Description
Digital Transformation for Reservoir performance monitoring: (ENI)
Eni has been using PI System for more than 10 years collecting, monitoring and analysing real time data in a subset of our productive sites, spreading this technology across the enterprise. By then, all AF features, PI Process Book/PI Vision has been widely used extending the monitoring from the surface to the subsurface, Eni started a digital transformation journey launching projects within all business area among them in Reservoir Department. Monitoring room has been settled down together with Production department allowing a full cooperation and sharing of reservoir and production competence. A stronger HQ support to Affiliates, for reservoir and well monitoring activities, is provided using our standardized monitoring tools; the improved routine work has reduced the latency and the errors in data sharing due to continuous availability of real-time data and KPI calculation so a fast, accurate and proactive monitoring is now available.
Big Data Advanced Analytics to Forecast and Manage Critical Upsets in Upstream Production System: (ENI)
This paper highlights development and results of innovative tools for prediction and prescription of upsets and hazard events associated with upstream oil&gas production operations. This software can give recommendations to mitigate or avoid operational issues, maximizing the asset value, while maintaining the highest safety and environmental quality. The in-house tool is based on the integration of a big data analytics architecture and OSIsoft products. The workflow allows predicting future events and impact parameters. This is done thanks to a powerful machine-learning algorithm specifically selected for the physical problems analyzed. The inputs come from a heterogeneous data-lake, composed by historical data, real-time series, analysis, etc. all managed by PI based Digital Oilfield System. The tool is fed with field data, through PI, at high velocity and frequency, predicting potential events with prescription of possible actions to avoid production and asset integrity issues.
Eni has been using PI System for more than 10 years collecting, monitoring and analysing real time data in a subset of our productive sites, spreading this technology across the enterprise. By then, all AF features, PI Process Book/PI Vision has been widely used extending the monitoring from the surface to the subsurface, Eni started a digital transformation journey launching projects within all business area among them in Reservoir Department. Monitoring room has been settled down together with Production department allowing a full cooperation and sharing of reservoir and production competence. A stronger HQ support to Affiliates, for reservoir and well monitoring activities, is provided using our standardized monitoring tools; the improved routine work has reduced the latency and the errors in data sharing due to continuous availability of real-time data and KPI calculation so a fast, accurate and proactive monitoring is now available.
Big Data Advanced Analytics to Forecast and Manage Critical Upsets in Upstream Production System: (ENI)
This paper highlights development and results of innovative tools for prediction and prescription of upsets and hazard events associated with upstream oil&gas production operations. This software can give recommendations to mitigate or avoid operational issues, maximizing the asset value, while maintaining the highest safety and environmental quality. The in-house tool is based on the integration of a big data analytics architecture and OSIsoft products. The workflow allows predicting future events and impact parameters. This is done thanks to a powerful machine-learning algorithm specifically selected for the physical problems analyzed. The inputs come from a heterogeneous data-lake, composed by historical data, real-time series, analysis, etc. all managed by PI based Digital Oilfield System. The tool is fed with field data, through PI, at high velocity and frequency, predicting potential events with prescription of possible actions to avoid production and asset integrity issues.