Petroleum Refinery Process Modeling

Y.A. Liu, the Alumni Distinguised Professor and the Frank C. Vilbrandt Endowed Professor of Chemical Engineering at Virginia Tech, received his B.S. (1967), M.S. (1970), and Ph.D. (1974) degrees from National Taiwan University, Tufts University and Princeton University, respectively. Professor Liu devoted his school breaks helping petrochemical industries in developing countries and chemical industries in Virginia with technology development and engineering training. He has taught intensive training courses on computer-aided design, advanced process control, energy and water savings, and refinery and polymerization process modeling to over 7,000 practicing engineers in China, Taiwan and United States. Ai-Fu Chang received his Ph.D. in the Department of Chemical Engineering at Virginia Polytechnic Institute and State University (Virginia Tech) in September, 2011. He received his B.S. in chemical engineering from National Taiwan University in 2001. He completed his doctoral dissertation on integrated process modeling and product design of biodiesel manufacturing, and refinery reaction and fraction systems. The latter was the basis of this textbook. He has worked on several industrial modeling projects, including poly (acrylonitrile-vinyl acetate), hydrocracking, and biodiesel. These projects were collaborative efforts between Virginia Tech, Aspen Technology, and industrial manufacturers. He is currently employed by Chevron Phillips Chemical Company. Kiran Pashikanti was a PhD student in the Department of Chemical Engineering at Virginia Tech. He received his B.S. in chemical engineering from Virginia Commonwealth University in 2005, and his Ph.D. in chemical engineering from Virginia Tech in September, 2011. He has worked on several industrial modeling projects on integrated modeling of refinery reaction and fraction systems, and of carbon-dioxide capture processes. This textbook grows out of his doctoral dissertation on the predictive modeling of fluid catalytic cracking (FCC) and catalytic reforming processes. He is currently employed by Chevron Phillips Chemical Company.

• About the Authors xiiiForeword by Lawrence B. Evans xvForeword by Steven R. Cope xviiPreface xixAcknowledgments xxiiiScope of Textbook xxvSoftware Selection and Copyright Notice xxvii1 Characterization and Physical and Thermodynamic Properties of Oil Fractions 11.1 Crude Assay 11.1.1 Bulk Properties 21.1.2 Fractional Properties 61.1.3 Interconversion of Distillation Curves 71.2 Boiling Point-Based Hypothetical or Pseudocomponent Generation 81.3 Workshop 1.1 – Interconvert Distillation Curves 131.4 Workshop 1.2 – Extrapolate an Incomplete Distillation Curve 131.5 Workshop 1.3 – Calculate MeABP of a Given Assay 131.6 Workshop 1.4 – Represent an Oil Fraction by the Old Oil Manager in Aspen HYSYS Petroleum Refining 161.7 Workshop 1.5 – Represent an Oil Fraction by the New Petroleum Assay Manager in Aspen HYSYS Petroleum Refining 251.8 Workshop 1.6 – Conversion from the Oil Manager to Petroleum Assay Manager and Improvements of the Petroleum Assay Manager over the Oil Manager 321.9 Property Requirements for Refinery Process Models 331.10 Physical Properties 361.10.1 Estimating Minimal Physical Properties for Pseudocomponents 361.10.2 MolecularWeight 371.10.3 Critical Properties 381.10.4 Liquid Density 401.10.5 Ideal Gas Heat Capacity 421.10.6 Other Derived Physical Properties 431.11 ProcessThermodynamics 451.11.1 Process Thermodynamics 471.11.2 Mixed or Activity Coefficient-Based Approach 471.11.3 Equation-of-State Approach 491.12 Miscellaneous Physical Properties for RefineryModeling 501.12.1 Two Approaches for Estimating Fuel Properties 511.12.2 Flash Point 521.12.3 Freeze Point 521.12.4 PNA Composition 531.13 Conclusion 54Nomenclature 55Bibliography 562 Atmospheric or Crude Distillation Unit (CDU) 592.1 Introduction 592.2 Scope of the Chapter 602.3 Process Overview 602.3.1 Desalting 612.3.2 Preheat Train and Heat Recovery 622.3.3 Atmospheric Distillation 622.4 Model Development 652.4.1 MESH Equations 662.4.2 Overall Column Efficiency and Murphree Stage Efficiency 662.4.3 Recommendation for Correctly Handling the Efficiency 682.4.4 Inside-Out Algorithm for Distillation Column Calculation Convergence 692.5 Feed Characterization 722.6 Data Requirements and Validation 732.7 A Representative Atmospheric Distillation Unit 762.8 Building the Model in Aspen HYSYS Petroleum Refining 772.8.1 Entering the Crude Information 782.8.2 Selection of aThermodynamic Model 842.8.3 Crude Charge and Prefractionation Units 872.8.4 Atmospheric Distillation Column – Initial 882.8.5 Atmospheric Distillation Column – Side Strippers 952.8.6 Atmospheric Distillation Column – Pumparounds 982.8.7 Atmospheric Distillation Column – Adding Custom Stream Properties 1012.8.8 Post-Convergence 1042.9 Results 1052.10 Model Applications to Process Optimization 1092.10.1 Improve the 5% Distillation Point for an Individual Cut 1092.10.2 Change Yield of a Given Cut 1092.10.3 Workshop 2.1 – Perform Case Studies to Quantify the Effects of Stripping Steam Rate and Product Draw Rate 1112.11 Workshop 2.2 – Rebuild Model Using “Backblending” Procedure 1142.11.1 Import Distillation Data into Aspen HYSYS Oil Manager 1152.11.2 Define a New Blend of the Backblended Crude Feed 1162.11.3 Build the CDU Model Based on the Backblended Feed 1202.11.4 Converging Column Model 1202.11.5 Comparison of Results 1232.12 Workshop 2.3 – Investigate Changes in Product Profiles with New Product Demands 1262.12.1 Update Column Specifications 1262.12.2 Vary Draw Rate of LGO 1272.13 Workshop 2.4 – Investigate the Effects of Process Variables on Product Qualities 1292.14 Workshop 2.5 – Application of Column Internal Tools (Column Hydraulic Analysis) 1312.15 Workshop 2.6 – Application of the Petroleum Distillation Column 1402.16 Conclusions 144Nomenclature 145Bibliography 1453 Vacuum Distillation Unit 1473.1 Process Description 1473.2 Plant Data Reconciliation 1493.2.1 Required Data 1493.2.2 Representation of the Atmospheric Residue 1493.2.3 Makeup of Gas Streams 1523.3 Model Implementation 1543.3.1 Plant Data and Modeling Approaches 1553.3.2 Workshop 3.1 – Build the Simplified VDU Model 1573.3.3 Workshop 3.2 – Build the Rigorous Model from a Simplified Model 1653.4 Model Application – VDU Deep-Cut Operation 1723.5 Workshop 3.3 – Simulation of the VDU Deep-Cut Operation 176Bibliography 1804 Predictive Modeling of the Fluid Catalytic Cracking (FCC) Process 1834.1 Introduction 1844.2 Process Description 1854.2.1 Riser–Regenerator Complex 1854.2.2 Downstream Fractionation 1874.3 Process Chemistry 1884.4 Literature Review 1904.4.1 KineticModels 1904.4.2 Unit-LevelModels 1934.5 Aspen HYSYS Petroleum Refining FCC Model 1954.5.1 Slip Factor and Average Voidage 1964.5.2 21-Lump Kinetic Model 1974.5.3 Catalyst Deactivation 1984.6 Calibrating the Aspen HYSYS Petroleum Refining FCC Model 1994.7 Fractionation 2004.8 Mapping Feed Information to Kinetic Lumps 2034.8.1 Fitting Distillation Curves 2034.8.2 Inferring Molecular Composition 2054.8.3 Convert Kinetic Lumps to Fractionation Lumps 2084.9 Overall Modeling Strategy 2094.10 Results 2114.11 Applications 2204.11.1 Improving Gasoline Yield 2204.11.2 Increasing UnitThroughput 2234.11.3 Sulfur Content in Gasoline 2244.12 Refinery Planning 2254.13 Workshop 4.1 – Guide for Modeling FCC Units in Aspen HYSYS Petroleum Refining 2314.13.1 Introduction 2314.13.2 Process Overview 2314.13.3 Process Data 2314.13.4 Aspen HYSYS and Initial Component and Thermodynamics Setup 2314.13.5 Basic FCC Model 2384.13.6 FCC Feed Configuration 2414.13.7 FCC Catalyst Configuration 2464.13.8 FCC Operating Variable Configuration 2504.13.9 InitialModel Solution 2524.13.10 Viewing Model Results 2534.14 Workshop 4.2 – Calibrating Basic FCC Model 2584.15 Workshop 4.3 – Build the Model for Main Fractionator and Gas Plant System 2674.15.1 T201_MainFractionator 2674.15.2 OverheadWet Gas System, Primary Stripper Column T302_Stripper, and Debutanizer or Gasoline Stabilization Column T304_Stabilizer 2754.15.3 T301_Absorber, Primary Absorber and T303_ReAbsorber, Sponge Oil Absorber, or Reabsorption Column 2814.16 Workshop 4.4 – Perform Case Studies to Quantify Effects of Key FCC Operating Variables 2854.17 Workshop 4.5 – Generate Delta-Base Vectors for Linear Programming (LP)-Based Planning 2914.18 Conclusions 297Nomenclature 298Bibliography 2995 Predictive Modeling of Continuous Catalyst Regeneration (CCR) Reforming Process 3035.1 Introduction 3045.2 Process Overview 3045.3 Process Chemistry 3115.4 Literature Review 3135.4.1 KineticModels and Networks 3145.4.2 Unit-LevelModels 3175.5 Aspen HYSYS Petroleum Refining Catalytic Reformer Model 3195.6 Thermophysical Properties 3235.7 Fractionation System 3235.8 Feed Characterization 3245.9 Model Implementation 3285.9.1 Data Consistency 3295.9.2 Feed Characterization 3305.9.3 Calibration 3305.10 OverallModeling Strategy 3335.11 Results 3355.12 Applications 3405.12.1 Effect of Reactor Temperature on Process Yields 3415.12.2 Effect of Feed Rate on Process Yields 3445.12.3 Combined Effects on Process Yields 3455.12.4 Effect of Feedstock Quality on Process Yields 3465.12.5 Chemical Feedstock Production 3475.12.6 Energy Utilization and Process Performance 3495.13 Refinery Production Planning 3505.14 Workshop 5.1 – Guide for Modeling CCR Units in Aspen HYSYS Petroleum Refining 3545.14.1 Introduction 3545.14.2 Process Overview and Relevant Data 3545.14.3 Aspen HYSYS and Initial Component and Thermodynamic Setup 3565.14.4 Basic Reformer Configuration 3585.14.5 Input Feedstock and Process Variables 3625.14.6 Solver Parameters and Running the InitialModel 3685.14.7 Viewing Model Results 3705.14.8 Updating Results with Molecular Composition Information 3725.15 Workshop 5.2. – Model Calibration 3765.16 Workshop 5.3 – Build a Downstream Fractionation System 3875.17 Workshop 5.4. – Case Study to Vary RON and Product Distribution Profile 3955.18 Conclusion 400Nomenclature 400Bibliography 4026 Predictive Modeling of the Hydroprocessing Units 4056.1 Introduction 4066.2 Aspen HYSYS Petroleum Refining HCR Modeling Tool 4116.3 Process Description 4166.3.1 MP HCR Process 4166.3.2 HP HCR Process 4196.4 Model Development 4196.4.1 Workflow of Developing an Integrated HCR Process Model 4196.4.2 Data Acquisition 4216.4.3 Mass Balance 4216.4.4 Reactor Model Development 4246.4.4.1 MP HCR Reactor Model 4246.4.4.2 HP HCR Reactor Model 4306.4.5 Delumping of the Reactor Model Effluent and FractionatorModel Development 4356.4.5.1 Applying the Gauss–Legendre Quadrature to Delump the Reactor Model Effluent 4386.4.5.2 Key Issue of the Building FractionatorModel – Overall Stage Efficiency Model 4406.4.5.3 Verification of the Delumping Method – Gaussian–Legendre Quadrature 4406.4.6 Product Property Correlation 4426.5 Modeling Results of MP HCR Process 4446.5.1 Performance of the Reactor and Hydrogen Recycle System 4446.5.2 Performance of Fractionators 4456.5.3 Product Yields 4476.5.4 Distillation Curves of Liquid Products 4496.5.5 Product Property 4516.6 Modeling Results of HP HCR Process 4546.6.1 Performance of the Reactor and Hydrogen Recycle System 4546.6.2 Performance of Fractionators 4556.6.3 Product Yields 4556.6.4 LPG Composition and Distillation Curves of Liquid Products 4596.6.5 Product Property 4626.7 Model Applications 4646.7.1 H2-to-Oil Ratio versus Product Distribution, Remained Catalyst Life, and Hydrogen Consumption 4646.7.2 WART Versus Feed Flow Rate Versus Product Distribution 4666.8 Model Application – Delta-Base Vector Generation 4686.9 Workshop 6.1 – Build a Preliminary Reactor Model of HCR Process 4716.10 Workshop 6.2 – Calibrate Preliminary Reactor Model to Match Plant Data 4816.11 Workshop 6.3 – Case Studies 4976.12 Workshop 6.4 – Fractionation System for HCR Reactor 5056.13 Conclusion 512Nomenclature 513Bibliography 5147 Alkylation, Delayed Coking, and Refinery-Wide Simulation 5177.1 Alkylation 5177.1.1 Process Description 5177.1.2 Feed Components and Alkylation Kinetics 5187.1.3 Workshop 7.1 – Hydrofluoric Acid Alkylation Process Simulation 5197.2 Delayed Coking 5287.2.1 Process Description 5287.2.2 Feed Characterization, Kinetic Lumps, and Coking Reaction Kinetics 5297.2.3 Workshop 7.2 – Simulation and Calibration of a Delayed Coking Process 5307.2.4 Workshop 7.3 – SimplifiedModel of Delayed Coker by Petroleum Shift Reactor for Production Planning Applications 5427.3 Refinery-Wide Process Simulation 5487.3.1 Refinery-Wide Process Model: A Key to Integrating Process Modeling and Production Planning 5487.3.2 An Example of a Refinery-Wide Process Simulation Model 5497.3.3 Tools for Developing Refinery-Wide Process Models 5517.3.4 Deployment and Applications of the Refinery-Wide Process Models for Process Engineering and Production Planning 5517.4 Conclusions 553Bibliography 554List of Computer Files 555Index 559