Training Introduction
The Field Production Optimization Using Agent Based Simulation Training Course is designed to provide participants with advanced techniques for optimizing oil and gas field operations without disrupting ongoing production. Real-world oil and gas systems are complex, involving exploration, production, and transportation processes that require careful planning and continuous improvement. Implementing changes in such systems can introduce risks, delays, and inefficiencies.
This Coventry Academy training course leverages Agent-Based Simulation (ABS) and multi-method modeling—including discrete event and system dynamics techniques—to create risk-free virtual environments. Participants will learn how to forecast well production, analyze decline curves, optimize production systems, and implement parameter changes safely in a simulated setting. Using AnyLogic simulation software, attendees will gain practical experience in modeling entire oil and gas fields, testing optimization strategies, and making informed decisions that enhance productivity, efficiency, and reliability.
Through hands-on exercises, guided modeling, and real-world case studies, this course ensures that participants can apply simulation techniques effectively to maximize field performance, improve planning, and minimize operational risk in oil and gas production systems.
Key Focus Areas of this Course:
- Fundamentals of petroleum production engineering and reservoir deliverability
- Forecasting well production and analyzing production decline
- Optimization techniques including linear, non-linear, and mixed-integer programming (MILP)
- Multi-method simulation using Agent-Based, System Dynamics, and Discrete Event modeling
- Practical application of AnyLogic software for process simulation and production optimization
- Integration of data acquisition and process modeling to improve production planning
- Scenario analysis, GIS connectivity, and performance evaluation
- Implementing optimal parameter values in oil and gas field systems for efficiency improvements
