fiberis 0.4.1

Fiber Reservoir Integrated Simulator

fibeRIS

fibeRIS: Fiber Optic Reservoir Integrated Simulator

fibeRIS is a Python-based toolkit for the analysis, simulation, and management of data relevant to reservoir engineering, with a particular focus on Distributed Fiber Optic Sensing (DFOS) data. It is developed by Shenyao Jin for research purposes.

This project provides a suite of modules for handling multi-dimensional datasets, performing signal processing, simulating pressure diffusion, and programmatically controlling the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework.

Core Modules

Analyzer (fiberis.analyzer)

The core of the data processing capabilities, providing specialized classes for different data dimensions:

• Data1D: Handling 1D time-series data (e.g., gauge pressure, pumping curves).
• Data2D: Handling 2D spatiotemporal data (e.g., DAS waterfall plots).
• Data3D: Handling 3D volumetric data or multi-variable datasets.
• Data1DG: Handling 1D geometric/spatial data (e.g., depth profiles).
• Geometry3D: Handling 3D wellbore trajectories and spatial geometries.
• TensorProcessor: Handling tensor data (e.g., stress/strain tensors) over time.

Utilities (fiberis.utils)

A collection of helper functions for:

• Signal Processing: Filtering (Butterworth), spectral analysis, outlier removal.
• History Management: Logging operations and tracking data lineage.
• Visualization: Plotting tools for 1D, 2D, and 3D data.

Simulation (fiberis.simulator & fiberis.moose)

• Simulator: A lightweight, independent 1D simulator for quick pressure diffusion modeling.
• MOOSE Wrapper: A programmatic interface to build, run, and analyze complex multiphysics simulations using the MOOSE framework.

Installation

You can install fibeRIS using pip:

pip install fiberis

To install from source for development:

git clone https://github.com/shenyaojin/fibeRIS.git
cd fibeRIS
pip install -e .

Testing

The repository includes a comprehensive test suite based on pytest. To run the tests:

1. Install test dependencies:

   pip install pytest numpy matplotlib scipy pandas
   

2. Run tests:

   pytest tests/
   

License

This project is licensed under MIT License - see the LICENSE file for details.

Contact

For questions or issues, please contact Shenyao Jin at [e-mail].