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https://github.com/sintefmath/jutuldarcy.jl
Darcy flow and reservoir simulator based on Jutul.jl
https://github.com/sintefmath/jutuldarcy.jl
blackoil carbon-sequestration co2-storage compositional darcy-flow geothermal julia mpi porous-media-flow reservoir-simulation simulation wells
Last synced: 7 days ago
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Darcy flow and reservoir simulator based on Jutul.jl
- Host: GitHub
- URL: https://github.com/sintefmath/jutuldarcy.jl
- Owner: sintefmath
- License: mit
- Created: 2022-04-04T14:04:14.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-10-29T13:08:26.000Z (22 days ago)
- Last Synced: 2024-10-29T13:12:21.009Z (22 days ago)
- Topics: blackoil, carbon-sequestration, co2-storage, compositional, darcy-flow, geothermal, julia, mpi, porous-media-flow, reservoir-simulation, simulation, wells
- Language: Julia
- Homepage: https://sintefmath.github.io/JutulDarcy.jl/dev
- Size: 202 MB
- Stars: 80
- Watchers: 18
- Forks: 18
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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> [!TIP]
> Visit the docs at https://sintefmath.github.io/JutulDarcy.jl/dev/
# Reservoir simulation in Julia
JutulDarcy.jl: Darcy-scale and subsurface flow (CO2 sequestration, gas/H2 storage, oil/gas fields) using [Jutul.jl](https://github.com/sintefmath/Jutul.jl) developed by the [Applied Computational Science group](https://www.sintef.no/en/digital/departments-new/applied-mathematics/applied-computational-sciences/) at [SINTEF Digital](https://www.sintef.no/en/digital/).
## Getting started
Install [Julia](https://julialang.org/) and add the package to your environment of choice:
```julia
using Pkg
Pkg.add("GLMakie")
Pkg.add("Jutul")
Pkg.add("JutulDarcy")
```
You can then run any of the examples in the [`examples`](https://github.com/sintefmath/JutulDarcy.jl/tree/main/examples) directory by including them.
For a minimal example that runs a industry standard input file and produces interactive plots:
```julia
using JutulDarcy, GLMakie
spe9_dir = JutulDarcy.GeoEnergyIO.test_input_file_path("SPE9")
file_path = joinpath(spe9_dir, "SPE9.DATA")
case = setup_case_from_data_file(file_path)
result = simulate_reservoir(case)
plot_reservoir_simulation_result(case.model, result)
```
Note that interactive plotting requires `GLMakie`, which may not work if you are running Julia over SSH.
## Key features
JutulDarcy is a general purpose porous media simulator with high performance written in Julia. It is fully differentiable with respect to forces and discretization parameters.
### Physical systems
- Immiscible multi-phase flow
- Black-oil type models with support for both dissolved vapor (Rs) and vaporized liquid (Rv)
- Equation-of-state compositional flow with up to three phases and any number of components
- Geothermal systems
All solvers can incorporate general multisegment wells with rigorous mass balance, friction pressure loss, complex well limits and time-dependent controls.
### Architecture
- Written in pure Julia, with automatic differentiation and dynamic sparsity detection
- Support for sensitivities with respect to any model parameters using the adjoint method
- High performance assembly and linear solvers, with support for two-stage CPR BILU(0)-CPR Krylov solvers
- MPI support with domain decomposition and BoomerAMG-CPR solver with automatic METIS partitioning
- Support for consistent discretizations (AvgMPFA / NTPFA)
### Input/output and workflow tools
- Support for reading in and running .DATA files with corner point grids, with support for non-conformal faults and inactive cells.
- Unstructured grids and complex cases input from [the Matlab Reservoir Simulation Toolbox (MRST)](https://www.mrst.no) using the `jutul` module
- 3D visualization of grids and wells by loading a [Makie.jl](https://docs.makie.org/stable/) backend (requires Julia 1.9, `GLMakie` for interactivity)
- Interactive plotting of well curves
The compositional simulator has been matched against commercial offerings, AD-GPRS and MRST. The blackoil simulator has been validated on the standard SPE benchmarks (SPE1, SPE9, ...).
## Example run times on benchmarks
| Name | Cells | Report steps | Preconditioner | Time [s] |
|-----------|--------|--------------|------------------|----------|
| SPE1CASE2 | 300 | 120 | block-ILU(0) | 0.30 |
| SPE9 | 9000 | 35 | block-ILU(0) | 3.41 |
| Egg | 18553 | 123 | CPR-block-ILU(0) | 8.60 |
| Norne | 44417 | 247 | CPR-block-ILU(0) | 259.0 |
| OLYMPUS1 | 192750 | 20 | CPR-block-ILU(0) | 162.5 |
Cases with CPR used hypre as the AMG solver. OYMPUS1 refers to realization 1 from the [OLYMPUS optimization benchmark challenge](https://link.springer.com/article/10.1007/s10596-020-10003-4).
## Paper and citing
The main paper describing `JutulDarcy.jl` is *JutulDarcy.jl - a Fully Differentiable High-Performance Reservoir Simulator Based on Automatic Differentiation*:
```bibtex
@article{jutuldarcy_ecmor_2024,
author = "M{\o}yner, O.",
title = "JutulDarcy.jl - a Fully Differentiable High-Performance Reservoir Simulator Based on Automatic Differentiation",
year = "2024",
volume = "2024",
number = "1",
pages = "1-9",
doi = "https://doi.org/10.3997/2214-4609.202437111",
publisher = "European Association of Geoscientists \& Engineers",
issn = "2214-4609",
}
```
[Paper is available from EAGE.](https://doi.org/10.3997/2214-4609.202437111) If you use JutulDarcy in your work, please cite this paper.
## A few of the packages used by Jutul and JutulDarcy
Jutul builds upon many of the excellent packages in the Julia ecosystem. Here are a few of them, and what they are used for:
- [ForwardDiff.jl](https://github.com/JuliaDiff/ForwardDiff.jl) implements the Dual number class used throughout the code
- [SparsityTracing.jl](https://github.com/PALEOtoolkit/SparsityTracing.jl/) provides sparsity detection inside Jutul
- [Krylov.jl](https://github.com/JuliaSmoothOptimizers/Krylov.jl) provides the iterative linear solvers
- [ILUZero.jl](https://github.com/mcovalt/ILUZero.jl/blob/master/src/ILUZero.jl) for ILU(0) preconditioners
- [AlgebraicMultigrid.jl](https://github.com/JuliaLinearAlgebra/AlgebraicMultigrid.jl) for AMG preconditioners
- [HYPRE.jl](https://github.com/fredrikekre/HYPRE.jl) for robust AMG preconditioners with MPI support
- [PartitionedArrays.jl](https://github.com/fverdugo/PartitionedArrays.jl) for MPI assembly and linear solve
- [Tullio.jl](https://github.com/mcabbott/Tullio.jl) for automatically optimized loops and [Polyester.jl](https://github.com/JuliaSIMD/Polyester.jl) for lightweight threads
- [TimerOutputs.jl](https://github.com/KristofferC/TimerOutputs.jl) and [ProgressMeter.jl](https://github.com/timholy/ProgressMeter.jl) gives nice output to terminal.
- [Makie.jl](https://makie.juliaplots.org/) is used for the visualization features
- [MultiComponentFlash.jl](https://github.com/moyner/MultiComponentFlash.jl) provides many of the compositional features
...and many more, both directly in the Project.toml file and indirectly!
# Additional examples and further reading
The [documentation](https://sintefmath.github.io/JutulDarcy.jl/dev/) is still work in progress, but contains a fair bit of useful information. In addition, see the [examples](examples/) folder for more information. Some functionality is also demonstrated in the [tests](https://github.com/sintefmath/JutulDarcy.jl/tree/main/test).
*Internals and undocumented functions are subject to change at this time. However, the main interface for the reservoir simulator itself seen in the examples should be fairly stable.*