This document describes a CFD model developed to simulate circulation patterns and temperature distribution in Lake Binaba, a small and shallow reservoir in Ghana. The model aims to predict heat storage and evaporation. It uses OpenFOAM to solve equations of motion and heat transfer over the lake's complex bathymetry under wind and atmospheric conditions. Results show velocities, heat fluxes at the surface, temperature profiles, and total heat storage over time. The CFD model provides a valuable tool for understanding small and shallow lakes.
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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.
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An effective reservoir management by streamline based simulation, history mat...Shusei Tanaka
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.
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.
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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.
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Can AI do good? at 'offtheCanvas' India HCI preludeAlan Dix
Invited talk at 'offtheCanvas' IndiaHCI prelude, 29th June 2024.
https://www.alandix.com/academic/talks/offtheCanvas-IndiaHCI2024/
The world is being changed fundamentally by AI and we are constantly faced with newspaper headlines about its harmful effects. However, there is also the potential to both ameliorate theses harms and use the new abilities of AI to transform society for the good. Can you make the difference?
2. Introuduction
Lake Binaba
CFD Model
Conclusion
Aims of the study
Outline
1
Introuduction
Aims of the study
2
Lake Binaba
Description
Why 3D-CFD Model?
3
CFD Model
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
4
Conclusion
Conclusion
2 / 24
3. Introuduction
Lake Binaba
CFD Model
Conclusion
Aims of the study
Aims of the study
The following goals are considered:
To develop a three-dimensional time-dependent hydrodynamic
and heat transfer model(CFD model)
Simulating the effects of wind and atmosphere conditions over a
complex bathymetry.
To predict the circulation patterns as well as the temperature
distribution in the water body.
To estimate total heat storage of small and shallow
lakes(reservoirs) in order to estimate evaporation from water
surface.
3 / 24
4. Introuduction
Lake Binaba
CFD Model
Conclusion
Description
Why 3D-CFD Model?
Outline
1
Introuduction
Aims of the study
2
Lake Binaba
Description
Why 3D-CFD Model?
3
CFD Model
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
4
Conclusion
Conclusion
4 / 24
5. Introuduction
Lake Binaba
CFD Model
Conclusion
Description
Why 3D-CFD Model?
Description
Lake Binaba:
Location: an artificial lake located in northern Ghana
Surface: the average area of the lake surface is 4.5 km2
Average depth: only 3 m
Maximum depth: 7 m
Usage: a small reservoir, used as a form of infrastructure for the
provision of water
Air temperature: fluctuates between 24 C and 35 C
Water surface temperature: varies from 28 C to 33 C
Climate: (semi-)arid region
5 / 24
8. Introuduction
Lake Binaba
CFD Model
Conclusion
Description
Why 3D-CFD Model?
Why 3D-CFD Model?
Using 3D-CFD Model for shallow lakes:
Inalnd water bodies such as lakes and reservoirs are very
important parts of the continental land surface.
Understanding the heat storage in lakes and reservoirs is essential
to estimate evaporation in energy budget methods.
Small and shallow lakes response to atmospheric conditions very
fast.
Accurate estimation of the heat transfer between the atmosphere
and water is extremely important to model the temperature
dynamics and stratification in the lakes.
1-D & 2-D models are not able to consider horizontal advection
term in morphometrically complex lakes and reservoirs
8 / 24
9. Introuduction
Lake Binaba
CFD Model
Conclusion
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
Outline
1
Introuduction
Aims of the study
2
Lake Binaba
Description
Why 3D-CFD Model?
3
CFD Model
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
4
Conclusion
Conclusion
9 / 24
11. Introuduction
Lake Binaba
CFD Model
Conclusion
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
Geometry
The starting point for all problems is a “geometry”.
Figure: Geometry of lake using in CFD model(V.S:100)
11 / 24
12. Introuduction
Lake Binaba
CFD Model
Conclusion
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
Equations
Continuity equation(mass is conserved):
∂uj
=0
∂xj
(1)
Momentum equations using Boussinesq approach
∂ui
∂
∂
∂ui ∂uj
+
(uj ui ) −
νef f
+
∂t
∂xj
∂xj
∂xj ∂xi
∂p
=−
+ gi [1 − β(T − Tref )]
∂xi
−
2
3
∂uk
∂xk
δij
(2)
Temperature(energy is conserved) in the water body
∂T
∂
∂ ∂T
+
(T uj ) − κef f
(
) = ST
∂t
∂xj
∂xk ∂xk
(3)
12 / 24
13. Introuduction
Lake Binaba
CFD Model
Conclusion
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
Equations
In the model, for incompressible flows the density is calculated as
a linear function of temperature as:
ρk = 1 − β (T − Tref )
(4)
Incoming shortwave radiation is included in the source term(ST ).
ST (z ∗ , t) =
1
ηI0 exp(−ηz ∗ )
ρ0 Cp
(5)
This function allows the radiation to be absorbed through a finite
distance in the upper layers of the model water column rather
than only at the air-water interface.
13 / 24
14. Introuduction
Lake Binaba
CFD Model
Conclusion
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
Boundary Conditions
Wind over water surface affects lake currents, sensible and latent
heat fluxes.
Shear Stress BC(U):
τsurf,u = ρ0 (νt + ν)
∂u
∂z
(6)
τsurf,v = ρ0 (νt + ν)
∂v
∂z
(7)
For Temperature, the water surface temperature is not needed.
Using a mixed(implicit) BC (T):
ρ0 Cp κef f
∂T
∂z
= Hnet
(8)
surf
Hnet = HLA + HLW + HS + HE
(9)
14 / 24
15. Introuduction
Lake Binaba
CFD Model
Conclusion
CFD Work Flow
Geometry
Solving
Using OpenFOAM
Results and Post-processing
OpenFOAM
OpenFOAM: Open Source Field Operation and
Manipulation
Open-Source Library
Free of Charge
Running in LINUX OS
C++ Library
Linking with PYTHON
New solvers and BCs can be implemented by the user
Running in parallel on distributed processors(tested for up to
1000 cores)
15 / 24
23. Introuduction
Lake Binaba
CFD Model
Conclusion
Conclusion
Conclusion
Computational fluid dynamics (CFD) analysis has proven to be a
valuable design tool in the water resources
Modelling is one of the best means to gain understanding of
complex flow fields
Wind over water surface affects lake currents, sensible and latent
heat fluxes
Buoyancy effect due to density gradiant in water body should be
considered in temperature profile
23 / 24