SeismoVision is a sophisticated seismic data interpretation application designed for reservoir identification using advanced machine learning techniques. This web-based tool provides an intuitive interface for geoscientists and engineers to analyze and interpret seismic data efficiently.
- Data Upload: Support for SEG-Y format seismic data files
- Interactive Visualization:
- Dynamic seismic section display
- Customizable color maps and contrast controls
- Interactive trace analysis
- Reservoir Identification:
- Machine learning-based reservoir prediction
- Real-time prediction overlay
- Statistical analysis of predictions
- Data Analysis Tools:
- Trace extraction and analysis
- Amplitude analysis
- Cross-sectional visualization
- Clone the repository
- Install the required dependencies:
pip install streamlit numpy pandas segyio plotly scikit-learn- Start the application:
streamlit run main.py- Access the application through your web browser at
http://localhost:5000 - Upload your SEG-Y format seismic data (or use example from
data_example/1x1.sgy) - Use the sidebar controls to adjust visualization parameters
- Run reservoir predictions and analyze results
- streamlit
- numpy
- pandas
- segyio
- plotly
- scikit-learn
- joblib
The application is built using Python and Streamlit framework, focusing on:
- Clean, maintainable code structure
- Efficient data processing
- Interactive visualization capabilities
- Machine learning integration
Developed by Tommy Xaypanya on 10/23/2024