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Water Management in a Petroleum Refinery by: Amy Frink, Timilehin Kehinde, and Brian Sellers.

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Presentation on theme: "Water Management in a Petroleum Refinery by: Amy Frink, Timilehin Kehinde, and Brian Sellers."— Presentation transcript:

1 Water Management in a Petroleum Refinery by: Amy Frink, Timilehin Kehinde, and Brian Sellers

2 Background In refineries, water is a crucial part in removal of contaminants from crude oil ▫Desalting ▫Steam cracking ▫Sweetening ▫Hydrotreating ▫Distillation 2 Crude fractionation unit

3 Background Water re-use as a practical way to reduce freshwater intake ▫Reduces wastewater treatment costs ▫Lessens need to comply with government standards for pollution levels ▫Relieves need to obtain larger amounts of freshwater (costly and limited) ▫Promotes a greener environment 3

4 Goals Mathematical programming becoming main approach to solving water allocation problem ▫Optimize stream placement between water-using and wastewater treatment processes by performing mass and contaminant balances ▫Current methods rely on assumption of fixed outlet concentrations ▫However, outlet concentration has shown to be a function of pressure, temperature, C in, etc. 4

5 Refinery Schematic Highlights water-using and regeneration processes 5 Red: Water-using units Green: Conventional water regeneration processes (i.e. end-of-pipe treatment)

6 Water Treatment Units Regeneration processes* 6 Regeneration process Type of contaminant removed Maximum outlet concentration (ppm) API SeparatorOrganics50 Activated Carbon Adsorption Organics50 Reverse OsmosisSalts20 Chevron Waste Water Treatment H 2 S NH Biological TreatmentOrganics230 *T YPICAL REFINERY STANDARDS

7 API Separator API separator ▫Separates suspended solids and oil from wastewater streams based on differences in specific gravities between the oil and the wastewater ▫Particles settle based on Stokes Law 7

8 API Separator Contaminant particles fall through the viscous fluid by their own weight Upward drag of small particles (assumed to be spheres) combines with the buoyancy force balances the gravitational force and creates a settling velocity 8 Buoyancy force Gravity Drag force

9 Chevron Wastewater Treatment Sour water containing H 2 S and NH 3 enter into a hydrogen sulfide stripper Steam absorbs H 2 S from passing liquid stream Wastewater is sent to a distillation column where NH 3 is stripped 9

10 Biological Treatment Microorganisms present in wastewater will feed on the carbonaceous organic matter in the wastewater and repopulate in an aquatic aerobic environment With a sufficient oxygen supply and an organic material food supply, the bugs (bacteria) will consume and metabolize the organic waste and transform it into cell mass, which settles in the bottom of a settling tank 10 Pseudomonas

11 Activated Sludge Air is pumped through the bottom of an aeration tank ▫Air rises and provides oxygen to the water Effluent is sent through a secondary clarifier that separates the used cellular material from the treated wastewater 11 Activated Sludge schematic

12 Reverse Osmosis Dissolved solutes are removed from a wastewater by a pressure- driven membrane High pressure applied at the feed creates differential pressure between the permeate and feed sides of the membrane 12

13 Reverse Osmosis Flux of water molecules through membrane: J W =k W (∆P - ∆π) Where: J w =apparent volumetric flux of water (L/m 2 s) k w = mass transfer coefficient of water molecules (L/m 2 s.atm) ∆P= change in external pressure (atm) ∆π= change in osmotic pressure (atm) 13

14 Reverse Osmosis Flux of salt solute through the membrane is: J S = k s (ΔC) where:J S = mass flux of solute (kg/m 2 s) k S = mass transfer coefficient of solute (L-S/m 2 ) 14

15 Reverse Osmosis Using van’t Hoff equation, the osmotic pressure is given as: π=cRT where: c = concentration of solute in feed/permeate (mol/L) R = gas constant ~ L.atm/(g-mol.K) T = temperature of solution (K) 15

16 Reverse Osmosis The flow rate of water molecules in permeate Flux of solutes is related to water flux by the equation Mathcad was used to generate data points Mathcad snapshot- Reverse Osmosis 16

17 Reverse Osmosis For N membranes Assume small membrane (negligible area/membrane ) Accuracy <0.005% error 17 C pN-1 C F0 C F2 C F1 C FN CpCp C p1 ΔAΔA N=1N=2N

18 Activated Carbon Adsorption A fixed bed of activated carbon adsorbs organics in wastewater The bed of activated carbon is regenerated using ▫Pressure-swing desorption ▫Thermal-swing desorption 18

19 Activated Carbon Adsorption Assumptions made ▫Isothermal and isobaric operation ▫Fixed bed adsorption ▫Langmuir isotherm for adsorption used At equilibrium: At saturation: 19 Mass transfer zone in column

20 Activated Carbon Adsorption Klinkenberg approximate solution Accuracy: <0.6% error 20 Dimensionless distance coordinate Dimensionless time coordinate corrected for displacement Excel sheet generated for ACA fixed bed

21 Simulation methods PRO/II was used to model H 2 S stripper, NH 3 stripper, and atmospheric distillation column Inlet stream parameters and system properties were varied and outlet concentrations measured MathCad generated points for input into GAMS for the API separator and reverse osmosis system 21 Snapshot of PRO/II crude oil distillation column Atmospheric distillation tower

22 Simulation methods Steady ▫Calculates a plant-wide mass balance and general dimensions of the unit processes involved Snapshot of Steady program 22

23 Outlet Concentration Models API Separator ▫Particles follow a normal distribution in size ▫Travel with a velocity that contains a horizontal and a vertical component ▫Furthermore, they are assumed to follow a uniform distribution along the height at which they enter Equation 1. Horizontal and vertical time component Equation 2. Mass fraction contaminants removed 23

24 Outlet Concentration Models Chevron Wastewater Treatment (H 2 S Stripper) Modeled as a distillation column in PRO/II with a partial reboiler Points 1-8: Varied C in, NH3 Points 9-57: Varied T Points : Varied η Points : Varied C in, H2S Points : Varied N R 2 ≈

25 Outlet Concentration Models Chevron Wastewater Treatment (NH 3 Stripper) 25 Modeled as a distillation column in PRO/II with a partial reboiler and a partial condenser Points 1-8: Varied C in, NH3 Points 10-58: Varied F Points 59-65: Varied η Points 66-71: Varied P Points 72-76: Varied N Points 77-83: Varied C in, H2S Points 84-89: Varied RFR R 2 ≈ 0.98

26 Outlet Concentration Models Biological Treatment 26 Modeled as an activated sludge system in Steady involving 1 source stream and 2 effluents Points 1-23: Varied C in Points 24-31: Varied biomass yield Points 32-38: Varied k d Points 39-45: Varied MCRT (mean cell residence time) Points 46-52: Varied MLVSS/MLSS

27 Outlet Concentration Models Crude oil distillation column 27 Modeled in PRO/II as a distillation column Points 1-50: Varied crude feedrate, F crude Points : Varied steam temperature, T Points : Varied steam flowrate, F steam Points : Varied efficiency, η Points : Varied x in, organics

28 Outlet Concentration Models Desalter (salts) 28 Points 1-7: Varied Points 8-14: Varied Points 15-21: Varied C in Points 22-27: Varied Voltage Points 28-34: Varied Points 35-41: Varied Voltage field gradient

29 Outlet Concentration Models Desalter (H 2 S) ▫Final equation: ▫Distribution coefficient is a measure of differential solubility of the compound between these two solvents: 29

30 Reliability of equations Varied parameters for 15 points in simulation Compared equation to simulation results Any equations with ≤5% error were used to generate tables as input to GAMS Figure 2. Linear regression between simulated results and developed equations Figure 1. % error between simulation result and regressed equation 30

31 GAMS Model GAMS: General Algebraic Modeling System Wastewater Model Solvers ▫MIP: Mixed Integer (Linear) Program  CPLEX Solver ▫rMIP: Relaxed Mixed Integer (Linear) Program  CPLEX Solver ▫MINLP: Mixed Integer (Non-Linear) Program  DICOPT Solver 31

32 GAMS Model Objective Functions ▫Cost  Cost = Annual Operation Cost + Annual Fixed Cost ▫Freshwater Usage  Consumption = Freshwater to water-using units + Freshwater to regeneration units 32

33 GAMS Model Fixed Outlet Concentrations ▫C out, regeneration process = C out, regeneration process Fixed Outlet Efficiency ▫C out, regeneration process = C in, regeneration process * (1 – η) Modeled Outlet Concentrations ▫ 33

34 GAMS Model 400,000+ Non-zero terms 1,200+ Non-linear, non-zero terms 1-5 hours to run 17,298 lines of code 34

35 Process Flow Diagram 35

36 Results Fixed Outlet Concentrations ▫Cost: $1,220,000 ▫Consumption: 33 tons/hour Modeled Outlet Concentrations ▫Cost: $950,000 ▫Consumption: 31 tons/hour Model Constraints ▫Flow Rates: 250 tons/hour ▫Contaminant Outlet Concentrations (Salts, Organics, H 2 S, Ammonia): (100, 100, 10, 100) ppm 36

37 Conclusions Water re-use can provide a means to save on operating costs while positively impacting the environment Non-linear models of the outlet concentration of contaminants provides a more accurate model to represent refinery waste water regeneration Equipment costs of the water-using units are a function of inlet concentrations and flow rates, as well as design parameters 37

38 Further Studies Enter outlet concentration models for the water- using units Define more specific concentrations limits in and out of the units, as well as flow rates ranges Define better investment and operating costs Compare actual data from a petroleum refinery with theoretical model results 38

39 Questions? 39

40 Derivation of osmotic pressure The blue line acts as a membrane which is permeable to water but blocks gas passage The green line acts as a membrane which allows the passage of gas 40

41 Derivation of osmotic pressure Van’t Hoff constructed a closed, isothermal, reversible process If the blue membrane moves up, the static membrane moves down to equilibrate system c g dV g = c s dV s 41 Cg Cs

42 Derivation of osmotic pressure Gibb’s free energy of the system G(T, p, N i ) = U + p V - T S U= internal energy S=entropy T=temperature 42 Cg Cs

43 Derivation of osmotic pressure In a reversible process at constant temperature and pressure DG = S i (∂G / ∂N i ) dN i = 0 where: ∂G / ∂N i is the energy used to remove component (i) from the system studied 43 Cg Cs

44 Derivation of osmotic pressure For two components in a reversible process p dV g = п dV s From the previous equation: c g dV g = c s dV s The equation for pressure is p (c s / c g ) dV s = p dV s 44 Cg Cs W=пdVs W=pdVg

45 Derivation of osmotic pressure Then p (c s / c g ) = п By ideal gas law; p = c g R T Also, п = c g R T 45 Cg Cs W=пdVs W=pdVg

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