README.md

metadata

title: LAB Model Alluvial Stratigraphy Simulator
emoji: 🟦
colorFrom: blue
colorTo: indigo
sdk: streamlit
sdk_version: 1.26.0
app_file: app.py
pinned: false

LAB Model Alluvial Stratigraphy Simulator

Overview

This project simulates sedimentary basin stratigraphy using a simple LAB model. It incorporates aggradation, lateral migration, and periodic avulsion to generate stratigraphic layers. The simulation is visualized using Streamlit and provides analytical results such as Net-to-Gross (N/G) ratio, Amalgamation ratio, and Total Sand Bodies.

Features

• Interactive Parameter Control: Adjust basin width, total time steps, channel width, avulsion period, lateral migration rate, and more using Streamlit sliders.
• Scenario Switching: Change parameters mid-simulation to observe the impact on stratigraphy.
• Visualization: View stratigraphy as a color-coded plot.
• Analysis: Get detailed statistics on sedimentary layers.

Installation

1. Clone the repository:

   git clone <repository-url>
   

2. Navigate to the project directory:

   cd Labmodel
   

3. Install dependencies:

   pip install -r requirements.txt
   

Usage

1. Run the Streamlit application:

   streamlit run app.py
   

2. Open the application in your browser at http://localhost:8501.
3. Adjust parameters in the sidebar and click "Run Simulation" to view results.

Parameters

• Basin Width: Width of the basin in cells.
• Total Time Steps: Total simulation time.
• Channel Width: Width of the channel in cells.
• Avulsion Period: Time steps between channel jumps.
• Lateral Migration Rate: Rate of channel movement per time step.
• Scenario Switch Step: Time step at which parameters change.

Results

• Net-to-Gross (N/G) Ratio: Proportion of sand to total sediment.
• Amalgamation Ratio: Vertical connectivity of sand layers.
• Total Sand Bodies: Number of connected sand regions.

License

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

Contributing

Feel free to submit issues or pull requests to improve the project.

Acknowledgments

This project uses the following libraries:

• Streamlit: For interactive web applications.
• NumPy: For numerical computations.
• Matplotlib: For plotting.
• SciPy: For image analysis.