Applications of Produced Water in Biodiesel Production and Distribution

Transcription

1 Applications of Produced Water in Biodiesel Production and Distribution Soumya Yadala, Selen Cremaschi, PhD The University of Tulsa November 17, International Petroleum Environmental Conference Denver, CO November 17-19, 2015

2 Presentation outline 2 1 Algae based-biodiesel 2 Biodiesel Production 3 Research Objective 4 Mathematical Modeling 5 6 Future directions 7 Questions?

3 Motivation Produced water 3 Methodology Salty water trapped in the reservoir rock and brought up along with oil or gas during production These waters exist under high pressures and temperatures It can contain very minor amounts of chemicals, oil, and metals Every year in the United States about 800 billion gallons of produced water is brought to the surface along with oil and gas and about 98% of this water is routinely disposed as a waste product However, these large quantities of saline water have great potential value for algal biofuel production Scientists recently were successful in conducting the first pilot-scale test of algae growth using water from an oil-production well in Jal, New Mexico

4 4 Advantages Methodology Higher growth rates & productivities CO 2 capture Higher oil yield Algae biofuel Grown on non-arable land and using produced water Food vs. fuel No sulfur, non-toxic & biodegradable

5 5 Challenges Methodology High capital, operating & production costs Variety of algae strains Relatively new technology Algae biofuel Lack of optimal design of cultivation systems Difficulty in scaling up

6 6 Biodiesel Production Methodology Selection of Algae Species Varying oil content and specific growth rates Selection of Location Influences climatic conditions and sunlight Algae Cultivation Harvesting Drying Extraction Transesterification

7 7 Research Objective Methodology

8 8 Optimization Optimization focuses on finding the best solution from a set of available alternatives subject to constraints. Alternatives Decision Variables Optimization Alternatives Objective Function Methodology Objective function To minimize the production, operating and transportation costs of biodiesel Optimal algae cultivation systems Reliable supply chain network flow topology of production and distribution centers Algae Species I. galbana Cultivation Units Raceway Ponds Geographical Locations USA Routes Means of ation Trucks, Rails, Barges, and Pipelines

9 9 Alternatives - Locations Supply Texas Mississippi Alabama Kentucky Georgia Oklahoma Virginia Arizona North Carolina South Carolina Port Methodology Houston Gulf of Mississippi Mobile Paducah Savannah Tulsa Norfolk Phoenix Wilmington Charleston Extraction Houston Gulf of Mississippi Mobile Paducah Savannah Tulsa Norfolk Phoenix Wilmington Charleston Houston Los Angeles Philadelphia Chicago Toledo Transesterification Demand Houston Gulf of Mississippi Mobile Paducah Savannah Tulsa Norfolk Phoenix Wilmington Charleston Houston Los Angeles Philadelphia Chicago Toledo Houston Los Angeles Philadelphia Chicago Toledo

10 10 Alternatives Means of ation Methodology S u p P o E x t r a E s t e r i D e p p l y o r t a c t i o n f i c a t i o n m a n d

11 Alternatives - Routes 11 Methodology Supply Port Extraction Transeste rification Demand

12 12 Decision Variables DAed(Ploc Ploc) Supply Port Methodology DAProduced(Sloc), N Pond (Sloc), TSA pond (Sloc) Truck (Sloc,Ploc), N Truck (Sloc,Ploc) DAAvailable(Ploc) Objective Alternatives Function Optimization Decision Variables Truck,Rail,Barge Truck,Rail,Barge (Ploc,Eloc Ploc,Eloc), N Truck,Rail,Barge (Ploc,Eloc) DAed(Eloc Eloc) Extraction AOProduced(Eloc) Truck,Rail,Barge Truck,Rail,Barge (Eloc,Tloc Eloc,Tloc), N Truck,Rail,Barge (Eloc,Tloc) AOed(Tloc) Transesterification BDProduced(Tloc) Demand Truck,Rail,Barge,Pipeline Truck,Rail,Barge,Pipeline (Tloc,Dloc Tloc,Dloc), N Truck,Rail,Barge,Pipeline (Tloc,Dloc)

13 13 Min Z = CpCt Objective Function Pond + Ext + Trans + TranportCt + Capital Costs 10 n= 0 1 1% 0% 1% 2% Site Preparation 5% 1% 3% 1% 1% Pond levees 4% 3% Paddle wheel 70% 8% Harvesting Flocculation Extraction 1 ( + MARR) Water & nutrient supply Waste treatment Buildings, roads, drainage Methodology Electric Supply and distribution Instumentation and machinery Engineering and contingency n ElecticCt + WaterCt + LandCt + OpCt Pond + Ext + Trans 4% 12% 44% Objective Alternatives Function Optimization Decision Variables Operating Costs 3% 18% 19% Nutrients Chemicals Labor Maintenance and repair Operating supplies Taxes and insurance

14 14 n pond DA produced Sloc Supply Methodology DAProduced (Sloc), N Pond (Sloc) Truck (Sloc,Ploc) Truck = DA Sloc,Ploc transporte d Ploc Truck Sloc,Ploc Objective Alternatives Function Optimization Decision Variables DAed (Ploc) Port DAAvailable (Ploc) Truck,Rail,Barge (Ploc,Eloc) DA transportedploc = DA availableploc TruckPloc,Eloc + RailPloc,Eloc + BargePloc,Eloc Dryalgae availableploc Eloc Eloc Eloc Truck + Rail Ploc,Eloc + Ploc,Eloc Barge = Ploc,Eloc Ploc Ploc Ploc DA transported Eloc

15 15 AO Eloc DAed(Eloc Eloc) produced Eloc Extraction Methodology AOProduced(Eloc) Truck,Rail,Barge (Eloc,Tloc) AOProduced Eloc DAtransported Eloc = ηextracction OCspecies Truck + Rail + Eloc,Tloc Eloc,Tloc Tloc Tloc + Objective Alternatives Function Optimization Decision Variables Tloc Truck Rail + Barge = Eloc,Tloc Eloc,Tloc Eloc,Tloc Eloc Eloc AO Barge Eloc,Tloc transported Tloc AOed(Tloc) Transesterification BDProduced(Tloc) AO transported Tloc = 3 η Truck,Rail,Barge,Pipeline (Tloc,Dloc) BD Produced transesterification Tloc MW MW BD lipid

16 16 Alternatives Alternatives Objective Function Objective Function Decision Variables Decision Variables Optimization Optimization Methodology Transesterification AOed AOed(Tloc Tloc) BDProduced BDProduced(Tloc Tloc) Truck,Rail,Barge,Pipeline Truck,Rail,Barge,Pipeline (Tloc,Dloc Tloc,Dloc) Pipe Barge Dloc Rail Dloc Truck Tloc produced Tloc,Dloc Tloc,Dloc Tloc,Dloc Tloc,Dloc BD Dloc Pipe Dloc Barge Tloc,Dloc Tloc,Dloc Dloc Dloc Pipe Dloc Barge Dloc Rail Dloc Truck Demand Tloc,Dloc Tloc,Dloc Tloc,Dloc Tloc,Dloc Alternatives Alternatives Objective Function Objective Function Decision Variables Decision Variables Optimization Optimization GAMS (General Algebraic Modeling System) BARON

17 17 Methodology Supply Port Extraction Transeste rification Demand Texas Houston Houston Houston Houston Mississippi Gulf of MS Gulf of MS Gulf of MS Los Angeles Alabama Mobile Mobile Philadelphia Kentucky Chicago Georgia Savannah Savannah Toledo Philadelphia

18 18 Methodology Production Costs Raceway Pond Dimensions = Channel Depth = 1 m Pond width = 3.5 m Pond length = 300 m Ct CpCtPond OpCtPond WaterCt CpCtTrans OpCtTrans CpCtExt OpCtExt LandCt ElectricCt

19 19 Methodology Supply Texas x N Pond (Sloc) E6 = E5 ha N Truck (Sloc,Ploc) E5 Mississippi x E6 = E5 ha E6 Alabama x E6 = E5 ha E5 Georgia x E7 = E6 ha E5

20 s 20 Methodology A mathematical framework is developed to estimate the best combination of algae species, geographical location, and raceway pond geometry by combining experimentally validated temperature, irradiance, and algae growth models with optimization Model the network flow topology of algae oil distribution in the United states Future directions Model the dynamic behavior of algae biomass cultivation using HYSYS simulation software

21 Acknowledgement 21 Methodology TUPSE Research Group Department of Chemical Engineering, The University of Tulsa IPEC

22 THANK YOU Questions??? November17, 2015