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Water Management in a Petroleum Refinery

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Presentation on theme: "Water Management in a Petroleum Refinery"— 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 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

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, Cin, etc.

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

6 Water Treatment Units Regeneration processes* Regeneration process
Type of contaminant removed Maximum outlet concentration (ppm) API Separator Organics 50 Activated Carbon Adsorption Reverse Osmosis Salts 20 Chevron Waste Water Treatment H2S NH3 5 30 Biological Treatment 230 *Typical 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

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 Buoyancy force Gravity Drag force

9 Chevron Wastewater Treatment
Sour water containing H2S and NH3 enter into a hydrogen sulfide stripper Steam absorbs H2S from passing liquid stream Wastewater is sent to a distillation column where NH3 is stripped

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 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 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

13 Reverse Osmosis Flux of water molecules through membrane: JW=kW (∆P - ∆π) Where: Jw=apparent volumetric flux of water (L/m2s) kw= mass transfer coefficient of water molecules (L/m2s.atm) ∆P= change in external pressure (atm) ∆π= change in osmotic pressure (atm)

14 Reverse Osmosis Flux of salt solute through the membrane is:
JS = ks (ΔC) where: JS = mass flux of solute (kg/m2s) kS = mass transfer coefficient of solute (L-S/m2)

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)

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

17 Reverse Osmosis Accuracy <0.005% error For N membranes
Assume small membrane (negligible area/membrane) Accuracy <0.005% error CpN-1 CF0 CF2 CF1 CFN Cp Cp1 ΔA N=1 N=2 N

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

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

20 Activated Carbon Adsorption
Klinkenberg approximate solution Accuracy: <0.6% error 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 H2S stripper, NH3 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 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

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

24 Outlet Concentration Models
Chevron Wastewater Treatment (H2S Stripper) Modeled as a distillation column in PRO/II with a partial reboiler Points 1-8: Varied Cin, NH3 Points 9-57: Varied T Points : Varied η Points : Varied Cin, H2S Points : Varied N R2 ≈ 0.99

25 Outlet Concentration Models
Chevron Wastewater Treatment (NH3 Stripper) Modeled as a distillation column in PRO/II with a partial reboiler and a partial condenser Points 1-8: Varied Cin, 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 Cin, H2S Points 84-89: Varied RFR R2 ≈ 0.98

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

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

28 Outlet Concentration Models
Desalter (salts) Points 1-7: Varied Points 8-14: Varied Points 15-21: Varied Cin Points 22-27: Varied Voltage Points 28-34: Varied Points 35-41: Varied Voltage field gradient Permittivity is a measure of the material’s ability to transmit or “permit” an electric field.

29 Outlet Concentration Models
Desalter (H2S) Final equation: Distribution coefficient is a measure of differential solubility of the compound between these two solvents:

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 1. % error between simulation result and regressed equation Figure 2. Linear regression between simulated results and developed equations

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

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

33 GAMS Model Fixed Outlet Concentrations Fixed Outlet Efficiency
Cout, regeneration process = Cout, regeneration process Fixed Outlet Efficiency Cout, regeneration process = Cin, regeneration process * (1 – η) Modeled Outlet Concentrations

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

35 Process Flow Diagram

36 Results Fixed Outlet Concentrations Modeled 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, H2S, Ammonia): (100, 100, 10, 100) ppm

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

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

39 Questions?

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

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 cg dVg = cs dVs     Cg Cs

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

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

44 Derivation of osmotic pressure
W=pdVg For two components in a reversible process p dVg = п dVs   From the previous equation:       cg dVg = cs dVs The equation for pressure is   p (cs / cg ) dVs = p dVs   Cg Cs W=пdVs

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

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