Refinery Supply Chain Optimization Hiren Shethna Stephen Wagner GLOBAL REFINING SUMMIT 2014 Barcelona © Copyright 2014, Saudi Aramco. All rights reserved. 1 Outline  Saudi Aramco Operations  Modeling for Refinery Assets  Conclusion 2 Background: Company Profile  National Oil Company of Saudi Arabia.  Over 54,000 employees.  One of the World’s largest oil companies.  A fully-integrated oil and gas company with affiliates, joint ventures and subsidiaries around the world. Korea China United States Japan Yanbu Jubail Dhahran 3 Saudi Aramco Operations 4 Enterprise-wide Optimization Minimize raw material cost Information Refinery Products Petroleum Base Oils Fuel Gases Maximize high value products Solvents Gasoline Kerosene Diesel Fuel Oil Lubricants Waxes NGL Methanol Petroleum EB / Styrene Refinery Products Minimize operating cost Polypropylene Polyethylene Consistently over long period of time 5 Challenges Faced Information • Spread across different sources and in different formats. Data Quality • Instrument measurement errors. Planning Accuracy • Consistency of plan and operations. • Investment planning (short- or long-term). Operational Issues • Day to day operational issues. • Shutdown planning/execution. Control Tuning Change Management • Maintenance of controller. • Connecting the plan to the set points. • Continuous change in people. 6 6 HIGH FIDELITY ASSET MODELS HAVE A KEY ROLE TO PLAY IN OPTIMIZING REFINERY PLANNING AND OPERATIONS 7 High Fidelity Model Requirements • Sustainable (at low cost) • Develop • Train • Evolve • Maintain • Serve multiple users/functions 8 9 10 11 Realistic pressure effects in columns. Pump-around and preheat train interactions. Impact of crude switches. Furnace limitations and fuel gas consumption. Preheat train/column retrofit scenarios. One model that serves multiple functions. Custom Excel interface. One model to evolve/maintain. 12 High Fidelity Model Requirements • Sustainable (at low cost) • Develop • Train • Evolve • Maintain • Serve multiple users/functions 13 13 Asset Models help with Optimization Information • Spread across different sources and in different formats. Data Quality • Instrument measurement errors. Planning Accuracy • Consistency of plan and operations. • Investment planning (short- or long-term). Operational Issues • Day to day operational issues. • Shutdown planning/execution. Control Tuning Change Management • Maintenance of controller. • Connecting the plan to the set points. • Continuous change in people. 14 14 Process Systems Modeling Spectrum • Data reconciliation • Integration • Simulation • Process Optimization • Inferential modeling Planning & Scheduling Process synthesis • Multi-site planning • Process Control Dynamic & Hydraulic Analysis CFD Molecular Modeling Consistency between each level important 15 Developing reduced order sub-models Light Naphtha Net Gas Naphtha LPG One approach requires LP independents be moved one at a time. Kero LP independent variables move simultaneously in operation. E100 Reformer Crude N2A Yield Reformate Independent variables in LP and operation are different. E100 Crude Unit Naphtha Splitter Stabilizer 16 Developing reduced order sub-models LPG Not usually sampled Naphtha VGO Hydrocracker - I Diesel Vacuum Column Main Fractionator Not all LP independents are sampled. LP independent variables move simultaneously in operation. Independent variables in LP and operation are different. Hydrocracker - II 17 Use of high fidelity simulation models to update planning models WHAT Sustainable WHY Complement information from plant HOW Develop integrated refinery unit models Regress models from plant data Provide validity to plant data Sufficient detail on unit operations Serve multiple functions Inherently material balanced Internal tool to generate LP sub-model 18 Light Gas Conversion Naphtha Yields Yields Yields Hydrocracker sub-model Selectivity Diesel Process Simulation Model (using Hydrocracker model) Light Gas Naphtha Fidelity Transition Diesel Light Gas CFR Naphtha Diesel Planning Model 19 Optimization of investment decisions Gasoline Blending Crude A Crude B D I S T I L L A T I O N Gasoline Isomerization Aromatics Complex Aromatics Reforming Diesel Blending Diesel Hydrocracking Fuel Oil Blending Fuel Oil Visbreaking Simplified Refinery Representation 20 Investment Decision Workflow Develop simulation model of the new process •Model development. •Calibrate conversion units. •Validate the feeds and product results with licensor results. LP model development •Reconcile the PIMS feed with HYSYS feed. •Develop the LP submodels for columns and conversion units. •Reconcile overall PIMS results vs. HYSYS results. Refinery optimization •Used for shut down scenarios. •Tankage optimization. •Is the overall design optimal under various future operating scenarios? Feedback 21 Asset Models Help with Optimization Information • Spread across different sources and in different formats. Data Quality • Instrument measurement errors. Planning Accuracy • Consistency of plan and operations. • Investment planning (short- or long-term). Operational Issues • Day to day operational issues. • Shutdown planning /execution. Control Tuning Change Management • Maintenance of controller. • Connecting the plan to the set points. • Continuous change in people 22 22 Reformer Operations Support Catalyst Deactivation Reformer Unit Simulation Model Recycle Compressor Optimization Custom user interface with model in background Combined Feed Heater Enhancement 23 Reformer Catalyst Deactivation Feed 1 WAIT vs Days 20 Temperature Coke 15 10 5 0 0 100 200 300 400 Days Feed 2 Days 95RON 93RON Coke 97RON 18 16 14 12 10 8 6 4 2 0 0 100 200 300 400 Days 24 Reuse of naphtha reformer model Model developed to improve planning. H2 Recycle Need to know the impact of change in H2 recycle. Conventional approach follows rebuilding model as required. Naphtha Reformate to Stabilizer This approach involves reuse, upgrade, and retrain as required. 25 Asset Models Help with Optimization Information • Complement by being source of good and consistent data. Data Quality • Provide validity to instrument measurement. Planning Update • Act as link between planning and operations. Operational Issues Control Tuning Change Management • Help with various aspects of plant operations. • Help with establishing steady state gains. • Become a common medium of communication. 26 26 Model Management HANDS ON TRAINING SESSIONS 27 Challenges in Detailed Asset Models Data • Good data required for good models. Established Work Processes • Difficult to make asset models part of established workflows. Model Management • Keeping models ever-green is resource intensive. Training • Making it easy for model users requires sustained effort. Software Capability Work internally to strive for continuous improvement • Ability of existing software to achieve desired results. 28 28 Double Bond Equivalent Molecular Level Data Quality Carbon # 29 Challenges in Detailed Asset Models Data • Good data required for good models. Established Work Processes • Difficult to make asset models part of established workflows. Model Management • Keeping models ever-green is resource intensive. Training • Making it easy for model users requires sustained effort. Software Capability • Ability of existing software to achieve desired results. Work internally to strive for continuous improvement Work with software vendor for continuous improvement 30 30 Conclusion  We are actively working on the optimization of the company’s HC value chain in refining.  Improving the process of achieving value through advanced process modeling technologies.  Work on leading edge process modeling technology.  Deploy leading edge process technology through sustainable model development and maintenance.  Enabling better decisions by conversion of data into information using first principle models 31