The petroleum refining industry stands at a critical juncture in its evolution. After more than a century of technological advancement, the sector faces unprecedented pressure to reimagine its operations in response to climate change imperatives, market transformations, and societal expectations. This transformation requires a shift in how fuels and chemicals are produced.

At the same time, the revolution in artificial intelligence through the development of Large Language Models (LLMs) that are trained on vast amounts of data, allows remarkable capabilities in knowledge integration and problem-solving across diverse domains. The emergence of sophisticated prompt engineering has transformed these models from research artifacts into practical tools for addressing complex industrial challenges.

This book explores the convergence of these two transformative forces: the imperative to reimagine industrial hydrocarbon processing and the emergence of AI systems capable of supporting that reimagination. It examines how LLMs, when properly directed, can accelerate the transition toward more sustainable refining technologies by enabling more efficient knowledge synthesis, system design optimization, and innovation across disciplinary boundaries.

In addition, this book:

• Develops an approach to prompt engineering that is tailored for engineering and industrial applications
• Describes patterns of innovations in petroleum refining which can help address contemporary transformation challenges
• Provides an assessment of the potential and limitations of AI-assisted design for industrial transformation

The petroleum refining industry stands at a critical juncture in its evolution. After more than a century of technological advancement, the sector faces unprecedented pressure to reimagine its operations in response to climate change imperatives, market transformations, and societal expectations. This transformation requires a shift in how fuels and chemicals are produced.

At the same time, the revolution in artificial intelligence through the development of Large Language Models (LLMs) that are trained on vast amounts of data, allows remarkable capabilities in knowledge integration and problem-solving across diverse domains. The emergence of sophisticated prompt engineering has transformed these models from research artifacts into practical tools for addressing complex industrial challenges.

This book explores the convergence of these two transformative forces: the imperative to reimagine industrial hydrocarbon processing and the emergence of AI systems capable of supporting that reimagination. It examines how LLMs, when properly directed, can accelerate the transition toward more sustainable refining technologies by enabling more efficient knowledge synthesis, system design optimization, and innovation across disciplinary boundaries.