Field Production Optimization
using Agent Based Simulation

Field production optimization using agent based simulation is a specialist skill set that gives petroleum engineers and production professionals a decisive advantage in how they model, analyse, and improve oilfield performance.

This course moves from petroleum production fundamentals through to multi-method simulation — covering discrete event, system dynamics, and agent-based models built within AnyLogic software.

You will work through reservoir deliverability, wellbore performance, and production decline analysis before progressing into optimization techniques including linear programming, MILP, and controllable rig time loss.

The final days focus on oilfield process modelling, GIS connectivity, scenario analysis, and incorporating worker performance into simulation models — including application to FEED engineering.

Practical exercises run throughout every day, ensuring the technical content is applied, not just understood.

This field production optimization using agent based simulation course is structured to take delegates from petroleum engineering fundamentals through to advanced simulation modelling and output-driven optimization.

By the end of this course, delegates will be able to:

• Analyse petroleum production systems — Apply knowledge of reservoir deliverability, wellbore performance, and fluid properties to production forecasting.
• Conduct production decline analysis — Use established techniques to model and forecast well production over time.
• Apply optimization techniques — Work with linear programming, non-linear programming, and MILP to optimise production variables.
• Build simulation models in AnyLogic — Create discrete event, system dynamics, and agent-based models using AnyLogic software.
• Model oilfield processes — Define oil production processes, gather operational data, and determine data distributions for simulation input.
• Use the AnyLogic fluid library — Build simulation models that replicate oilfield fluid behaviour and supply chain flows.
• Run scenario and output analysis — Compare outputs across scenarios and use GIS connectivity to enhance model relevance.
• Incorporate worker performance modelling — Integrate human performance variables into multi-method simulation models.
• Apply simulation to FEED engineering — Follow a structured methodology for applying multi-method simulation within front-end engineering and design.

This field production optimization using agent based simulation course is designed for professionals involved in petroleum production, reservoir engineering, and oilfield operations who need to apply simulation-based tools to real optimization challenges.

This course is suitable for:

• Petroleum Engineers — Those working with production systems, wellbore performance, and reservoir deliverability who need advanced modelling capability.
• Production Engineers — Professionals responsible for optimising field output and managing controllable production losses.
• Reservoir Engineers — Specialists who need to integrate simulation tools into production forecasting and decline analysis workflows.
• Process Engineers — Engineers involved in oilfield process design who want to model and test production scenarios before implementation.
• Simulation and Modelling Analysts — Technical professionals building or improving agent-based and multi-method simulation models for oil and gas applications.
• FEED Engineers — Those working in front-end engineering and design who need structured simulation methodology for production planning.
• Operations and Planning Professionals — Personnel involved in oil supply chain management and field-level production planning.

This field production optimization using agent based simulation course is delivered through a combination of structured technical instruction and hands-on software exercises — ensuring delegates can build and apply models, not just understand the concepts behind them.

Delivery methods include:

• Instructor-Led Technical Sessions — Expert-led instruction covers petroleum production fundamentals, optimization techniques, and simulation methodology in a clear, structured sequence.
• AnyLogic Software Exercises — Delegates work directly in AnyLogic throughout the course, building models from introductory simulations through to full agent-based and fluid library models.
• Process Modelling Workshops — Structured exercises guide delegates through creating discrete event models, agent-based models, and multi-method simulations step by step.
• Oilfield Case Application — Delegates apply modelling techniques to oil production process definition, data gathering, and supply chain review using realistic oilfield scenarios.
• Scenario and Output Analysis — Practical sessions cover output comparison, GIS connectivity, and worker performance integration within simulation models.
• FEED Engineering Application Review — The course closes with a structured review of how multi-method simulation is applied within front-end engineering and design workflows.

• AZTech Certificate of Completion for delegates who attend and complete the training course