Artificial Intelligence in Oil and Gas: Strategy and Applications

Overview

Artificial intelligence has moved from pilot projects to daily operations in many oil and gas companies, from predicting equipment failures and optimising production to reading drilling reports and screening contracts. Yet many initiatives stall because they start with the technology instead of the business problem, or because the data, people and governance are not ready. This course gives engineers and managers a clear, non-technical understanding of what AI can and cannot do in the energy industry. Participants learn the main families of AI, including machine learning, computer vision and large language models, and see how they are applied across upstream, midstream and downstream through real industry examples. The course then covers how to choose and prioritise use cases, prepare data, build a business case, manage risk and ethics, and organise teams so that AI projects deliver measurable value.

Objectives

• Explain the main types of AI in plain business terms
• Recognise proven AI applications across the oil and gas value chain
• Identify and prioritise AI use cases in their own organisation
• Assess data readiness and infrastructure needs
• Build a simple business case and success measures for an AI project
• Address risk, cybersecurity, ethics and regulation
• Plan the people, skills and governance needed to scale AI

Who should attend

Training methodology

The course mixes short explanations with live demonstrations of AI tools on industry data, such as a failure prediction model and a document assistant built on a language model. Participants analyse published case studies from operators and service companies, then work in teams to identify, score and prioritise use cases from their own areas. A business case template is completed during the week, and each team presents an AI roadmap on the final day for peer and trainer feedback.

Programme outline

Dates and fees

Certificate

Frequently asked questions