Why choose this training course
The oil refining process is one of the most complex processes in today’s industry, as it incorporates catalyst systems, complex reactor designs, sophisticated computer control hardware and software, and advanced safety and environmental controls.
A typical medium-size refinery has hundreds of pumps, heat exchangers and drums; dozens of furnaces, compressors, and high temperature/high pressure reactors; and thousands of control loops and associated computer control technologies. In order to optimize these complex systems and their interactions approach to single point or single system optimizing cannot work as effectively as we hope, as the refinery has to be considered as a system, rather than connection of its parts. Here is where the multi-method simulation comes to play an important part, as we can use Discrete Event, Agent Based and System Dynamics simulation to incorporate all the refinery systems into one and be able to have the outputs from the system, as well as its components, rather than just having an output from one of the components.
This training course will feature:
- Explanation of refinery process
- Basis of Discrete Event, Agent Based and System Dynamics simulation
- Establishing relationships between measurements and reservoir properties
- How to minimize overall operating costs while achieving the maximum possible “upgrade” for each hydrocarbon molecule (called “molecule management”)
- Hands-on practice in AnyLogic software for all three methods of simulation
- Advanced concepts: AnyLogic fluid library, incorporating operator performance
Who is this training course for?
This Coventry Academy training course is designed for all professionals working in the field of data analysis, oil and gas exploration, geology and reservoir modelling and will greatly benefit:
- Process engineers
- Refinery schedulers
- Planners and managers
- Data Scientists
- Data Analysts
- Petroleum engineers
- Refinery Plant Engineers
How will this training course be presented?
This Coventry Academy training course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes presentation of theoretical concepts, video lectures and many exercises that will be done through the guided work of the delegates themselves. The delegates will use free Personal Learning Edition AnyLogic software to create models and define and select statistics.
Course Outline
Day One: Refinery Process:
- Basics of Petroleum refining industry
- Refinery Configuration
- Distillation Processes
- Coking and Thermal Processes
- Catalytic Processes
- Cracking Processes
- Alteration Processes
- Treatment Processes
- Product Blending
- Mathematical Programming in Refining
Day Two: Multi-method Simulation:
- Discrete Event Simulation Modeling
- System Dynamics Simulation Modeling
- Agent Based Simulation Modeling
- Introduction to AnyLogic software
- Exercise: First model development in AnyLogic software
- Multi-method modeling and its application to refinery process
- Exercise: Multi-model creation in AnyLogic
Day Three: Petroleum Refinery Planning:
- Characterization, Physical and Thermodynamic Properties of Oil Fractions
- Crude Assay
- Bulk properties
- Fraction properties
- Regression-Based Planning
- Artificial-Neural-Network-Based Modeling
- Exercise: using fluid library in AnyLogic
Day Four: Planning Under Uncertainty for a Single Refinery:
- Deterministic Model Formulation
- Stochastic Model Formulation
- Sampling Methodology
- Objective Function Evaluation
- Variance Calculation
- Demand Uncertainty
- Process Yield Uncertainty
- Variation Coefficient
- Exercise: Refinery plant model creation in AnyLogic
Day Five: Integration with Petrochemical Supply Chain:
- Refinery and Petrochemical Synergy Benefits
- Delivery of crude oil to refinery
- Exercise: Connecting the delivery process with refinery process
- Exercise: Calculating outputs and statistics
- Exercise: Optimization results of the system as a whole
- Areas of application for multi-method-based simulation