Refinery Planning & Economics (LP Modelling) Training Course

Course Overview

Learning Objectives

• Analyze the drivers of refinery economics, including crude and product prices, crack spreads, yields, operating costs, and margins, on Day 1.
• Evaluate refinery configurations, complexity, and the role of process units in determining product yields and value.
• Interpret crude assays and apply crude valuation and breakeven analysis to support crude selection.
• Explain process unit yields, capacities, operating constraints, and their representation in planning models.
• Apply product specifications and blending principles for gasoline, diesel, jet fuel, fuel oil, and other products.
• Apply linear programming fundamentals, including objective functions, decision variables, constraints, and feasibility.
• Interpret LP results, including marginal values, reduced costs, ranging, and sensitivity analysis.
• Describe refinery LP model structure, including crude and process submodels, delta-base representation, recursion, and hydrogen and fuel balances.
• Build and run a simplified refinery LP model in Excel to optimize crude slate, unit operations, and product slate.
• Apply LP models to strategic, annual, and monthly planning, turnaround impacts, and investment and margin improvement studies.
• Validate models through backcasting and conduct plan-versus-actual analysis to identify margin gaps.
• Evaluate the impact of emissions, carbon costs, and energy transition trends on refinery planning and economics by the end of Day 5.

Who Should Attend

Learning Outcomes

• By the end of the course, participants will be able to:
• Explain how refineries make money and what drives margins.
• Assess how refinery configuration affects profitability.
• Use crude assays to value crudes and compare alternatives.
• Describe how process units and constraints are represented in planning models.
• Apply product specifications and blending rules in planning.
• Formulate simple linear programming problems.
• Interpret marginal values, reduced costs, and sensitivity results.
• Explain how refinery LP models are structured and why recursion is needed.
• Build and use a simplified refinery LP model in Excel.
• Use LP models for planning, turnaround, and investment decisions.
• Validate LP models and analyze plan-versus-actual performance.
• Consider emissions and carbon costs in refinery planning.

Course Outline