research Subject
Effectiveness of the Digital Twin platform for integrating data/documents/models to support risk analysis, safety control, process intervention sequencing, simulations, and to reduce time for information retrieval, shutdown planning, and incident rates
Publication Details
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2023-10-17
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