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Digital Twin Technology for Enhancing GOSP Performance and Oil Production Efficiency
Subject area: Science,Engineering and Technology · Area of research: Digital Twin Technology
DOI: https://doi.org/10.64388/IREV10I2-1722212
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.
How to cite this paper
@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}
}