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Advanced CPD

Applied Digitalisation for Oil & Gas

This advanced 5 days programme provides professionals with a rigorous, practice-oriented grounding in Applied Digitalisation for Oil & Gas. Designed for those working across the Digital & Technology sector, the course combines established theoretical frameworks with current industry practice through expert-led instruction, structured case studies, and hands-on workshops.

5 daysDuration
AdvancedLevel
5 Days · 15 ModulesProgramme
YX-DIG-002Code
Classroom Online In-House Blended
Starting From
$4,950
per delegate · live online
Classroom
Face-to-face at a global venue
$5,950
Online
Live interactive virtual sessions
$4,950
In-House
Delivered at your premises
Quote
Enquire & Book Request In-House Quote
Internationally Accredited
50+ Global Locations
Expert Advisory Team
Secure Booking Process

Course Overview

About this programme

This advanced 5 days programme provides professionals with a rigorous, practice-oriented grounding in Applied Digitalisation for Oil & Gas. Designed for those working across the Digital & Technology sector, the course combines established theoretical frameworks with current industry practice through expert-led instruction, structured case studies, and hands-on workshops.

Participants will engage with the most relevant tools, standards, and methodologies used in Digital Transformation today. By the final day, delegates will leave with a clear personal action plan and the confidence to apply their learning immediately, contributing to improved performance, compliance, and competitive advantage within their organisations.

Programme Objective

Equip professionals with the knowledge, skills, and frameworks required to excel in Applied Digitalisation for Oil & Gas, driving measurable improvement in Digital & Technology performance and delivering tangible value to their organisations.

5 daysTotal Duration
5 DaysTraining Days
15 ModulesModules Covered
Max 20Class Size
EnglishLanguage
CPDAccreditations

What You Will Learn

11 key learning outcomes

01

Understand the strategic landscape of digital transformation and its impact on the energy sector

02

Apply data analytics and visualisation techniques to extract actionable insights from operational datasets

03

Evaluate AI and machine learning applications relevant to oil and gas, energy, and industrial operations

04

Assess cybersecurity risks in operational technology environments and apply mitigation frameworks

05

Design digital use cases that deliver measurable business value and operational improvement

06

Communicate digital strategy and technology roadmaps to senior leadership and business stakeholders

07

Apply cloud computing concepts and data architecture principles to enterprise digital initiatives

08

Understand and apply relevant digital standards, governance frameworks, and data management practices

09

Evaluate emerging technologies — IoT, digital twins, RPA, and blockchain — for energy sector applications

10

Build and prioritise a digital transformation roadmap aligned to organisational goals and capabilities

11

Apply change management principles to drive digital adoption across technical and non-technical teams

Course Outline

5 training days · 15 modules · hands-on workshops

1
Digital
Transformation
2
Data
Architecture,
3
AI,
Machine
4
Digital
Twin,
5
Digital
Transformation
Day 1

Digital Transformation Strategy & Energy Context

Understand the strategic drivers, maturity models, and energy sector context for digital transformation.

8 hours 3 modules
Module 1

The Digital Transformation Imperative

  • Industry 4.0 and 5.0: technological pillars and energy sector impact
  • Digital maturity models: from analogue to autonomous operations
  • Value drivers: cost reduction, safety, production, and sustainability
  • Digital transformation failure modes: why 70% of programmes fail
Module 2

Digital Technology Landscape

  • Internet of Things (IoT): sensors, edge computing, and connectivity
  • Cloud computing: IaaS, PaaS, SaaS, and hybrid cloud architectures
  • Artificial intelligence and machine learning: use case taxonomy
  • Digital twins: definition, maturity levels, and value creation
Module 3

Building the Digital Business Case

  • Value identification: revenue, cost, and risk impact categories
  • Business case structure: costs, benefits, and NPV analysis
  • Prioritisation frameworks: effort-impact matrix and strategic alignment
  • Stakeholder mapping and sponsorship for digital programmes
Practical Workshop

Digital maturity assessment: teams apply a structured maturity model to a provided oil and gas asset, score current state across six dimensions, and identify the highest-value improvement opportunities.

Day 2

Data Architecture, Management & Analytics

Apply data management principles and analytics techniques to generate operational insights.

8 hours 3 modules
Module 1

Data Management Foundations

  • Data types: structured, semi-structured, and unstructured
  • Data lifecycle: collection, storage, processing, and archiving
  • Master data management: data quality, governance, and ownership
  • Data architecture: data lakes, data warehouses, and data mesh
Module 2

Operational Data & Historian Systems

  • Process historian systems: OSIsoft PI, AVEVA, and InfluxDB
  • WITSML and PRODML: industry data standards for well and production data
  • Real-time data streaming: MQTT, OPC-UA, and event-driven architecture
  • Data cleaning and preprocessing: outlier detection and imputation
Module 3

Analytics & Visualisation

  • Descriptive analytics: dashboards, KPIs, and exception-based surveillance
  • Diagnostic analytics: drill-down, root cause, and anomaly detection
  • Predictive analytics: forecasting production, equipment health, and demand
  • Data visualisation tools: Power BI, Tableau, and Python Matplotlib
Practical Workshop

Analytics use case development: groups build a production surveillance dashboard concept for a provided dataset, defining KPIs, alert thresholds, and visualisation approach.

Day 3

AI, Machine Learning & Automation

Apply AI and machine learning concepts to industrial and energy sector use cases.

8 hours 3 modules
Module 1

AI & ML Fundamentals

  • Machine learning types: supervised, unsupervised, and reinforcement
  • Common algorithms: regression, decision trees, random forests, and neural networks
  • Feature engineering: variable selection, normalisation, and transformation
  • Model evaluation: accuracy, precision, recall, RMSE, and confusion matrix
Module 2

AI Use Cases in Energy & Oil and Gas

  • Predictive maintenance: anomaly detection and remaining useful life
  • Production optimisation: reservoir performance and well scheduling
  • Safety applications: hazard detection, PPE compliance, and incident prediction
  • Natural language processing: maintenance work order analysis and document search
Module 3

Responsible AI & Governance

  • AI bias: sources, detection, and mitigation strategies
  • Model explainability: SHAP values and LIME techniques
  • AI governance frameworks: accountability, transparency, and audit
  • Ethics and regulation: EU AI Act implications for energy sector applications
Practical Workshop

AI use case design workshop: teams select one of three provided operational challenges and design an end-to-end ML solution, covering data requirements, algorithm selection, and deployment strategy.

Day 4

Digital Twin, IoT & Connected Operations

Design digital twin architectures and IoT systems for connected asset operations.

8 hours 3 modules
Module 1

Digital Twin Architecture

  • Digital twin types: asset, process, and enterprise twins
  • Components: physical asset, digital model, and data connector
  • Simulation fidelity: from lookup tables to physics-based models
  • Digital twin use cases: virtual commissioning, operator training, and optimisation
Module 2

Industrial IoT Implementation

  • IIoT architecture: sensors, gateways, edge devices, and cloud platforms
  • Industrial communication protocols: OPC-UA, MQTT, and AMQP
  • Wireless technologies: WirelessHART, 5G private network, and LoRaWAN
  • Data security at the edge: device authentication and encrypted transmission
Module 3

Connected Operations & Remote Monitoring

  • Remote operations centre (ROC) design: workflow, staffing, and technology
  • Exception-based surveillance: alert management and escalation
  • Predictive maintenance integration with CMMS and work order generation
  • Operational technology cybersecurity: network segmentation and monitoring
Practical Workshop

Digital twin concept design: groups design a digital twin for a provided rotating equipment or production system, specifying data inputs, model type, update frequency, and use case benefits.

Day 5

Digital Transformation Roadmap & Change Management

Build and communicate a prioritised digital roadmap and manage the organisational change.

8 hours 3 modules
Module 1

Digital Roadmap Development

  • Technology radar: assessing emerging technologies for adoption readiness
  • Use case backlog: discovery, prioritisation, and sprint planning
  • Build vs. buy vs. partner: technology sourcing strategy
  • Agile delivery: MVP approach, iterative development, and value tracking
Module 2

Digital Operating Model

  • Digital organisation design: CDO, CoE, and federated model
  • Digital talent: data scientists, engineers, and product managers
  • Vendor and partner management: ecosystem and open innovation
  • Scaling successful pilots: from proof of concept to enterprise deployment
Module 3

Change Management for Digital Adoption

  • Digital culture: growth mindset and learning organisation principles
  • Stakeholder engagement: communicating digital vision and progress
  • Resistance management: addressing fear of automation and job change
  • Training and upskilling: digital academies and on-the-job learning
Practical Workshop

Capstone digital roadmap: teams present a 3-year digital transformation roadmap for a provided asset or business unit, covering use cases, technology investments, change programme, and expected value.

The course outline is indicative. Content may be adapted to reflect current industry developments and delegate experience levels.

Who Should Attend

This programme is designed for professionals across these roles

Data Analysts & Data Scientists

Professionals working with data to generate insights, models, and business intelligence

IT & OT Engineers

Engineers managing information technology or operational technology systems and infrastructure

Business Leaders & Managers

Leaders responsible for digital strategy, technology investment, and transformation programmes

Cybersecurity Professionals

Security teams protecting operational technology and digital assets in industrial environments

Operations & Asset Personnel

Operations, maintenance, and engineering staff adopting digital tools in their work processes

Digital Innovation Leads

Innovation champions tasked with identifying and delivering digital use cases across the business

Schedule & Fees

Upcoming public dates — enrol anytime

Jun
07
07 Jun – 11 Jun 2026
Dubai, UAE
Classroom 9 seats available
$5,950
per delegate
Jul
02
02 Jul – 06 Jul 2026
Live Online (Zoom)
Online 9 seats available
$4,950
per delegate
Jul
28
28 Jul – 01 Aug 2026
Singapore
In-House 8 seats available
Quote
custom pricing
Aug
24
24 Aug – 28 Aug 2026
Houston, USA
Blended Only 3 seats left!
Quote
custom pricing
Sep
27
27 Sep – 01 Oct 2026
Abu Dhabi, UAE
Classroom 7 seats available
$5,950
per delegate
Oct
25
25 Oct – 29 Oct 2026
Live Online (Zoom)
Online 7 seats available
$4,950
per delegate
Can't find a suitable date? Contact us for private cohort scheduling or in-house delivery options at your premises.

Accreditations & Recognition

This course carries internationally recognised professional credits

CPD Certified

Course Resources

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Ready to Enrol?

Speak with our training advisors to confirm availability, group rates, and customised in-house options.