jutuldarcy 1.0.1

Reservoir simulation with JutulDarcy in Python.

PyJutulDarcy

Python wrapper for JutulDarcy.jl, a fully differentiable reservoir simulator written in Julia. This package facilitates automatic installation of JutulDarcy from Python, as well as a minimal interface that allows fast simulation of .DATA files in pure Python. For more details about JutulDarcy.jl, please see the Julia Documentation.

The package also provides access to all the functions of the Julia version under jutuldarcy.jl.JutulDarcy, jutuldarcy.jl.GeoEnergyIO and jutuldarcy.jl.Jutul. These functions are directly wrapped using JuliaCall. For more details, see the JuliaCall Documentation on converting of types.

Installation

The package can be installed with pip:

pip install jutuldarcy

On first time usage of the package JuliaCall will automatically install Julia and manage all dependency packages.

A minimal example

import jutuldarcy as jd
# Load SPE9 dataset to disk
pth = jd.test_file_path("SPE9", "SPE9.DATA")
# Simulate the model
res = jd.simulate_data_file(pth)
# Get field quantities and plot
import matplotlib.pyplot as plt
fopr = res["FIELD"]["FOPR"]
days = res["DAYS"]
plt.plot(days, fopr)
plt.ylabel("Field oil production")
plt.xlabel("Days")
plt.show()

Here, res is a standard dict containing the following fields:

• "FIELD": Field quantities (average pressure, total water injection, etc) as numpy arrays.
• "WELLS": Well quantities (bottom hole pressures, injection rates, production rates, etc)
• "STATES": Reservoir states for all active cells, given as a list with a dict for each timestep. For example, res["STATES"][10]["Rs"] will give you an array of the solution gas-oil-ratio at step 10.
• "DAYS": Array of the number of days elapsed for each step.

Optionally, convert = False can be passed to get access to the "full" output as seen in Julia, where it is possible to get access to grid geometry, model parameters, and so on.

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",
}

Contributing

Contributions that expose additional functionality is welcome.