About the Course

The energy sector has the world’s largest supply chain. The complexity of energy systems grows nonlinearly with the number of elements, the scale, and the level of interconnectivity, requiring a system-based approach for implementing a successful digital transformation program.

Digital Transformation can create infinite value across the energy value chain, including upstream, midstream, and downstream. Successful energy companies can accelerate digital transformation by focusing on adopting digital workflow processes and schemes to deploy emerging digital technologies, including Cloud Computing, Big Data Analytics, Artificial Intelligence and the Internet of Things (IoT). As energy firms shift paradigms towards greener, cleaner operations, effective digital transformation becomes necessary to tackle old and new challenges facing operators, service providers and consumers.

This 5-day interactive Digital Transformation in the Energy Sector training course will facilitate the delegates with innovative digital energy and optimisation methods. Also, the delegates will gain first-hand exposure to novel opportunities arising from the convergence of information technology and operational technology in energy generation and distribution operations while honing the digital engineering skills required to leverage the capabilities of the fourth industrial revolution. Delegates will study energy informatics use cases to capture lessons learned and embark on forward-looking opportunities.

Core Objectives

The delegates will achieve the following objectives:

• Understand how to integrate technical skills with energy informatics
• Create and maintain business value with artificial intelligence
• Leverage digital energy and optimisation
• Overcome organisational challenges to digital energy
• Embark on opportunities from the convergence of OT & IT

Training Approach

This training course will utilise various proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information and innovative methods presented, including theoretical concepts, team and individual exercises, case study analyses, educational videos and real-life applications. The delegates will also learn how to develop a digital information architecture strategy for digital energy and optimisation. They will also be acquainted with the design of digital systems and optimise decision-making processes.

The Attendees

This training course is designed for those who might be new to the field of digital transformation and energy informatics and will serve as useful building blocks for those already active in this area. It is equally relevant to those involved in the broader application of digital transformation.

Likewise, it will be valuable to the professionals but not limited to the following:

• Leaders and Professionals in the Energy Industry
• Operation Supervisors
• Engineering Disciplines
• Instrumentation and Control Technicians
• Services and Field Operators
• Digital Transformation Authorities
• Anyone working in the Industrial Sector

Daily Discussion

DAY ONE: DIGITAL TRANSFORMATION LANDSCAPE

• Definitions Digital Transformation
• Digital Transformation Failure Reasons
• Digital Transformation Challenges and Solutions
• Digital Transformation Misconception
• Important Points for the Digital Transformation Journey

DAY TWO: MACHINE LEARNING (ML) & ARTIFICIAL INTELLIGENCE (AI)

• Definition ML &AI
• How to create and maintain business value with AI?
• AI Benefits
• AI Applications
• Organisational and Behavioral Aspects

DAY THREE: IT & OT CONVERGENCE

• Industrial System Engineering
• PI AF
• PI System
• PI AF Analytics
• DevOps

DAY FOUR: PROCESS CONTROL, CONNECTIVITY, AND OPTIMISATION

• Major Challenges Facing in the Energy Sector
• SCADA
• Advanced Process Control
• Beyond APC: Real-Time Optimisation
• Big Data Analytics

DAY FIVE: INTEGRATED CYBERSECURITY

• Physical vs Cyber Security
• Three Linked Pillars of Security
• Risk Management Matrix for Cybersecurity
• Cyber Operations Control Centers
• Information Risk Management