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 developed by the Applied Computational Science group at SINTEF Digital.

Getting started

Install Julia and add the package to your environment of choice:

using Pkg
Pkg.add("GLMakie")
Pkg.add("Jutul")
Pkg.add("JutulDarcy")

You can then run any of the examples in the examples directory by including them.

For a minimal example that runs a industry standard input file and produces interactive plots:

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) using the jutul module
• 3D visualization of grids and wells by loading a Makie.jl 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.

Paper and citing

The main paper describing JutulDarcy.jl is JutulDarcy.jl - a Fully Differentiable High-Performance Reservoir Simulator Based on Automatic Differentiation:

@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. 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 implements the Dual number class used throughout the code
• SparsityTracing.jl provides sparsity detection inside Jutul
• Krylov.jl provides the iterative linear solvers
• ILUZero.jl for ILU(0) preconditioners
• AlgebraicMultigrid.jl for AMG preconditioners
• HYPRE.jl for robust AMG preconditioners with MPI support
• PartitionedArrays.jl for MPI assembly and linear solve
• Tullio.jl for automatically optimized loops and Polyester.jl for lightweight threads
• TimerOutputs.jl and ProgressMeter.jl gives nice output to terminal.
• Makie.jl is used for the visualization features
• 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 is still work in progress, but contains a fair bit of useful information. In addition, see the examples folder for more information. Some functionality is also demonstrated in the tests.

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.