Modelling, Simulation and Optimization of Refining Processes


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Presentation of Jacques Niederberger for the "Workshop Virtual Sugarcane Biorefinery"

Apresentação de Jacques Niederberger realizada no "Workshop Virtual Sugarcane Biorefinery "

Date / Data : Aug 13 - 14th 2009/
13 e 14 de agosto de 2009
Place / Local: ABTLus, Campinas, Brazil
Event Website / Website do evento:

Published in: Business, Technology
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Modelling, Simulation and Optimization of Refining Processes

  1. 1. Modelling, Simulation and Optimization of Refining Processes Jacques Niederberger, M.Sc. PETROBRAS Research & Development Center (CENPES) August/2009
  2. 2. Summary Introduction Oil characterization Modelling Refining Processes Optimization Aspects
  3. 3. Introduction: PETROBRAS operations and R&D
  4. 4. PETROBRAS AN INTEGRATED ENERGY COMPANY Total Investments: 15 Refineries US$ 29 billion in 2008 Installed Capacity: 2.125 million bpd Natural Gas Production: Employees: 74,204 420 thousand boe per day Net Operating Revenues US$ 127 billion (2008) Proved Reserves : Oil Production:15.1 billion barrels of oil 1,980 thousands barrels perand gas equivalent (boe) day (bpd) of oil and LPG Natural Gas Sales: Gas stations: 6,485 65 million m3/d Thermoeletric Energy Plants : 10 Installed Capacity : 1,912 MW Dec 2004
  6. 6. R&D EXPENDITURES 2.000 1.750 1.500 1.250R$ MM 1.000 750 500 250 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 CENPES Ano 137 Laboratories EXAMPLES OF MAIN CHALLENGES 14 TECHNOLOGY PROGRAMS  Ultra deep water production technology  Production in the Pre-salt sequence  Lower environmental impact products  Better output products Optimization Pre-salt &  Zero discharge / zero emissions processes Reliability
  7. 7. TECHNOLOGICAL INTEGRATION R&D CENTERTypes: Types: Contracts and agreements with Universities  Joint Industry Projects and Research Centers  Cooperating Research  Strategic Alliances National networks of excellence - about  Technology Interchange different oil & gas themesOver 120 Brazilian Institutions Over 70 International Institutions
  8. 8. Oil Characterization
  9. 9. • What is oil ?• Where does it come from ?
  10. 10. EXPERIMENTAL DATAComplete assay contains: Distillation curve Specific Gravity curve Light end contents Viscosity Sulphur, nitrogen and metals contents Other properties
  11. 11. TRADITIONAL CHARACTERIZATION PROCEDURETrue Boiling Point Curve - TBP• Product withdraws at constant volume or at constant temperature• Near ideal fractionation• Long time demanded, high cost
  12. 12. TRADITIONAL CHARACTERIZATION PROCEDURE Crude Oil TBPtemperature, Co % vaporized
  13. 13. TRADITIONAL CHARACTERIZATION PROCEDURE Crude Oil TBPtemperature, C o % vaporized
  14. 14. TRADITIONAL CHARACTERIZATION PROCEDURE Distillation curve, Specific gravity Pseudo-components Characterization MethodPseudo-component: fake component, oil fraction.Crude oil and its derivatives are hydrocarbons mixtures, well described by cubic equations of state (SRK, PR)The characterization method provides pseudo-component properties: Tc, Pc, w, PM, d60, Teb, etc.
  15. 15. IMPROVED CHARACTERIZATIONInstead of pseudocomponents, real molecules.• Group of molecules typically present in a determined fraction• Bulk properties: distillation curve and specific gravity• Mixture composition obtained through an optimization method
  16. 16. Modelling Refining Processes
  18. 18. EFFECTS OF THE CHARACTERIZATION METHOD Processes involving chemical reactions:  Heavy Feedstock → Gases + Light Distillates + Medium Distillates + unconverted or  Heavy Feedstock + H2 → Organic Gases + H2S + NH3 + Light Distillates + Medium Distillates + unconverted
  19. 19. EFFECTS OF THE CHARACTERIZATION METHODHow to model chemical reactions ?Kinetics x ThermodynamicsKinetics: reaction order, kineticparametersThermodynamics: Gibbs free energy
  20. 20. EFFECTS OF THE CHARACTERIZATION METHODEither Kinetics or Thermodynamicsrequire pure component data.Pseudo-component approach:not good!Compositional approach:no big deal!
  21. 21. EFFECTS OF THE CHARACTERIZATION METHODIf we characterize using molecules:
  22. 22. EFFECTS OF THE CHARACTERIZATION METHOD•How to build phenomenologicalmodels of conversion processesdealing with pseudocomponents ?•Relating the overall conversion andproduct profile to bulk properties ofthe feedstock and processconditions.
  23. 23. REFINING PROCESSES MODELLING•We model phase equilibrium andseparation process with the traditionaltools provided by Thermodynamics•And for the conversion processes webuild semi-empirical models
  24. 24. REFINING PROCESSES MODELLING•Main conversion processes:FCC – fluid catalytic crackingDelayed CokingHydrotreatingHCC – catalytic hydrocracking
  25. 25. REFINING PROCESSES MODELLINGFor instance, in the FCC process:Gasoil → Combustible gas + LPG +Naphta + LCO + DO + coke•Overall conversion depends on:feedstock propertiescatalyst propertieshardware geometryprocess conditions
  26. 26. REFINING PROCESSES MODELLING•Product profile depends on:feedstock propertiescatalyst propertieshardware geometryprocess conditions•Product properties depend on: ...
  27. 27. REFINING PROCESSES MODELLINGHow do we address any other effectnot directly taken into account by thesemi-empirical model ?Introducing adjustable tuningparameters in the model.Process data is necessary for fittingthe parameters.
  28. 28. REFINING PROCESSES MODELLINGQuality of the model predictionsequals the quality of process andfeedstock data
  29. 29. Optimization Aspects
  30. 30. REFINING PROCESSES OPTIMIZATIONWhat does optimization mens ?Generally speaking, any improvementin a process with a few degrees offreedom may be called optimization.From our point of view, optimization isfinding THE best solution, in a systemwith one ore more degrees of freedom.
  31. 31. SCOPE X TIME SCALE Task Scope Time horizonPlanning operations and All the eleven Petrobras’ 5 to 20 years The scope of the optimization problem andinvesments for the next refineries the time horizon varies in the sameyears direction.Designing a new plant One or more units of a 5 years refineryPlanning the production One single refinery Monthly, weeklyof a sigle industrial plantOptimizing operating Crude distillation + FCC Every 1 or 2 hoursconditions of one or converter + FCCmore units of a single fractionation section of aplant refinery
  32. 32. SCOPE X MODEL COMPLEXITY The largerTask scope, the simpler must be the Model typePlanning operations and investments for the Linear models (linear the years programming)Planning the production of an entire refinery Linear models (linear programming)Designing a new unit Rigorous mixed integer-non- linear models (MINLP)Optimizing operating conditions of one or Rigorous non-linear modelsmore units of a single plant
  33. 33. OPTIMIZATION & PROCESS DESIGN Design Synthesis Initial estimates Decision variables Analysis Mass & energy balances OptimizationEquipment sizing and cost estimates Parametric Structural Optimization Optimization Economic Evaluation Final Design
  36. 36. OPERATING CONDITIONS OPTIMIZATION - RTOMany plants don’t have a much stableoperation.Optimal conditions for onedetermined run may not be the bestfor another run.If optimization is off-line, we need tore-optimize for every different run.
  37. 37. OPERATING CONDITIONS OPTIMIZATION - RTOImagine if we had an optimizationmachine that could read process dataat real time, tune automatically theprocess model, run automatically theoptimization problem and sendautomatically the optimal conditionsfor the digital control system …That would be Real Time Optimization -RTO.
  38. 38. RTO STRUCTURE Hibernation Steady State DetectionNo Stationary ? Yes Model tuning OptimizationNo Solution obtained? Yes New setpoints for the control system
  39. 39. RTO benefitsReal Time Optimization PETROBRAS experience: RTO implemented on Distillation and FCC Units using Equation Oriented and Sequential Modular approaches
  40. 40. RTO benefitsReal Time Optimization FCC Example: Operational modifications (Reaction temperature, Feed temperature and Main Fractionator top reflux) due to RTO
  41. 41. RTO Challenges RTO runs only when the unit is Steady  but what is Steady State?  commercial applications use a kind of statistical approach (mean, std dev, Student and F-test) along with some heuristics (“tuning factor”) on a set of the most representative variables (temperatures and flow rates linked to the unit heat and mass balance)  do we really have to wait Steady-State?  it can take 1-2 hours between runs  if a disturbance enters the unit in between  no RTO run  maybe for a long period  Change the “tuning factor” or improve APC / Regulatory control
  42. 42. RTO ChallengesReal Time Optimization How to deal with the “unknown” feed composition (especially in Distillation)?  Online analyzers  NMR or NIR?  Lab analysis  frequence? Methods?  Feed Reconciliation  as long as you have confidence on the model, use it as an analyzer  Redistribute the amount of the pseudocomponents in order to match some information from the unit (operations and product quality)  It is an optimization problem  maybe the most difficult one (more than the profit optimization)
  43. 43. RTO ChallengesReal Time Optimization Non convergence tracking: it is a hard task, sometimes, to find out the origin of the failure, especially, when it is not associated with instrumentations or well-known process problems Initialization techniques Scaling: heuristic rules X numerical analysis of the system Integrating multiple process unities: how to deal with the increasing problem size to get the most of integrated unities optimization and its flexibilities?  How to deal with non convergence?
  44. 44. RTO ChallengesReal Time Optimization Entire plant rigorous RTO – feasible, but still not possible Multi-scale Optimization: integration and information exchange between different optimization levels is an issue that demands more attention Dynamic RTO: it is still an open issue  Computational efforts?  Numerical issues?  How to implement it on industrial applications?
  45. 45. Questions ?