Digital Twin Technology for Enhancing GOSP Performance and Oil Production Efficiency

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@article{1722212,
      author = {Muhammed Asharaf T V},
      title = {Digital Twin Technology for Enhancing GOSP Performance and Oil Production Efficiency},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {10},
      number = {2},
      pages = {710-723},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1722212.pdf},
      abstract = {Gas-oil separation plants (GOSPs) are tightly coupled production systems in which well behaviour, multiphase flow, separator performance, rotating equipment, instrumentation, pipelines, utilities and environmental constraints interact continuously. A digital twin can create operational value only when it connects these physical dependencies to traceable measurements, validated engineering models and accountable field decisions. This paper presents a practice-informed technical review and an implementation framework for applying digital-twin technology to GOSP performance and oil production efficiency. The work is informed by the author's current involvement in a digital-twin initiative and by AVEVA-oriented digital training, while deliberately excluding confidential project information. The proposed reference architecture integrates field and control-system data, AVEVA PI System for operational data management and contextualisation, AVEVA Process Simulation for online first-principles modelling, equipment-performance analytics, engineering information, and controlled operator or maintenance workflows. Technical depth is developed around three high-value use cases: three-phase separator stability, pump and compressor reliability, and production-deferment diagnosis. The paper defines the minimum model logic required for these applications, including phase mass balances, residence time, equipment-curve residuals, uncertainty-weighted data reconciliation, anomaly thresholds and constrained production optimisation. It also proposes a validation workflow based on historical events, shadow-mode operation, prediction error, false-alarm rate, missed-event rate and engineering acceptance. The review uses only sources that were traceable through a working DOI or an official institutional or vendor page at the time of preparation. The resulting framework positions the digital twin as a governed engineering decision system rather than a visual dashboard, and provides a technically defensible route for staged deployment in Saudi smart oil-field projects without overstating unverified benefits.},
      keywords = {Digital Twin, GOSP, AVEVA PI System, Process Simulation, Data Reconciliation, Separator Performance, Predictive Maintenance, Production Optimisation, Saudi Oil Fields.},
      month = {August},
      doi = {https://doi.org/10.64388/IREV10I2-1722212}
  }