Automatic and frequent calibration of steady state and dynamic models - facilitates an invaluable tool for the Production Engineer to provide fast and efficient decision-support, troubleshooting, production optimization, etc. when needed...and to prepare...
We deployed the BPT Digital Production Twins for an operating field at the Norwegian Continental Shelf operated by a major oil company. The complete twin solution was deployed in a Microsoft Azure cloud environment and included the following main automated application features:
- quality-check and correction of the production data received from plant historian (approx. 2500 sensor values)
- provision of dynamic asset component integrity limits
- performance monitoring of equipment
- calibration of steady state and dynamic simulator models of entire topside processing facility
In the following, the focus is on the later part on how the simulation models added value to field operations, split in steady state and dynamic mode.
Steady state model-based applications:
- Automatically determine full set of data including mass balance, flow rates and compositions (for current operation or for any other scenario)
- Investigate well combinations giving optimized product quality (taking into account constrains)
- Check possible re-routing of wells streams to different manifolds
- Optimize energy consumption and minimize CO2 emissions
- Test changes in operating mode (e.g. number of trains in operation)
- Perform generic steady state What-If scenarios
- Provide updated models for desktop users
Dynamic model-based applications:
- Tuning of PID-controller settings at simulator, before implementing in control system
- Analyze dynamic transitions when changing mode (e.g. number of trains in operation and setpoint selections)
- Real-time comparison between plant and dynamic model at component level to determine component performance deterioration. (e.g. heat exchangers, control valves and actuators)
- Simulate start-up, shut-downs and other dynamic scenarios prior to operational action
- Check and improve operational procedures
- Validate complicated operations and advanced control logics (e.g. automatic field start-up)
- Perform generic dynamic What-If scenarios
- Provide updated models for desktop users at a click of a button at any time
- Automatically provide compositional feed updates to dynamic simulation and flow assurance applications
Both the steady state and dynamic models could be used manually by the user or may as well be configured as automatic what-if, look-ahead or multi-run scenarios doing optimization etc.
The illustration above shows the overall architecture of the BPT Digital Production Twins. As part of the base solution layer, the reconciliation solver for sensor value correction running a full-fledge process simulator model. In the application layer, calibrated simulator models are available both in steady state and dynamic modes. These are typically used for different purposes by the production engineers in decision support, troubleshooting and production optimization.