The use of the streamline-based method for reservoir management is receiving increased interest in recent years because of its computational advantages and intuitive appeal for reservoir simulation, history matching and rate allocation optimization. Streamline-based method uses snapshots of flow path of convective flow. Previous studies proved its applicability for convection dominated process such as waterflooding and tracer transport. However, for a case with gas injection with strong capillarity and gravity effects, the streamline-based method tends to lose its advantages for reservoir simulation and may result in loss of accuracy and applicability for history-matching and optimization problems.
In this study, we first present the development of a 3D 3-phase black oil and compositional streamline simulator. Then, we introduce a novel approach to incorporate capillary and gravity effects via orthogonal projection method. The novel aspect of our approach is the ability to incorporate transverse effects into streamline simulation without adversely affecting its computational efficiency. We demonstrate our proposed method for various cases, including CO2 injection scenario. The streamline model is shown to be particularly effective to examine and visualize the interactions between heterogeneity which resulting impact on the vertical and areal sweep efficiencies.
Next, we apply the streamline simulator to history matching and rate optimization problems. In the conventional approach of streamline-based history matching, the objective is to match flow rate history, assuming that reservoir energy was matched already, such as pressure distribution. The proposed approach incorporates pressure information as well as production flow rates, aiming that reservoir energy are also reproduced during production rate matching.
Finally, we develop an NPV-based optimization method using streamline-based rate reallocation algorithm. The NPV is calculated along streamline and used to generate diagnostic plots of the effectiveness of wells. The rate is updated to maximize the field NPV. The proposed approach avoids the use of complex optimization tools. Instead, we emphasize the visual and the intuitive appeal of streamline methods and utilize flow diagnostic plots for optimal rate allocation.
We concluded that our proposed approach of streamline-based simulation, inversion and optimization algorithm improves computational efficiency and accuracy of the solution, which leads to a highly effective reservoir management tool that satisfies industry demands.
Skin factor is a dimensionless parameter that quantifies the formation damage around the wellbore. it also can be negative (which indicates improvement in flow) OR positive (which means formation damage exists). Positive skin can lead to severe well production issues and thus reducing the well revenue
Apresentação de Victor Manuel Salazar Araque, da Computer Modelling Group, durante o evento promovido pelo Sistema FIEB, Fundamentos da Exploração e Produção de Não Convencionais: a Experiência Canadense.
I hope this presentation helps you to understand why we use acidizing process and calculations needed to perform the optimum acidizing .
Any questions contact me at karim.elfarash@std.suezuniv.edu.eg
Skin factor is a dimensionless parameter that quantifies the formation damage around the wellbore. it also can be negative (which indicates improvement in flow) OR positive (which means formation damage exists). Positive skin can lead to severe well production issues and thus reducing the well revenue
Apresentação de Victor Manuel Salazar Araque, da Computer Modelling Group, durante o evento promovido pelo Sistema FIEB, Fundamentos da Exploração e Produção de Não Convencionais: a Experiência Canadense.
I hope this presentation helps you to understand why we use acidizing process and calculations needed to perform the optimum acidizing .
Any questions contact me at karim.elfarash@std.suezuniv.edu.eg
The acidizing is pumping of the acids into the wellbore to remove near well formation damage and other damaging substances, matrix acidizing is applied primarily to remove skin damage that caused by drilling, completion, work over, well killing or injection fluids.
This project is concerned with carbonate reservoirs that exceeded in Kurdistan subsurface formations.
Conduct a case study using real industrial data of Arab-D formation (Ghawar oil field – Saudi Arabia) which has five water wells were treated with 50 gallon of HCl acid The treatment acid was placed with coiled tubing and foam was used as diverter. The foam was made from nitrogen, water and surfactants.
Water injection pressure, injection rate and injection flow meter profiles prior to and after the treatment for the five wells show optimistic results to an acceptable extent
In coiled tubing acid placement, the coiled tubing/borehole annulus is usually filled with acid which allow the acid to be in contact with the entire zone at bottom hole temperature condition. This reduces the degree of diversion effectiveness.
Recommend people who work in carbonate reservoirs they should done their work on petrophysical analysis and the porosity should not have exceeded by the acids
The flow of fluids through these pores is often restricted because of permeability damage in the near-wellbore (NWB) formation. During matrix acidizing, the acid treatment is injected at matrix pressure and staying below formation fracture pressure.
Matrix acidizing of carbonates and silicates are worlds apart.
Reservoir simulation modeling of the surfactant flooding using Schlumberger Petrel Simulation modeling software.
Definition and Process Description
Surfactant Conservation (Mass Balance) Equations
Simulation Solution Vector
Surfactant Effects;
Treatment of PVT data
Treatment of SCAL data
Modeling the Change in Wettability
Surfactant Keywords Summary
Simulation Model Construction
Sensitivities Runs & Simulation Results
Conclusions
Reservoir engineers cannot capture full value from waterflood projects on their own. Cross-functional participation from earth sciences, production, drilling, completions, and facility engineering, and operational groups is required to get full value from waterfloods. Waterflood design and operational case histories of cross-functional collaboration are provided that have improved life cycle costs and increased recovery for onshore and offshore waterfloods. The role that water quality, surveillance, reservoir processing rates, and layered reservoir management has on waterflood oil recovery and life cycle costs will be clarified. Techniques to get better performance out of your waterflood will be shared.
A novel approach for incorporation of capillary and gravity into streamline s...Shusei Tanaka
The effective use of streamline simulators for flow simulation of multi-million cell detailed 3D models relies on the ability to take large simulation time-steps with few pressure solutions. For processes that are convective, the streamline approach works quite well while for flow simulation with compressibility, strong capillarity or strong gravity terms, the maximum time step size may be substantially reduced, limiting the utility of streamline simulation. This is the case when applying the conventional streamline operator-splitting approach, where the nonlinear terms associated with capillarity and gravity limit the time step. Earlier studies have shown the importance of an anti-diffusive correction in which numerical dispersion from the convective solution must be removed before capillary pressure can be accurately modeled. Evaluation of the antidiffusive term involves the solution of a local Riemann problem which, unfortunately, is difficult to determine in full field multi-dimensional problems with heterogeneity, and spatially variable viscosity, fluid velocity, and saturations. The alternative approach is to perform the operating splitting calculation with very small time-steps to minimize the numerical dispersion, but this is not an effective simulation strategy.
Why Frac & How it works!
Rock Mechanics
Fundamentals of Hydraulic Fracturing
Fracturing models
Design criteria for frac treatments
Frac Equipment
Frac chemicals and proppants
QC for Frac job
Hydraulic fracturing technologies and practices
The acidizing is pumping of the acids into the wellbore to remove near well formation damage and other damaging substances, matrix acidizing is applied primarily to remove skin damage that caused by drilling, completion, work over, well killing or injection fluids.
This project is concerned with carbonate reservoirs that exceeded in Kurdistan subsurface formations.
Conduct a case study using real industrial data of Arab-D formation (Ghawar oil field – Saudi Arabia) which has five water wells were treated with 50 gallon of HCl acid The treatment acid was placed with coiled tubing and foam was used as diverter. The foam was made from nitrogen, water and surfactants.
Water injection pressure, injection rate and injection flow meter profiles prior to and after the treatment for the five wells show optimistic results to an acceptable extent
In coiled tubing acid placement, the coiled tubing/borehole annulus is usually filled with acid which allow the acid to be in contact with the entire zone at bottom hole temperature condition. This reduces the degree of diversion effectiveness.
Recommend people who work in carbonate reservoirs they should done their work on petrophysical analysis and the porosity should not have exceeded by the acids
The flow of fluids through these pores is often restricted because of permeability damage in the near-wellbore (NWB) formation. During matrix acidizing, the acid treatment is injected at matrix pressure and staying below formation fracture pressure.
Matrix acidizing of carbonates and silicates are worlds apart.
Reservoir simulation modeling of the surfactant flooding using Schlumberger Petrel Simulation modeling software.
Definition and Process Description
Surfactant Conservation (Mass Balance) Equations
Simulation Solution Vector
Surfactant Effects;
Treatment of PVT data
Treatment of SCAL data
Modeling the Change in Wettability
Surfactant Keywords Summary
Simulation Model Construction
Sensitivities Runs & Simulation Results
Conclusions
Reservoir engineers cannot capture full value from waterflood projects on their own. Cross-functional participation from earth sciences, production, drilling, completions, and facility engineering, and operational groups is required to get full value from waterfloods. Waterflood design and operational case histories of cross-functional collaboration are provided that have improved life cycle costs and increased recovery for onshore and offshore waterfloods. The role that water quality, surveillance, reservoir processing rates, and layered reservoir management has on waterflood oil recovery and life cycle costs will be clarified. Techniques to get better performance out of your waterflood will be shared.
A novel approach for incorporation of capillary and gravity into streamline s...Shusei Tanaka
The effective use of streamline simulators for flow simulation of multi-million cell detailed 3D models relies on the ability to take large simulation time-steps with few pressure solutions. For processes that are convective, the streamline approach works quite well while for flow simulation with compressibility, strong capillarity or strong gravity terms, the maximum time step size may be substantially reduced, limiting the utility of streamline simulation. This is the case when applying the conventional streamline operator-splitting approach, where the nonlinear terms associated with capillarity and gravity limit the time step. Earlier studies have shown the importance of an anti-diffusive correction in which numerical dispersion from the convective solution must be removed before capillary pressure can be accurately modeled. Evaluation of the antidiffusive term involves the solution of a local Riemann problem which, unfortunately, is difficult to determine in full field multi-dimensional problems with heterogeneity, and spatially variable viscosity, fluid velocity, and saturations. The alternative approach is to perform the operating splitting calculation with very small time-steps to minimize the numerical dispersion, but this is not an effective simulation strategy.
Why Frac & How it works!
Rock Mechanics
Fundamentals of Hydraulic Fracturing
Fracturing models
Design criteria for frac treatments
Frac Equipment
Frac chemicals and proppants
QC for Frac job
Hydraulic fracturing technologies and practices
New Approach to Design Capillary Pressure Curves, which Would Improve Simulat...Faisal Al-Jenaibi
This presentation is discussing New Approach to Design Capillary Pressure Curves, which Would Improve Simulation Models Initialization and shorten History Match time consumed.
The seventh lecture in the module Particle Technology, delivered to second year students who have already studied basic fluid mechanics.
Centrifugal Separation covers both sedimenting and filtering centrifuges as well as hydrocyclones. Adaptation of the gravity settling and conventional filtration models, to account for the conceptual centrifugal acceleration, is included. Examples of industrial equipment for centrifugal separation are included.
Streamline based history matching of arrival times and bottom-hole pressure d...Shusei Tanaka
Streamline-based history matching techniques have provided significant capabilities in integrating field-scale water-cut and tracer data into high resolution geologic models. The effectiveness of the streamline approach lies in the fact that parameter sensitivities can be computed analytically as one-dimensional integrals along streamlines and requires little additional computational overhead beyond the forward simulation. However, application of the streamline-based approach for simultaneous integration of water-cut and bottomhole pressure has been rather limited. This is partly because the convective streamlines appear to offer no particular advantage while computing parameter sensitivities for the bottomhole pressure data. This limits the utility of streamline-based history matching particularly for three-phase black-oil and compositional systems where the integration of pressure data is a requirement to accurately model reservoir depletion mechanisms.
Pumps are used in virtually all industries and are big uses of energy. This presentation shows methods of condition monitoring and how to optimise time to overhaul.
Use of streamline flow diagnostics for injection production rate allocation o...Shusei Tanaka
Rate allocation optimization for water and gas injection/production problem are typically complex, require multiple simulations to find optimal injection/production strategy to improve the economic value of the asset. The objective of this work is to develop and demonstrate the fast (one or few iteration of simulations) and robust (improve efficiency based on economic values with derivative-free method) workflow to achieve water and gas flooding rate allocation optimization by streamline-based technique.
Design Considerations for Antisurge Valve SizingVijay Sarathy
Centrifugal Compressors experience a phenomenon called “Surge” which can be defined as a situation where a flow reversal from the discharge side back into the compressor casing causing mechanical damage.
The reasons are multitude ranging from driver failure, power failure, upset process conditions, start up, shutdown, failure of anti-surge mechanisms, check valve failure to operator error to name a few. The consequences of surge are more mechanical in nature whereby ball bearings, seals, thrust bearing, collar shafts, impellers wear out and sometimes depending on the how powerful are the surge forces, cause fractures to the machinery parts due to excessive vibrations.
The following tutorial explains how to size an anti-surge valve for a single stage VSD system for Concept/Basic Engineering purposes.
Improving Energy Efficiency of Pumps and Fanseecfncci
Pumps and Fans are energy consuming equipment that can be found in almost all Industries. Therefore, it is important to check if they are running efficiently. This presentation give an overview about energy saving opportunities in pump and fan equipment. It was prepared in the context of energy auditor training in Nepal in the context of GIZ/NEEP programme. For further information go to EEC webpage: http://eec-fncci.org/
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
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Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
An effective reservoir management by streamline based simulation, history matching and rate allocation optimization
1. An Effective Reservoir Management by
Streamline-based Simulation, History
Matching and Optimization
Shusei Tanaka
May, 2014
2. • Development of a general purpose streamline-based reservoir
simulator:
Inclusion of diffusive flux via Orthogonal Projection
Illustration by black oil model
Extension to a multicomponent system
• Application to Brugge benchmark case:
Streamline-based simulation
Streamline-based BHP/WCT data integration
Flow diagnostics for streamline-based NPV optimization
• Conclusion
Outline
2/50
3. Streamline Technology: Overview
3/50
• Key concept of Streamline:
Fast IMPES-based reservoir simulation
History matching(HM) by calibration of travel time
Improves sweep efficiency by streamline information
Pressure field Streamlines Connection map
4. Problem Statement:
SL-based Reservoir Management
4/50
• Challenges for mature field, multiple well…
Quick forecasting
HM for individual well
Improve NPV by reallocating well rate
• Streamline is efficient, but can we apply all the time?
What if flow is not convective dominant?
How about prior to breakthrough for HM?
Can we improve NPV?
Mature field with
multiple
wells
6. Motivation
6/50
Solve 1D Convection EquationsCalculate Diffusive Flux on Grid
Compute Pressure
& Velocity Field
• Streamline simulation is difficult to apply if…
System of equation is highly nonlinear (ex. Gas injection)
Capillary and gravity effects are dominant
Error by Operator-Split
Error by IMPES
7. ;0
w
w
u
t
S
Why Split the Equation?
• Water velocity does not follow total velocity with capillary
(and gravity)
7/50
tuwu
Streamline
cowowtww pkFuFu
8. • Split equation by physical mechanisms
Convective
Transport
Capillary
Diffusion
0
cowow
w
pkF
t
S
0
w
w
u
t
S
0
wt
w
Fu
t
S
cowowtww pkFuFu
Saturation Transport
Equation
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 0.2 0.4 0.6 0.8 1
WaterSaturation
Normalized Distance
Correct Solution
Convection Flow
Too much diffusion
with large time step
(SPE 163640)
Operator Splitting
Capillary after
convection
8/50
9. 0
~
wtw
w
Fuu
t
S
cowowtwwwtw pkFuFFFuu
~~
• Split equation by physical mechanisms
• Anti-diffusive corrections
Computationally expensive:
Function of (P, T, composition,
Initial state) for each grid, time step
0
w
w
u
t
S
0
wt
w
Fu
t
S
Splitting with anti-
diffusive flux
Convection Eq.
Corrected Operator Splitting
Anti-diffusive concave envelope
9/50
10. 0
w
w
u
t
S
wtww uufu
Parallel component,
calculate along
streamline
Anti-diffusive correction
not needed
Orthogonal Projection
• Split equation into parallel and transverse flux terms
twf u
wu
tuwu
Streamline
10/50
11. twf u
wu
0
w
w
u
t
S
0
tw
w
uf
t
S
0
w
w
u
t
S
tuwu
Orthogonal Projection
Parallel to Ut
(Solve along streamline)
Transverse to Ut
(Solve on grids)
Streamline
• Split equation into parallel and transverse flux terms
wtww uufu
Parallel component,
calculate along streamline
Anti-diffusive correction not
needed
11/50
12. 1.Compute pressure & velocity field
Include capillary effects
2.Trace streamlines
Solve 1D convection equations
Include capillarity and gravity
3.Map back saturation to grid
Calculate corrector term
Predictor-Corrector Workflow
Iterative IMPES
Orthogonal Projection
12/50
13. • Pressure equation(IMPES)
• Transport equation (along SL)
Orthogonal Projection:
Application to Multicomponent System
0
owgj
j
owgj
j
owgj
jj
owgj
jjr Qupuc
t
p
Scc
i
sl
ii fm
t
cfgDpFy
u
k
yFfSym sl
ii
owgj owgj jogwmm
m
jmjmcmjjij
t
jijj
sl
ij
ogwj
jiji
1
,2
,,
Δ
• Transport equation (on Grid, corrector)
ogwj jmogwm
m
jmcjmmjjijtt
i
DgpFykuuI
t
m
,
ˆˆ
Pc,Gravity along streamline
Transverse Pc,Gravity on grid
0
owgj
ijijjjijjjij qyuySy
t
• Governing equation
13/50
14. Illustrative Example
100 mD
5 mD
• Water injection 0.2PVI, then CO2 0.2PVI
• Single time step for each injection period
• Observe capillarity by parallel/transverse to Ut
tw uf
wu
14/50
15. Water Saturation and Capillary Flux
Distributions
• Capillarity traps water at
center by J-Function
• Capillarity flows back water
towards injector during gas
injection period
Sw after water injection
Arrow: water capillary flux
Sw after gas injection
Arrow: water capillary flux
1
)(
kSwJpcow
15/50
16. Water Capillary Flux:
Parallel and Transverse to Total Velocity
Total capillary flux
Capillary flux transverse
to total velocity
Capillary flux along
total velocity
• Most of the capillary effects can be included along the streamlines
cow
t
tt
t
ow
t
w p
u
uu
I
u
k
u
2
Along streamline On grids
16/50
cow
t
t
t
ow
p
u
u
k 2
17. Water Saturation Distribution
Commercial, FD Operator Splitting
(no correction)
Orthogonal Projection
• OP can take large time step without anti-diffusive correction
17/50
18. Injection :: CO2
10 rb/D – 1000 [Days]
Production :: BHP
(1900 psi)
2D Cross-Section CO2 Flooding Model
Pc, Convection
Pc, Gravity
Simulation model:
• 7 HC component + Water
• Rel-Perm by Corey
• Water-wet Capillarity
Initial & Boundary Condition
• 2000+ psi , 212F˚
• Constant production BHP, constant CO2 injection at 10 rb/D
• 1000 days
18/50
19. CO2 Mole Fraction Distribution:
Along Streamline
Including Pc & GravityConvection only
19/50
20. Production Mole Fraction of CO2
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 200 400 600 800 1000
ProductionMoleFraction(CO2)
Time [Days]
Streamline
Commercial Simulator
Number of time step:
Commercial FD = 56
Streamline = 21
20/50
21. CO2 Mole Fraction Distribution:
Final Distribution
Orthogonal Projection
(After corrector term)
Commercial FD
(E300)
21/50
22. 0
50
100
150
200
250
300
350
400
450
500
2D Areal 2D Cross-Section 2D Cross-
SectionHetero
Goldsmith Field
E300 FIM
Streamline
Previous case
Comparisons of Number of
Time Step
NumberofTimeStep
Tested simulation cases
in the paper
10×
2×
4×
3×
22/50
23. 0
50
100
150
200
250
300
350
400
450
500
2D Areal 2D Cross-Section 2D Cross-
SectionHetero
Goldsmith Field
E300 FIM
Streamline
Previous
case
Comparisons of Number of
Time Step
NumberofTimeStep
Tested simulation cases
in the paper
10×
2×
4×
3×
23/50
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 180 360 540 720 900 1080
ProductionMoleFraction(CO2)
Time [Days]
Streamline
Commercial Simulator
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.0E+00 2.5E+04 5.0E+04 7.5E+04 1.0E+05
ProductionMoleFraction(CO2)
Time [Days]
Streamline
Commercial Simulator
24. Conclusions
24/50
• Developed a new SL-based simulation method to incorporate
capillarity and gravity and applied to CO2 injection cases
• Computational advantages:
• Minimizes the saturation correction term
• Can take large time steps without anti-diffusive corrections
• Demonstrated by synthetic and field case:
• Iterative IMPES approach handles nonlinearity
• Larger time stepping obtained compared with commercial FD
simulator
25. Application to Brugge Benchmark:
- Streamline-Simulation
- History Matching
- NPV Optimization
26. Brugge Benchmark Example
26/50
• Benchmark model for HM, optimization problem
• 20 producers, 10 injectors in complex geometry
• Conduct 40 years of waterflood, 1000 stb/d per wel
Oil saturation and well location
Initial So Net gross ratio
Porosity
Rock table ID
28. Comparisons of Oil Saturation
Distribution
28/50
Initial oil saturation
After 20 years
Streamline Commercial (ECL)
29. Presented at student paper contest
2013
Application to Brugge Benchmark:
- Streamline-Simulation
- History Matching
- NPV Optimization
30. 0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 500 1000 1500 2000
WaterCut
Time [Days]
Streamline-based Inverse Modeling
30/50
min 𝛿𝐝 𝑤𝑐𝑡 − 𝐒 𝑤𝑐𝑡 𝛿𝐤
𝛿𝐝
1. Run reservoir simulation
by given model
2. Trace Streamlines and
calculate parameter sensitivity
3. Update parameters to satisfy:
Observation
Prediction
31. Motivation and Objective
31/50
Streamlines
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 500 1000 1500 2000
WaterCut
Time [Days]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 500 1000 1500 2000
CO2MoleFraction
Time [Days]
WCT
• What can we tell prior to breakthrough?
Pressure data can be used while not considered previously
• Study objective
New approach to calculate pressure sensitivity along SL
Simultaneous inversion of pressure and water-cut data
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0 50 100 150 200
BottomHolePressure
Time [Days]
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0 50 100 150 200
BottomHolePressure
Time [Days]
BHP
Observation
Initial
32. ik
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0 500 1000 1500 2000
WaterCut
Time [Days]
𝛿𝒕 𝑤𝑐𝑡
Production WCT
Parameter Sensitivity Along Streamline
32/50
• TOF( ): Travel time of neutral tracer along streamlines
, ,
, ,
x y z
Inlet
ds
x y z
u
𝜕𝑡
𝜕𝑘𝑖
= −
𝜕𝑆
𝜕𝜏
𝜕𝜏
𝜕𝑘𝑖
∙
𝜕𝑆
𝜕𝑡
−1
=
1
𝑓′(𝑆)
∆𝜏𝑖
𝑘𝑖
• Water-cut travel time sensitivity:
injector
Producer
[He et. al,2003]
𝜕𝑝 𝑏ℎ𝑝
𝜕𝑘𝑖
=
𝜕∆𝑝𝑖
𝜕𝑘𝑖
≈
∆𝑝𝑖
𝑘𝑖
• Bottom hole pressure sensitivity: [new]
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0 50 100 150 200
BottomHolePressure
Time [Days]
Production BHP
𝛿𝒑 𝑏ℎ𝑝
𝜕𝑝 𝑏ℎ𝑝
𝜕𝑘𝑖
≈
𝜏𝑖
𝜏
𝜕∆𝑝𝑖
𝜕𝑘𝑖
≈
𝜏𝑖
𝜏
∆𝑝𝑖
𝑘𝑖
Rate-Rate constraint
Rate-BHP constraint
33. Sensitivity Results: 1D CPG
(3phase Gas Injection)
-20.0
-15.0
-10.0
-5.0
0.0
0.0 0.5 1.0
PressureSensitivity,wrtk
Normalized Distance
Analytical (Stremaline)
Adjoint Method
0.0
5.0
10.0
15.0
20.0
0.0 0.5 1.0
PressureSensitivity,wrtk
Normalized Distance
Analytical (Stremaline)
Adjoint Method
33/50
Inj: Gas Rate
Prd: Rate
Producer BHP
sensitivity to k
Injector BHP
sensitivity to k
34. Sensitivity Results: 2D Areal
34/50
Inj
P1
P2P3
P4
Injector BHP sensitivity by k
P1 BHP sensitivity of by k
Permeability field
(Wells by rate constraint)
Adjoint Proposed
35. Inversion of Permeability by LSQR
35/50
• Run simulation and get following parameter
• Solve LSQR Matrix :
• Advantages:
• Find pressure/WCT sensitivity during SL simulation
• Localized (high resolution) changes in permeability
min 𝛿𝐝 𝑤𝑐𝑡 − 𝐒 𝑤𝑐𝑡 𝛿𝐤 + 𝛿𝐝 𝑏ℎ𝑝 − 𝐒 𝑏ℎ𝑝 𝛿𝐤 + 𝛽1 𝐈𝛿𝐤 + 𝛽2 𝐋𝛿𝐤
𝐒 𝑤𝑐𝑡
𝐒 𝑏ℎ𝑝
𝛽1 𝐈
𝛽2 𝐋
∆𝐤 =
𝛿𝐝 𝑤𝑐𝑡
𝛿𝐝 𝑏ℎ𝑝
0
0
Water-Cut Pressure - Smoothness
- Consistency with
static model
Scaled by stdev
36. History Matching of Brugge Field
• Use simulation result of Real.77 as observed data
• Use Real.1 as initial model
• Assume 3 years of data is available
Reference model Initial model
36/50
38. Reference kx Initial kx
Change of kx, WCT Change of kx, WCT&BHP
High perm
at middle layer
Change of Permeability
38/50
39. Reduction of Data Mismatch
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 20 40 60 80 100
NormalizedAbsoluteError.Pressure
Number of Iteration
0.0
0.3
0.6
0.9
1.2
1.5
0 20 40 60 80 100
NormalizedAbsoluteError,WaterCut
Number of Iteration
Pressure RMSE error WCT RMSE error
Individual well
Mean
39/50
40. • Have developed a new SL-based method to integrate
pressure data into prior geologic models
• Same advantages as prior streamline work:
• Analytic calculation of streamline sensitivities
• Requires only a single flow simulation per iteration
• Can be applied to field pressure/rate data prior to water
breakthrough
• Can be integrate pressure with water-cut or GOR
simultaneously, for black-oil and compositional
simulation
Conclusion
40/50
41. Presented at student paper contest
2014
Application to Brugge Benchmark:
- Streamline-Simulation
- History Matching
- NPV Optimization
42. Overview
42/50
• Problem:
Determining optimal injection/production rates to
maximize NPV
• Solution:
Developed a new streamline and NPV-based rate
allocation method
• Advantages:
Visualize efficiency of injector and producer
Extensible to any secondary recovery process with
commercial simulator
43. - Improve oil production rate
- Works only after breakthrough
SL-based Flow Rate Allocation
Optimization: Previous Study
43/50
• Use of Well Allocation Factors (WAFs):[Thiele et. al, 2003]
Well Allocation Factor map [SPE84080]
[SPE113628]
- WAFs: offset oil production of well-pair
• Equalize arrival time of injection fluid: [Al-Hutali et. al, 2009]
Norm Wt. - 0
After2yearsAfter5yearsears
Base
Base Improved
Norm Wt. - 0
After2yearsAfter5yearsyears
Base
- Control well rate to have equivalent
‘breakthrough’ time
- Increase well rate of high WAFs
Decrease
Increase
Decrease
Decrease
Decrease
Increase
- Improves sweep efficiency
- Works only before breakthrough
• Fast
• Not robust
• Does not optimize NPV
44. Proposed Optimization Method:
Overall Workflow
44/50
2. Trace Streamlines and
Find connection map
3. Calculate NPV diagnostic plot
4. Reallocate
well rate
via efficiency
1. Run simulation model
45. I1 I2 I3
I6
I5
I7 I8
NPV-based Efficiency of Streamline
P1 P2
P3 P4 P5
P6 P7
Hydrocarbon value, along SL
NPV along SL, integrate over reservoir life time
𝑣 𝑠𝑙
= 𝑞 𝑠𝑙
𝑛𝑜𝑑𝑒
𝑆 𝑜 𝑏 𝑜 𝑅 𝑜 ∆𝜏
𝑟𝑠𝑙 = 𝑞 𝑠𝑙
𝑛𝑜𝑑𝑒
𝑆 𝑜 𝑏 𝑜 𝑅 𝑜 + 𝑆 𝑤 𝑏 𝑤 𝑅 𝑤 ∆𝜏 ∙ 1 + 𝑑 −∆𝜏/365
∉
𝑝𝑟𝑑
𝑛𝑜𝑑𝑒
∆𝜏 > 𝑡 𝑟𝑠𝑚
• Hydrocarbon value and NPV along streamline
Pore volume × Saturation × FVF × Price
Discount rate Reservoir life
I4
45/50
48. NPV(Normalized)
Total value (Normalized)
Streamline-based Rate Allocation:
A New Approach
48/50
𝑞 𝑛𝑒𝑤
= 𝑞 𝑜𝑙𝑑 𝑒 𝑝𝑎𝑖𝑟
ҧ𝑒𝑓𝑖𝑒𝑙𝑑
ത𝐞 𝐟𝐢𝐞𝐥𝐝
decrease rate
Increase rate
Before update After update
• Advantages:
• Dynamically visualize efficiency of the injector and producer
• Able to propose ‘better’ well rate during SL-simulation
49. Oil Saturation and Well Location
• Constraints:
- Field water injection qt <= 20,000 bbl/d
- Well flow rate qti <= 6000 bbl/d
- Producer BHP > 100 psi, Injector BHP < 6000 psi
• Simulation Model:
- Synthetic water flooding
- 20 producers, 10 injectors
- 20 years of simulation
- Relative oil, water price = 1, -0.2 $/bbl
Brugge Benchmark Application
• Compare developed model with 3 approaches:
• Uniform injection (Uniform), Well allocation factors
(WAFs), Equalize Arrival Time (EqArrive), Developed model
(SLNPV)
49/50
52. MCERI
• Have developed a new SL-based rate allocation method to
improve recovery considering NPV
• Proposed a new diagnostic plot to visualize the relative value
and efficiency of a well in the asset
• Results in greater NPV compared to prior streamline-based
rate allocation methods
• Can be applied to IOR/EOR simulation study with any
commercial simulator, with low computational cost
Conclusions
54
Editor's Notes
Allow me start presentation.
This is the outline of this presentation and it has 3 main chapters:
1st, Development of a streamline simulator. Im going to show basic formulation and validation by 1D case
Then, Im going to show the methodology to incorporate capillary ad gravity, with case study of 1D to 3D SPE10 model
3rd, Im going to show the data integration of pressure and water-cut and application on synthetic case,
And the last, future work plan
Last, Im going to show some demonstration on developed model.
The objective of this study is as follows
1st, Develop a streamline-based simulator which can handle black oil and multi-component simulation
2nd , generally, streamline method has difficulties to incorporate capillary effect, but we present novel approach to incorpolate..
3rd, Apply simulator for history-matching problem, focusing on not only water-cut but also pressure data integration.
The objective of this study is as follows
1st, Develop a streamline-based simulator which can handle black oil and multi-component simulation
2nd , generally, streamline method has difficulties to incorporate capillary effect, but we present novel approach to incorpolate..
3rd, Apply simulator for history-matching problem, focusing on not only water-cut but also pressure data integration.
Allow me start presentation.
Streamline based method has been used for simulation, history-matching or optimization, however, we often ignore diffusive flux especially capillary.
The main reason is that because streamline is traced along total velocity and cannot take into account transverse flux caused by capillary and gravity. To take into account for this, the operator splitting method is used, however, it has some difficulties for the practical application, such as time-stepping restriction.
For this study, we present an approach to take into account these effect by Orthogonal projection, and since this method take into account gravity and capillary along streamline, we might able to use same analogy for history matching and optimization problem.
Orthogonal Projection.
In orthogonal projection, we split equation by physical phenomena but this approach will split flux along streamline and transverse flux.
The parallel component, which expressed by total fractional flow, including convection flow as well as capillary and gravity. Since we cannot consider every transverse flux along streamline, we split equation for transverse term calculated on grid.
Let me start talking about operator splitting and its problem.
The basic idea of operator splitting is that we split equation into several pieces, this is caused by numerical scheme that we take or coupling two softweare might end up with this situation.
This paticular example, we have convection diffusion equation,…
In order to prevent this problem, we have corrected operator splitting, which we have same equation in convection but give treatment to prevent diffusive flux as shown this equation.
This is called anti-diffusive correction.
The too much diffusive flux was caused by fractional flow following this green line, and we give anti-diffusive flux shown in red, will give you original fractional flow curve shown in blue.
This approach will solve issues about overestimation of diffusive flux,however, the concave construction is computationally expensive and it is not feasible to use this for every grid, and time step.
Orthogonal Projection.
In orthogonal projection, we split equation by physical phenomena but this approach will split flux along streamline and transverse flux.
The parallel component, which expressed by total fractional flow, including convection flow as well as capillary and gravity. Since we cannot consider every transverse flux along streamline, we split equation for transverse term calculated on grid.
Orthogonal Projection.
In orthogonal projection, we split equation by physical phenomena but this approach will split flux along streamline and transverse flux.
The parallel component, which expressed by total fractional flow, including convection flow as well as capillary and gravity. Since we cannot consider every transverse flux along streamline, we split equation for transverse term calculated on grid.
This slide shows the schematic flow of my simulator.
Simulation is based on conventional IMPES-based streamline approach, solve pressure on, trace streamlines and solve 1D transport equations.
The black character shows the standard streamline simulation approach, and red character shows the one I added for my research.
we have a capillary effects in pressure equation, which Im not going to cover this presentation.
Then, I calculate fluid transport on streamline. Here we have capillary and gravity effects, instead of using operator splitting technique.
Then, reminder tem is also calculated but on grid.
Let me talk about transverse flux and 1D equations.
The approach is applied for Black oil system, and we observed that orthogonal projection is effective and we will have time stepping advantage, so we apply this for multi component system.
Im not going into detail but we solve pressure by IMPES method, and transport equation is solved for total mole fraction shown as here.
In terms of capillary and gravity, we solve parallel part along streamine and non-parallel part on grid.
The study objectives becomes follows.
Firstly I am going to develop new streamline simulator and apply ‘orthogonal projection method’ for transverse flux.
The effect of capillary is also included in pressure equation.
Then, I test my approach by comparing ECLIPSE, which will validate my solution
I also compare the solution with conventional operator-splitting approach. It is well known that the operator splitting approach cannot take nonlinearity when the time-step is large.
The study objectives becomes follows.
Firstly I am going to develop new streamline simulator and apply ‘orthogonal projection method’ for transverse flux.
The effect of capillary is also included in pressure equation.
Then, I test my approach by comparing ECLIPSE, which will validate my solution
I also compare the solution with conventional operator-splitting approach. It is well known that the operator splitting approach cannot take nonlinearity when the time-step is large.
The study objectives becomes follows.
Firstly I am going to develop new streamline simulator and apply ‘orthogonal projection method’ for transverse flux.
The effect of capillary is also included in pressure equation.
Then, I test my approach by comparing ECLIPSE, which will validate my solution
I also compare the solution with conventional operator-splitting approach. It is well known that the operator splitting approach cannot take nonlinearity when the time-step is large.
The study objectives becomes follows.
Firstly I am going to develop new streamline simulator and apply ‘orthogonal projection method’ for transverse flux.
The effect of capillary is also included in pressure equation.
Then, I test my approach by comparing ECLIPSE, which will validate my solution
I also compare the solution with conventional operator-splitting approach. It is well known that the operator splitting approach cannot take nonlinearity when the time-step is large.
The result of cross-sectional model.
Model has capillary and gravity effects.
This is the results of water saturation distribution, x is normalized distance and y-axis shows water saturation.
This is the results of water saturation distribution, x is normalized distance and y-axis shows water saturation.
This is the results of water saturation distribution, x is normalized distance and y-axis shows water saturation.
This is the results of water saturation distribution, x is normalized distance and y-axis shows water saturation.
This is the results of water saturation distribution, x is normalized distance and y-axis shows water saturation.
Outline is as follows.
First,
Secondly,
Then,
Last, …….
Allow me start presentation.
Allow me to start the presentation.
Before start talking about study background, let me briefly overview the workflow of streamline-based history matching.
This approach is deterministic method, so our target reservoir is water/gas flooded and objective of the history matching is to match production profile such as WCT,GOR. So, the first step is to run simulation on given model.
2ndstep, streamlines are traced by given flux field and calculate parameter sensitivity for production profile.
There is to advantages here:
One is computational efficiency. Sensitivity is calculated by single simulation run using streamline properties.
2nd , streamline trajectory will automatically confine the reservoir into connection pair. This will make minimization problem easier.
3rd step is to update reservoir parameters to minimize production error by solving equation shown here. Our objective function is single number, shifting time and thus dimension of this matrix is small. Thus, this calculation has very small computational cost.
After updating reservoir parameter, we will continue this process until we get history match.
This approach has lots of advantages, however, one and biggest disadvantages of this method is we will not think about pressure during history matching. If we want to match pressure, we need to add additional process inside this loop.
Same behavior can be seen in production profile. We can match production concentration of CO2
Let me briefly overview previous work that former student established.
First, we have Time of flight sensitivity which describe relationship between time of flight and reservoir parameter by combining darcy’s law.
For instance, permeability and time of flight has negative relationship.
By combining this time of flight sensitivity and Buckley Levelette concept. We will have travel time sensitivity. For incompressible system, this is combined form of saturation speed and time of flight sensitivity.
More general form is developed including solution gas. This equation can be used for miscible compressible flow problem.
Allow me to start the presentation.
The same behavior can be seen in production profile. We can match the production concentration of CO2
Let me overview the previous streamline based rate allocation method.
The first approach that we can find is the use of well allocation factors.
The well allocation factors are defined as offset oil production or oil cut of the well pair. If the value is close to 1, that pair is efficient.
Their approach is to update well by comparing field average efficiency. If the efficiency is higher than average, then inject more by factors.
The second approach is called Equalize arrival time of injection fluid.
The objective of this method is to equalize arrival time of all injection-production pair, by solving this equation.
The example in right picture shows that by equaliing arrival time, we can improve sweep efficieny of the field.
In addition to this assumption, these previous study does not optimize NPV.
Let me start from motivation and objective of this study.
Streamline method is used for flow simulation, optimization and history-matching, and the one of the advantage of the streamine simulation is visualization of the flow dynamics and its application.
The picture below shows the streamline contoured by TOF, the travel time of the injection fluid.
The picture center is the drainage map, obtained by mapping injection to production connection to underline grid. With this we can visualize the region where injector drained.
Once we superimpose all the streamline information to reprehensive line, we can obtain connection map.
The previous study of SL-Based rate allocation optimization is done using this connection map, however, is not based on NPV and there is limitations due to assumptions.
The objective is to propose new flow diagnostic plot and rate allocation optimization method to optimize NPV.
In order to overcome limitation of the previous study, Im going to show the NPV-based flow diagonostics with example of 2D field.
The goal is to find the NPV and efficiency along streamline.
Then Im going to talk the procedure to update well rate according to the flow diagnostics.
The flow chat is shown here, we run simulation with single step, and then…
Update individual flow rate based on average efficiency of the field.
Then Im going to talk the procedure to update well rate according to the flow diagnostics.
The flow chat is shown here, we run simulation with single step, and then…
Update individual flow rate based on average efficiency of the field.
