COURSE OVERVIEW:

Crude assay interpretation and refinery planning are the foundational pillars of economic optimization in the downstream oil and gas industry. This course provides a detailed exploration of how the physical and chemical properties of crude oil, as documented in a laboratory assay, directly influence refinery configuration and product yields. Participants will learn to navigate complex assay data sheets, interpreting key indicators such as API gravity, sulfur content, distillation curves, and metal concentrations to determine the suitability of a crude for specific process units.

The scope of this training bridges the gap between raw data and commercial strategy by introducing the principles of Linear Programming (LP) and refinery modeling. Attendees will examine how planners use assay data to forecast the output of high-value products like gasoline, jet fuel, and diesel versus lower-value residuals. The course emphasizes the importance of understanding "crude flexibility," teaching participants how to evaluate the economic trade-offs of processing discounted opportunity crudes that may present technical challenges like high acidity or salt content.

Coverage includes the integration of refinery constraints into the planning process, such as unit capacities, utility availability, and environmental regulations. Participants will explore the supply chain elements of refinery planning, including crude acquisition, inventory management, and product blending requirements. By mastering the art of assay interpretation and the logic of refinery economics, professionals will be equipped to make data-driven decisions that maximize the gross product margin while maintaining plant integrity and safety.

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

1.  Decode and interpret a comprehensive crude oil assay laboratory report.

2.  Calculate the impact of API gravity and sulfur content on refinery yields.

3.  Utilize True Boiling Point (TBP) curves to estimate product volume fractions.

4.  Identify the technical risks associated with high-TAN and high-metal crudes.

5.  Explain the role of Linear Programming in refinery economic optimization.

6.  Evaluate the compatibility of different crude oils for refinery blending.

7.  Assess the impact of crude quality on the performance of secondary units like the FCC.

8.  Forecast refinery margins based on crude costs and product market prices.

9.  Identify bottlenecks in refinery configurations using assay-driven simulations.

10.  Manage the trade-offs between crude throughput and product quality specifications.

11.  Understand the logistics of crude procurement and supply chain timing.

12.  Formulate a basic refinery production plan based on market demand.

13.  Conduct a sensitivity analysis on the impact of crude price fluctuations on profitability.

TARGET AUDIENCE:

Refinery Planners, Commercial Analysts, Process Engineers, Crude Traders, and Operations Managers involved in feed selection and production scheduling.

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximise the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.