Digitalization for Oil and Gas
Select Other "city & date"
Digitalization for Oil and Gas Course
Introduction:
The world runs on energy, or better yet, wastes a lot of energy, as the energy is wasted during its production, transport and consumption. Incredible as it may seem but the world could save almost 20% of energy if it would just improve its consumption, by delivering energy only when and where it is required. This computing was not available before, but as the era of Big Data came about the advancement in the Data Mining and Artificial Intelligence (AI) should provide the answer to the questions of energy-saving and optimization of energy resources use.
By using AI and digitization methods creating of the virtual twins of the energy and industry systems help the entities and communities achieve a high level of energy savings as well as high optimization of industrial processes, as they provide the possibilities of experimentation, innovation, simulation and forecasting.
Course Objectives:
By the end of the training, participants will be able to:
- Apply the data mining methodology for energy usage patterns
- Effectively utilize Artificial Intelligence algorithms for real-time optimization
- Identify key areas where the Data Mining and Artificial Intelligence can be utilized
- Understand the benefits through the example cases
- Use Data Mining and Artificial Intelligence methods for optimization of spinning reserves
Who Should Attend?
This training course is suitable for a wide range of professionals. These include:
- Oil and Gas professionals who want to learn techniques of Data Mining and Artificial Intelligence
- Team Leaders, Supervisors, Section Heads and Managers
- Professionals who have an interest in Data Science
- Technical Professionals including those in Maintenance, Engineering & Production
- Project Managers
- Anyone interested in optimization and energy consumption reduction
Course Outlines:
Data Mining and Pattern Recognition
- Data Mining Process
- Data Preparation
- Association and Pattern Recognition
- Data Mining in the Energy Industry
- Data Mining-clusters and Outliers
Artificial Intelligence Algorithms
- Artificial Intelligence Development
- Linear Regression
- Logistic Regression
- Decision Tree
- Support Vector Machine
- Other Algorithms Applied in Artificial Intelligence (AI)
Energy Distribution Planning and Optimization
- Energy Storage Planning
- Managing Incidents and Instrument Failures
- Energy Grid Management
- Energy Consumption Forecasting
Developing Digital Twins
- Digitization of Industry and Energy
- Optimal Power Flow Problem Formulation
- Neural Network Application to Optimal Power Flow
- Particle Swarm Optimization for Optimal Power Flow
- Total Transfer Capability Enhancement by Evolutionary Algorithm
Simulation, Machine Learning, and Smart Contracts
- Dynamic Simulation of Industry Systems
- Simulation of Unit Commitment Problem
- Machine Learning for Renewable Energy
- Forecasting Renewable Energy Generation
- Smart Contracts within the Energy Industry
