pythermonomics 0.1.2

Tools for geothermal techno-economics, including NPV, LCOE, well simulation, and more.

PyThermoNomics

PyThermoNomics is a Python package for techno-economic analysis of geothermal energy projects. It provides tools to compute Net Present Value (NPV), Levelized Cost of Energy (LCOE), and related financial metrics using simulation data, well trajectories, and project configuration.

Features

• Calculate NPV and LCOE for geothermal projects
• Integrate simulation results (CSV, OPM/Eclipse output)
• Model well trajectories and deviations
• Flexible configuration via YAML files
• Command-line interface (CLI) for easy usage
• Extensible API for custom workflows
• Documentation and tests included

Reference in the literature

The PyThermoNomics has been used in:

Barros, E.G.D.; Szklarz, S.P.; Khoshnevis Gargar, N.; Wollenweber, J.; van Wees, J.D. Optimization of Well Locations and Trajectories: Comparing Sub-Vertical, Sub-Horizontal and Multi-Lateral Well Concepts for Marginal Geothermal Reservoir in The Netherlands. Energies 2025, 18, 627. DOI

Installation

Install the latest version using pip:

pip install pythermonomics

Optional Dependencies

• Documentation:
  To build and view the documentation, install with the docs extra:

  pip install pythermonomics[docs]
  

• Testing:
  To run tests, install with the tests extra:

  pip install pythermonomics[tests]
  

• Run Jupyter Notebook example:
  To run the notebook example, install with the notebook extra:

  pip install pythermonomics[notebook]
  

Install from source

Install the package from the repository root:

pip install .

Usage

Command-Line Interface

After installation, use the CLI tool:

pythermonomics -c config.yml -i sim_data.csv -d deviations/ -t trajectory.yml

See CLI Documentation for all options.

Python API

Import and use in your own scripts, for example, when using summary (reservoir simulation out in CSV format) and deviation files (XYZMD-records for each well):

from pythermonomics.geothermal_economics import GeothermalEconomics

economics = GeothermalEconomics.from_summary_deviation_file(
    settingfile='config_file.yml',
    summary_file='sim_data.csv',
    deviation_files_dir='dev_files/',
)

npv, lcoe_val, cashflow, wellRes, well_states, well_results = economics.compute_economics()

or if you want to use GeothermalEconomics using only the config and a well trajectory file (see examples for a trajectory file):

from pythermonomics.geothermal_economics import GeothermalEconomics

economics = GeothermalEconomics.from_trajectory(
    settingfile='config_file.yml',
    trajectoryfile='trajectoryfile,yml',
)

npv, lcoe_val, cashflow, wellRes, well_states, well_results = economics.compute_economics()

Documentation

Browse the full API reference and usage examples at Docs or build locally:

mkdocs serve

Testing

Run the test suite with:

pytest

Project Structure

src/
    pythermonomics/  # Main package code
        config/          
        data/
        energy_model/
        npv_model/
        cli.py
        geothermal_economics.py
docs/
    api/                   # API documentation
tests/                     # Unit and integration tests
pyproject.toml             # Package setup
mkdocs.yml                 # Documentation config

Contributing

Contributions are welcome! Please open issues or submit pull requests.

License

GNU General Public License v3 (GPLv3)

Contact information

Stephan de Hoop ([e-mail])

Acknowledgements

This study has been performed as part of the RESULT project (Enhancing REServoirs in Urban deveLopmenT: smart wells and reservoir development). RESULT has been subsidized through the ERANET Cofund GEOTHERMICA (EC Project no. 731117), by the Ministry of Economic Affairs and Climate Policy (the Netherlands), Rannis (Iceland) and GSI (Ireland).

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For more information, see the API Reference or contact the maintainers.