Demo

Implementation of PIPER Operational Intelligence Platform at Perupetro

Talara, Peru

  • Company:

PERUPETRO S.A.

  • Location:

Talara, Peru

Implementation of PIPER Operational Intelligence Platform for Perupetro, integrating 9 data-collection interfaces from flow computers, SCADA systems, industrial historians and APIs. The solution centralized and contextualized hydrocarbon batch information through a hierarchical operational model, reused common properties through element templates and implemented Analytics to calculate daily, biweekly and monthly production. The project delivered more than 78 PIPER View visualization views for inspection monitoring, operational control and reporting.

  • Challenges
  • Integrate data from different flow computers, multiplexers, SCADA systems and oil and gas contractor historians.
  • Implement connections through multiple industrial protocols and technologies.
  • Ensure secure communication, data persistence and data forwarding after communication interruptions.
  • Recover historical data from flow computers and automatically synchronize information after connectivity failures.
  • Consolidate hydrocarbon batch information in a centralized repository.
  • Represent operational information according to the hierarchical structure of the batches and their attributes.
  • Standardize similar properties and variables to avoid repetitive configuration.
  • Execute a large number of calculations to generate daily, biweekly and monthly production indicators.
  • Develop dashboards and reports for inspection monitoring and operational control.
  • Solution

PIPER Operational Intelligence Platform

Implementation of the PIPER operational intelligence infrastructure in a cloud environment using:

  • PIPER Historian: storage and management of real-time and historical industrial data.
  • PIPER Modeler: hierarchical modeling, batch contextualization and Analytics configuration.
  • PIPER Forms: management of operational information and manual records, where applicable.
  • PIPER View: visualization of production indicators, variables and operational reports.

Data Collection and Industrial Integration

Implementation of 9 data-collection interfaces for the different hydrocarbon batches using:

  • Rocklink ROC809L.
  • ROC800.
  • Fisher ROC Plus Serial.
  • Fisher ROC Plus Ethernet.
  • FloBoss 100.
  • OPC DA.
  • Modbus TCP.
  • REST API.

The solution integrated data from flow computers, multiplexers, SCADA systems and industrial historians.

Operational Modeling and Contextualization

A hierarchical operational model was developed in PIPER Modeler, using elements to represent hydrocarbon batches and their corresponding attributes, variables and operational properties.

Element templates were used to reuse common properties and structures across batches, supporting model standardization and simplifying the creation of new elements.

Collected data was associated with the corresponding elements and attributes through the following contextualization structure:

Batch → Attribute → Industrial Variable → Calculation → Production Indicator

Analytics and Production Calculations

Several Analytics were developed in PIPER Modeler to execute the calculations required by the inspection process.

The Analytics combined direct variables, historical data and calculation expressions to generate:

  • Daily production.
  • Biweekly production.
  • Monthly production.
  • Cumulative production.
  • Indicators calculated from flow computer variables.

PIPER’s analytical and recalculation capabilities also enabled the processing of historical information for selected time periods and the updating of the corresponding indicators.

Visualization and Reporting

A Production by Batch dashboard was developed in PIPER View, using the hierarchical structure defined in PIPER Modeler.

The solution included more than 78 visualization views presenting:

  • Production indicators by batch.
  • Direct and calculated variables.
  • Historical trends.
  • Batch comparisons.
  • Trend, scatter, bar and pie charts.
  • Daily, biweekly and monthly reports.
  • PDF export of visualization views.
  • Results
  • 9 data-collection interfaces implemented to integrate data from different industrial equipment and systems.
  • More than 78 visualization views developed in PIPER View.
  • Hierarchical operational model representing hydrocarbon batches and their attributes.
  • Element templates used to reuse common properties and structures.
  • Analytics implemented to calculate daily, biweekly and monthly production indicators.
  • Production by Batch dashboard developed on top of the operational model.
  • Centralized cloud repository for consolidating operational information.
  • Initial storage capacity of at least 1 TB, with room for expansion.
  • Historical data recovery and synchronization mechanisms for communication failures.
  • Operational reports exportable to PDF to support the inspection process.
  • Gallery
  • Key Benefits
  • Improved availability and centralization of hydrocarbon batch information.
  • Integration of heterogeneous industrial data sources into a common platform.
  • Greater continuity and reliability of data collection.
  • Automatic recovery of historical information after communication interruptions.
  • Standardization of properties and variables through reusable templates.
  • Reduced repetitive configuration of operational elements.
  • Automated and consistent calculation of production indicators.
  • Contextualized visualization of production by batch.
  • Access to real-time and historical information for analysis and control.
  • Easier comparison of batches and review of operational trends.
  • Availability of daily, biweekly and monthly reports.
  • Scalable architecture for additional data sources and operational requirements.

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