Process Analyst is a comprehensive data analytics and visualization solution for oil and gas processing operations. This platform provides three different interfaces to access and leverage process data insights:
- GitHub Repository - Access to source code, analysis notebooks, and development resources
- Web Dashboard - Interactive visualization and analysis through a browser interface
- Telegram Bot - Quick insights and alerts through convenient messaging
Each interface serves different user needs while accessing the same underlying analytics engine.
- Process Efficiency Analysis: Identify optimal operating parameters to maximize output
- Energy Consumption Optimization: Track and reduce energy usage across operations
- Environmental Impact Assessment: Monitor and minimize CO2 emissions
- Catalyst Performance Evaluation: Compare and optimize catalyst usage
- Interactive Visualizations: Filter and explore process data dynamically
- Safety Incident Tracking: Monitor and improve safety performance
The platform analyzes process data with 23 key fields including:
- Process types and steps
- Operating parameters (temperature, pressure, duration)
- Resource metrics (energy, catalysts, worker count)
- Efficiency metrics (processing efficiency, energy per ton)
- Environmental impact (CO2 emissions)
- Economic indicators (operational costs, cost per ton)
URL: https://github.com/Ismat-Samadov/ProcessAnalyst
The GitHub repository provides:
- Source Code Access: View and download all project components
- Jupyter Notebooks: Run detailed analysis scripts locally
- Documentation: Comprehensive project documentation
- Development Resources: Contribute to or extend the platform
ProcessAnalyst/
├── README.md # Main project README
├── analysis/ # Data analysis component
│ ├── README.md # Analysis module documentation
│ ├── analyse.ipynb # Jupyter notebook for analysis
│ └── data/ # Data directory
│ ├── charts/ # Generated chart images
│ ├── data.csv # Process data (CSV format)
│ └── data.xlsx # Process data (Excel format)
├── dashboard/ # Interactive dashboard component
│ ├── README.md # Dashboard documentation
│ ├── app.py # Flask application
│ ├── data/ # Dashboard data
│ │ └── data.csv # Process data for dashboard
│ ├── requirements.txt # Python dependencies
│ ├── static/ # Static assets
│ │ ├── css/ # Stylesheets
│ │ │ └── style.css # Dashboard styling
│ │ └── js/ # JavaScript files
│ │ └── main.js # Dashboard interactivity
│ └── templates/ # HTML templates
│ └── index.html # Dashboard HTML template
└── telegram/ # Telegram bot component
├── README.md # Bot documentation
├── app.py # Bot application
├── data/ # Bot data
│ └── data.csv # Process data for bot
└── requirements.txt # Python dependencies
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Clone the repository:
git clone https://github.com/Ismat-Samadov/ProcessAnalyst.git cd ProcessAnalyst -
Create and activate a virtual environment:
python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate
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Install dependencies:
pip install -r requirements.txt
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Run the analysis notebooks:
cd analysis jupyter notebook analyse.ipynb -
Launch the dashboard locally:
cd dashboard python app.py
URL: https://processanalyst.onrender.com/
The web dashboard provides:
- Interactive Visualizations: Explore data through dynamic charts and graphs
- Filtering Capabilities: Drill down into specific processes, timeframes, or parameters
- Performance Metrics: Track KPIs and benchmarks in real-time
- Mobile-Responsive Design: Access insights from any device
- Overview Panel: High-level metrics and KPIs
- Process Analysis: Detailed breakdowns by process type and step
- Efficiency Tracker: Monitor energy, environmental, and cost efficiency
- Catalyst Comparison: Compare performance across different catalysts
- Custom Reports: Generate tailored reports for specific needs
- Navigate to https://processanalyst.onrender.com/
- Use the process type filter to focus on specific process categories
- Navigate between different sections using the sidebar menu
- Interact with charts to drill down into data
- View detailed analyses for efficiency, energy, environmental impact, and catalysts
The Telegram bot provides:
- Quick Insights: Get key metrics and stats on demand
- Automated Alerts: Receive notifications about process anomalies
- Data Visualizations: View charts and graphs directly in Telegram
- Convenient Access: Use from any device with Telegram installed
/start- Begin interaction with the bot (REQUIRED FIRST STEP)/help- View available commands and instructionsƏsas Məlumatlar- Get basic information about process dataSəmərəlilik Analizi- View efficiency analysisEnerji İstifadəsi- See energy usage patternsƏtraf Mühit Təsiri- View environmental impact analysisXərc Analizi- Get cost analysis informationOpenAI Təhlili- Generate AI-powered insights
- Open Telegram and search for
@analyst_bot - IMPORTANT: You MUST send the
/startcommand to initialize the bot - After sending
/start, a keyboard menu will appear - Use the keyboard menu to request specific analyses
- Receive visual charts and data summaries directly in your chat
- Get AI-powered insights through natural language processing
- Data Analysis: Python, Pandas, NumPy, SciPy, Scikit-learn
- Visualization: Matplotlib, Seaborn, Plotly.js
- Web Dashboard: Flask, Bootstrap, HTML/CSS/JavaScript
- Telegram Bot: pyTelegramBotAPI, OpenAI API integration
- Deployment: Render (cloud platform)
- Statistical analysis of process parameters
- Interactive data visualization
- Performance metric tracking
- Basic reporting and alerts
- Machine learning models for process optimization
- Predictive maintenance algorithms
- Anomaly detection for quality control
- Real-time optimization recommendations
- Advanced integration with production systems
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For Repository Use:
- Python 3.9+
- Git for version control
- Dependencies listed in requirements.txt
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For Dashboard Access:
- Modern web browser (Chrome, Firefox, Safari, Edge)
- Internet connection
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For Telegram Bot:
- Telegram account
- Mobile device or desktop Telegram client