An Interactive 5-Day Training Course
Digital Twin & Operator Training Simulators for Production
Smarter Production Through Digital Twins
Secure your spot now!
Duration
5 Days
Price
$ 3,500
Starting From
13 Sep 2027
Digital Twin & Operator Training Simulators for Production
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Digital Twin & Operator Training Simulators for Production - PE-DTS-PEA27
| Code | Date | Time | Duration | Location | Currency | Early Bird Fee Per Person |
|---|---|---|---|---|---|---|
| PE-DTS-PEA27 | 13 - 17 Sep 2027 | 10 AM CST | 4 Hours Per Day |
Online |
USD |
3500 |
Need this for a group? We deliver the same course in-house — face-to-face at your location or online — tailored to your assets and team level. Contact info@peassociations.com.
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Digital Twin & Operator Training Simulators for Production
Description
The Digital Twin & Operator Training Simulators for Production course provides an intermediate-level understanding of digital twin technologies and operator training simulators for oil and gas production systems. Participants will learn about digital twin architecture, live data integration, model calibration, predictive maintenance, virtual metering, and production optimisation.
The course also covers simulator design, control system replication, scenario development, emergency response training, and competence assessment. It equips production, operations, process, and facilities engineers, along with training and digital technology professionals, to evaluate, implement, and maintain these technologies for improved operational performance and safer decision-making.
A digital twin is a model of a physical production system that is kept current with live data and used to answer questions about that system: what is happening now, what happens if a setting changes, what has changed since the model was built. An operator training simulator reproduces plant or well behaviour realistically enough for operators to learn and practise on it without risk.
The first half covers twin concepts, architecture, model fidelity, data connection, calibration and applications. The second half covers simulator models, control system replication, scenario design, competence assessment, implementation and value.
- Define digital twin concepts and distinguish levels of fidelity and scope.
- Describe digital twin architecture, data flows and integration requirements.
- Select model types appropriate to the intended application.
- Connect, synchronise and calibrate models against live data.
- Apply digital twins to condition monitoring, virtual metering and what-if analysis.
- Apply digital twins to optimisation and predictive maintenance.
- Specify operator training simulator models and control system replication.
- Design training scenarios, including upsets and emergency situations.
- Use simulators for competence assessment and training programmes.
- Plan implementation, maintenance and value assessment for both tools.
- Improve operator competence in upset and emergency handling.
- Reduce start-up and commissioning problems through simulator training.
- Support predictive maintenance and optimisation with model-based insight.
- Assess digital twin and simulator proposals with realistic expectations.
- Budget for model upkeep as well as the initial build.
- Understand what digital twins are and what they can do.
- Specify model type, data and calibration requirements.
- Understand operator training simulator design and scenario development.
- Use simulators for competence development and assessment.
- Evaluate implementation and value cases.
- Tell a current, calibrated twin from a model with a new name.
- Production engineers
- Operations engineers
- Process engineers
- Facilities engineers
- Training and competence staff
- Control and automation engineers
- Digital and technology teams
- Operations supervisors and trainers
Module 01: Digital Twin Concepts
- Definitions and levels of digital twin
- Scope: well, facility, field and asset twins
- Fidelity and purpose
- What a twin is not
Module 02: Architecture and Data
- Twin architecture and components
- Live data connection and synchronisation
- Historians and data quality requirements
- Latency and update frequency
- Integration with existing systems
Module 03: Model Types
- Data-driven models
- Steady state process and well models
- Dynamic process models
- Hybrid approaches
- Selecting fidelity for the application
Module 04: Calibration and Maintenance
- Calibrating models against measured data
- Detecting model drift
- Recalibration cadence
- Managing changes to the physical asset
- Model governance and ownership
Module 05: Monitoring and Prediction Applications
- Condition monitoring and anomaly detection
- Virtual metering and soft sensors
- Equipment performance degradation tracking
- Predictive maintenance applications
Module 06: Decision Support Applications
- What-if and scenario analysis
- Production optimisation
- Constraint and debottlenecking analysis
- Supporting start-up and shutdown decisions
Module 07: Operator Training Simulators
- Purpose and scope of training simulators
- Dynamic model requirements
- Control system replication and emulation
- Instructor station and facilities
- Fidelity requirements for training value
Module 08: Scenario Design and Training Delivery
- Normal operations scenarios
- Upset, trip and emergency scenarios
- Well control and production scenarios
- Scenario difficulty and progression
- Debriefing and feedback
Module 09: Competence, Implementation and Value
- Competence assessment using simulators
- Integration with training programmes
- Implementation planning and cost
- Ongoing maintenance requirements
- Measuring value delivered
Upon successful completion of this training course, delegates will be awarded an official Certificate of Completion issued by the Petroleum Engineers Association (PEA), an ISO 9001:2015 certified training organization. The certificate carries 10 Credits and formally records the total learning hours completed.
Each certificate is signed by the Course Facilitator and the CEO of the Petroleum Engineers Association, and serves as verifiable proof of professional training that delegates can present to employers and professional bodies worldwide.
Frequently Asked Questions
All course bookings made through PEA are strictly non-refundable. By registering for a course, you acknowledge and accept that all fees are payable in full and are not subject to refund under any circumstances, including changes in personal or professional commitments or partial attendance.
PEA reserves the right to make reasonable adjustments to course content, trainers, or schedules where necessary, without entitling delegates to a refund. Comprehensive details of each course — including objectives, target audience, and content — are clearly outlined before enrolment, and it is the responsibility of the delegate to ensure the course's suitability prior to booking.
For any inquiries related to cancellations or bookings, please contact our support team, who will be happy to assist you.
