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Artificial Intelligence & Machine Learning for Oil & Gas Operations Training Course

Equips oil and gas teams to identify high-value AI and machine learning uses, from production optimization to predictive maintenance, and their data needs.

DOFE · Digital Oilfield & Smart Energy TechnologiesAll Levels#2103ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Course Overview

This advanced training course provides a comprehensive framework for understanding and applying Artificial Intelligence (AI) and Machine Learning (ML) technologies across modern oil and gas operations. It focuses on how AI and ML can transform operational data into actionable insights that support production optimization, predictive maintenance, asset reliability, process efficiency, risk management, and data-driven decision-making. The program examines the foundations of AI and ML within the oil and gas value chain, including data preparation, machine learning algorithms, predictive analytics, intelligent monitoring, anomaly detection, forecasting, optimization, and automated decision support. Participants will explore practical applications across exploration, drilling, production, processing, facilities, maintenance, and asset management. The course also addresses advanced applications such as predictive maintenance, production forecasting, equipment failure prediction, reservoir and well analytics, process optimization, digital twins, intelligent automation, and real-time operational decision support. Particular attention is given to data quality, model performance, explainability, cybersecurity, governance, and responsible use of AI in industrial environments. Through practical case studies, data-driven exercises, and scenario-based workshops, participants will develop the ability to identify suitable AI and ML use cases, evaluate data readiness, select appropriate analytical approaches, interpret model outputs, assess business value, and develop practical implementation strategies for AI-enabled oil and gas operations.

Learning Objectives

  • By the end of the course, participants will be able to:
  • Understand the fundamentals of Artificial Intelligence and Machine Learning in oil and gas operations.
  • Identify high-value AI and ML applications across the oil and gas value chain.
  • Evaluate data requirements and data quality for AI-driven applications.
  • Apply machine learning approaches to operational and production data.
  • Develop predictive models for equipment performance and operational risks.
  • Apply AI techniques to production optimization and forecasting.
  • Evaluate AI applications for wells, reservoirs, facilities, and production systems.
  • Use anomaly detection to identify abnormal operational conditions.
  • Assess the use of AI for predictive maintenance and asset reliability.
  • Evaluate AI model performance, accuracy, and operational relevance.
  • Identify governance, cybersecurity, explainability, and responsible AI requirements.
  • Develop practical strategies for implementing AI and ML solutions in oil and gas operations.

Who Should Attend

This course is designed for Oil and Gas Managers, Asset Managers, Operations Managers, Production Managers, Petroleum Engineers, Reservoir Engineers, Production Engineers, Drilling Engineers, Facilities Engineers, Maintenance and Reliability Professionals, and technical specialists involved in operational optimization. It is also suitable for Digital Transformation Professionals, Data Scientists, Data Analysts, Automation and Control Engineers, Information Technology and Operational Technology Professionals, Artificial Intelligence Specialists, Project Managers, and professionals responsible for digital innovation and technology implementation. The program is particularly relevant to oil and gas organizations seeking to leverage operational data and AI technologies to improve production performance, asset reliability, predictive capabilities, operational efficiency, and data-driven decision-making.

Learning Outcomes

  • Upon completion of the course, participants will be able to:
  • Assess AI and ML opportunities across oil and gas operations.
  • Identify suitable AI use cases based on operational requirements and business value.
  • Evaluate the quality, availability, and suitability of operational data.
  • Prepare and structure data for machine learning applications.
  • Select appropriate machine learning approaches for different oil and gas problems.
  • Develop predictive models for production, equipment, and operational performance.
  • Apply anomaly detection techniques to identify abnormal operating conditions.
  • Use AI-based forecasting to support production and operational planning.
  • Evaluate AI applications for predictive maintenance and asset reliability.
  • Interpret AI model results and assess model performance.
  • Identify AI governance, cybersecurity, explainability, and data management requirements.
  • Develop an implementation roadmap for AI and ML adoption in oil and gas operations.

Course Outline

Course Outline

Day 1

Artificial Intelligence & Machine Learning Fundamentals for Oil & Gas

  • Evolution of AI in the oil and gas industry
  • AI, Machine Learning, Deep Learning, and predictive analytics
  • AI applications across the oil and gas value chain
  • Oilfield data sources and industrial data environments
  • Structured and unstructured operational data
  • Data quality, preparation, and feature engineering
  • Supervised and unsupervised learning
  • Classification, regression, and clustering
  • AI project lifecycle and value assessment
  • Practical Application: Identifying and prioritizing AI and ML use cases for an oil and gas operation
Day 2

Machine Learning for Production, Wells & Reservoirs

  • Production data analytics
  • Production forecasting using machine learning
  • Well performance prediction
  • Reservoir data and predictive analytics
  • Decline and production trend analysis
  • Artificial lift optimization
  • Drilling data analytics
  • Predictive models for production optimization
  • Model validation and performance assessment
  • Practical Workshop: Developing an AI-based production forecasting and optimization use case
Day 3

AI for Predictive Maintenance & Asset Reliability

  • AI applications in asset management
  • Equipment health monitoring
  • Predictive maintenance principles
  • Failure prediction and remaining useful life estimation
  • Anomaly and fault detection
  • AI applications for pumps, compressors, turbines, and rotating equipment
  • Static equipment and process monitoring
  • Condition-based maintenance using operational data
  • Reliability analytics and maintenance decision support
  • Practical Application: Developing an AI-driven predictive maintenance model for a critical oil and gas asset
Day 4

Intelligent Operations, Optimization & Real-Time Decision Support

  • AI-driven process optimization
  • Real-time operational analytics
  • Intelligent control and automated decision support
  • AI applications in processing and production facilities
  • Digital twins and AI-enabled simulation
  • Intelligent alarm and anomaly management
  • Operational risk prediction
  • AI integration with automation and industrial control systems
  • Edge and cloud AI for oil and gas operations
  • Practical Workshop: Designing an AI-enabled operational decision-support solution
Day 5

AI Strategy, Governance & Implementation in Oil & Gas

  • AI strategy development for oil and gas organizations
  • AI use-case prioritization and business case development
  • Model deployment and operationalization
  • AI performance monitoring and continuous improvement
  • Data governance and model governance
  • AI explainability and responsible AI
  • Industrial cybersecurity and AI-related risks
  • Workforce capabilities and change management
  • Scaling AI across assets and operations
  • Final Integrated Workshop: Developing a comprehensive AI and Machine Learning implementation roadmap covering data readiness, use-case prioritization, predictive analytics, production optimization, predictive maintenance, intelligent operations, model governance, cybersecurity, performance measurement, and implementation priorities.

Upcoming Dates

Selected date

Casablanca · 28 Dec 2026 – 1 Jan 2027 · Classroom

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CityDatesPrice per ParticipantEarly Bird
AmmanScheduled
27 – 31 Dec 2026€4,000€3,600until 7 Dec
DubaiScheduled
27 – 31 Dec 2026€4,700€4,230until 7 Dec
OnlineScheduled
27 – 31 Dec 2026€2,700€2,430until 7 Dec
Kuala LumpurScheduled
28 Dec 2026 – 1 Jan 2027€4,700€4,230until 7 Dec
IstanbulScheduled
28 Dec 2026 – 1 Jan 2027€5,300€4,770until 7 Dec
MadinahScheduled
28 Dec 2026 – 1 Jan 2027€4,800€4,320until 7 Dec
TunisiaScheduled
28 Dec 2026 – 1 Jan 2027€4,300€3,870until 7 Dec
ParisScheduled
28 Dec 2026 – 1 Jan 2027€6,700€6,030until 7 Dec
BakuScheduled
28 Dec 2026 – 1 Jan 2027€5,300€4,770until 7 Dec
ManamaScheduled
28 Dec 2026 – 1 Jan 2027€5,300€4,770until 7 Dec
RiyadhScheduled
28 Dec 2026 – 1 Jan 2027€4,800€4,320until 7 Dec
RomeScheduled
28 Dec 2026 – 1 Jan 2027€7,000€6,300until 7 Dec
CasablancaScheduled
28 Dec 2026 – 1 Jan 2027€4,700€4,230until 7 Dec
LondonScheduled
28 Dec 2026 – 1 Jan 2027€5,800€5,220until 7 Dec
DohaScheduled
28 Dec 2026 – 1 Jan 2027€4,700€4,230until 7 Dec
GenevaScheduled
28 Dec 2026 – 1 Jan 2027€7,300€6,570until 7 Dec
DammamScheduled
28 Dec 2026 – 1 Jan 2027€4,800€4,320until 7 Dec
ViennaScheduled
28 Dec 2026 – 1 Jan 2027€6,400€5,760until 7 Dec
LisbonScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec
BarcelonaScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec
MuscatScheduled
28 Dec 2026 – 1 Jan 2027€6,300€5,670until 7 Dec
MilanScheduled
28 Dec 2026 – 1 Jan 2027€7,000€6,300until 7 Dec
MadridScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec
CairoScheduled
28 Dec 2026 – 1 Jan 2027€3,800€3,420until 7 Dec
SalalahScheduled
28 Dec 2026 – 1 Jan 2027€6,300€5,670until 7 Dec
MarrakeshScheduled
28 Dec 2026 – 1 Jan 2027€4,700€4,230until 7 Dec
ZurichScheduled
28 Dec 2026 – 1 Jan 2027€5,800€5,220until 7 Dec
BangkokScheduled
28 Dec 2026 – 1 Jan 2027€6,700€6,030until 7 Dec
AmsterdamScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec
MunichScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec

Available in: Istanbul · Dubai · London · Riyadh · Doha · Amsterdam

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