Applications of Produced Water in
Biodiesel Production and
Distribution
Soumya Yadala,
Selen Cremaschi, PhD
The University of Tulsa
2015 International Petroleum Environmental Conference
Denver, CO
November 17-19, 2015
November 17, 2015
Presentation outline
2
1
Algae based-Biodiesel
2
Biodiesel Production
3
Research Objective
4
Mathematical Modeling
5
Results
6
Future directions
7
Questions?
Soumya Yadala, Selen Cremaschi
2015 IPEC
Motivation – Produced water
3
Introduction
Objectives
Methodology
Results
Conclusion
 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
Soumya Yadala, Selen Cremaschi
2015 IPEC
Advantages
4
Introduction
Objectives
Methodology
Results
Higher growth rates & productivities
CO2 capture
Higher oil yield
Algae biofuel
Food vs. fuel
Grown on non-arable land
and using produced water
No sulfur, non-toxic & biodegradable
Soumya Yadala, Selen Cremaschi
2015 IPEC
Conclusion
Challenges
5
Introduction
Objectives
Results
Methodology
Conclusion
High capital, operating & production costs
Relatively new technology
Variety of algae strains
Algae biofuel
Lack of optimal design of cultivation systems
Difficulty in scaling up
Soumya Yadala, Selen Cremaschi
2015 IPEC
Biodiesel Production
6
Introduction
Objectives
Results
Methodology
Selection of Algae Species
Conclusion
Varying oil content and specific growth rates
Selection of Location
Influences climatic conditions and sunlight
Algae Cultivation
Harvesting
Drying
Extraction
Transesterification
Soumya Yadala, Selen Cremaschi
2015 IPEC
Research Objective
7
Introduction
Objectives
Methodology
Soumya Yadala, Selen Cremaschi
2015 IPEC
Results
Conclusion
Optimization
8
Objectives
Introduction
Methodology
Results
Conclusion
Optimization focuses on finding the best solution from a set of available
alternatives subject to constraints.
Alternatives
Objective function
Objective
Function
To minimize the production, operating and
transportation costs of biodiesel
Optimization
Decision
Variables
Constraints
 Optimal algae cultivation systems
 Reliable supply chain network flow topology
of production and distribution centers
Alternatives
 Algae Species – I. galbana
 Cultivation Units – Raceway Ponds
 Geographical Locations – USA
 Routes
 Means of Transportation – Trucks, Rails, Barges, and Pipelines
Soumya Yadala, Selen Cremaschi
2015 IPEC
Alternatives - Locations
9
Introduction
Objectives
Methodology
Conclusion
Results
Supply
Texas
Mississippi
Alabama
Kentucky
Georgia
Oklahoma
Virginia
Arizona
North Carolina
South Carolina
Port
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
Houston
Demand
Gulf of Mississippi
Mobile
Paducah
Savannah
Tulsa
Norfolk
Phoenix
Wilmington
Charleston
Houston
Los Angeles
Philadelphia
Chicago
Toledo
Soumya Yadala, Selen Cremaschi
2015 IPEC
Houston
Los Angeles
Philadelphia
Chicago
Toledo
Alternatives – Means of Transportation
Objectives
Introduction
10
S
u
p
p
l
y
P
o
r
t
Methodology
E
x
t
r
a
c
t
i
o
n
Soumya Yadala, Selen Cremaschi
2015 IPEC
Results
E
s
t
e
r
i
f
i
c
a
t
i
o
n
Conclusion
D
e
m
a
n
d
Alternatives - Routes
11
Introduction
Supply
Objectives
Port
Methodology
Extraction
Soumya Yadala, Selen Cremaschi
2015 IPEC
Results
Transeste
rification
Conclusion
Demand
Decision Variables
12
Introduction
Methodology
Objectives
Results
DAProduced(Sloc),
NPond(Sloc),
TSApond(Sloc)
Supply
TransportTruck(Sloc,Ploc), NTruck(Sloc,Ploc)
DATransported(Ploc)
Port
Conclusion
Objective
Function
Optimization
Decision
Constraints
Variables
Alternatives
DAAvailable(Ploc)
TransportTruck,Rail,Barge(Ploc,Eloc), NTruck,Rail,Barge(Ploc,Eloc)
DATransported(Eloc)
Extraction
AOProduced(Eloc)
TransportTruck,Rail,Barge(Eloc,Tloc), NTruck,Rail,Barge(Eloc,Tloc)
AOTransported(Tloc)
Transesterification
BDProduced(Tloc)
TransportTruck,Rail,Barge,Pipeline(Tloc,Dloc), NTruck,Rail,Barge,Pipeline(Tloc,Dloc)
Demand
Soumya Yadala, Selen Cremaschi
2015 IPEC
Objective Function
13
Objectives
Introduction
Methodology
Min
10
1
n
n  0 1  MARR 
Z  CpCtPond  Ext  Trans  TranportCt  
Objective
Alternatives
Function
 ElecticCt

Optimization
 WaterCt



 LandCt
 Decision
Constraints
Variables


 OpCtPond  Ext  Trans 
Capital Costs
1%
1%
3%
0% 1% 1%
1% 5%
2%
3%
4%
Operating Costs
Site Preparation
Pond levees
3%
Paddle wheel
8%
Harvesting
4%
12%
Extraction
Nutrients
18%
Chemicals
19%
Flocculation
44%
Water & nutrient supply
Waste treatment
Buildings, roads, drainage
70%
Conclusion
Results
Electric Supply and distribution
Instumentation and machinery
Engineering and contingency
Soumya Yadala, Selen Cremaschi
2015 IPEC
Labor
Maintenance and repair
Operating supplies
Taxes and insurance
Constraints
14
Objectives
Introduction
Supply
Methodology
Conclusion
Results
Objective
Function
Optimization
DAProduced (Sloc), NPond(Sloc) Alternatives
TransportTruck(Sloc,Ploc)
n pond  DAproduced Sloc  TransportTruck Sloc,Ploc
Decision
Variables
Constraints
TransportTruck Sloc,Ploc  DAtransported Ploc
Port
DATransported (Ploc)
DAAvailable (Ploc)
TransportTruck,Rail,Barge(Ploc,Eloc)
DAtransportedPloc = DAavailablePloc
DryalgaeavailablePloc ≥ å TransportTruckPloc,Eloc + å TransportRailPloc,Eloc + å TransportBargePloc,Eloc
 Transport
Ploc
Eloc
Truck Ploc,Eloc
Eloc
Eloc
  Transport RailPloc,Eloc   Transport BargePloc,Eloc  DAtransported Eloc
Ploc
Ploc
Soumya Yadala, Selen Cremaschi
2015 IPEC
Constraints
15
Methodology
Objectives
Introduction
Extraction
DATransported(Eloc)
AOProduced(Eloc)
Objective
Function
Optimization
Alternatives
TransportTruck,Rail,Barge(Eloc,Tloc)
DAtransported Eloc 
Conclusion
Results
AOProduced Eloc
Decision
Variables
ηextracction  OCspecies
Constraints
AO produced Eloc   TransportTruck Eloc,Tloc   Transport RailEloc,Tloc   Transport BargeEloc,Tloc
 Transport
Tloc
Tloc
Truck Eloc,Tloc
Eloc
Tloc
  Transport RailEloc,Tloc   Transport BargeEloc,Tloc  AOtransported Tloc
Eloc
AOTransported(Tloc)
Eloc
Transesterification
BDProduced(Tloc)
TransportTruck,Rail,Barge,Pipeline(Tloc,Dloc)
AOtransported Tloc 
BDProducedTloc
 MWBD
3  ηtransesterification  
 MW
lipid





Soumya Yadala, Selen Cremaschi
2015 IPEC
Constraints
Methodology
Objectives
Introduction
16
Transesterification
AOTransported(Tloc)
 Transport
TruckTloc,Dloc
Dloc
Objective
Function
Optimization
Alternatives
BDProduced(Tloc)
TransportTruck,Rail,Barge,Pipeline(Tloc,Dloc)
BD produced Tloc 
Conclusion
Results
Decision
Variables
Constraints
  Transport RailTloc,Dloc
Dloc
  Transport BargeTloc,Dloc   Transport PipeTloc,Dloc
Dloc
Dloc
 Transport
TruckTloc,Dloc
Dloc
  Transport RailTloc,Dloc
Dloc
  Transport BargeTloc,Dloc   Transport PipeTloc,Dloc  Demand Dloc
Dloc
Dloc
Objective
Function
Optimization
Alternatives
Decision
Variables
GAMS
(General Algebraic Modeling System)
Constraints
Soumya Yadala, Selen Cremaschi
2015 IPEC
BARON
Results
17
Introduction
Objectives
Methodology
Results
Conclusion
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
Georgia
Savannah
Savannah
Toledo
Philadelphia
Soumya Yadala, Selen Cremaschi
2015 IPEC
Chicago
Results
18
Introduction
Objectives
Methodology
Production Costs
Raceway Pond Dimensions = Channel Depth = 1 m
Pond width = 3.5 m
Pond length = 300 m
Soumya Yadala, Selen Cremaschi
2015 IPEC
Results
Conclusion
TransportCt
CpCtPond
OpCtPond
WaterCt
CpCtTrans
OpCtTrans
CpCtExt
OpCtExt
LandCt
ElectricCt
Results
19
Introduction
Results
Methodology
Objectives
Supply
Conclusion
NTruck(Sloc,Ploc)
NPond(Sloc)
Texas
x
8.5000E6
=
8.5000E5 ha
Mississippi
x
8.5200E6
=
8.5200E5 ha
Alabama
x
8.8200E6
=
8.8200E5 ha
3.5821E5
Georgia
x
1.0665E7
=
1.0665E6 ha
4.3563E5
Soumya Yadala, Selen Cremaschi
2015 IPEC
3.7686E5
7.5971E6
Conclusions
20
Introduction
Objectives
Methodology
Results
Conclusion
 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
Soumya Yadala, Selen Cremaschi
2015 IPEC
Acknowledgement
21
Introduction
Objectives
Methodology
Results
Conclusion
 TUPSE Research Group
 Department of Chemical Engineering, The University of Tulsa
 IPEC
Soumya Yadala, Selen Cremaschi
2015 IPEC
THANK YOU
Questions???
Soumya Yadala, Selen Cremaschi
2015 IPEC
November17, 2015