Applied AI for Production Chemistry Professionals

Why Choose Garranto Academy for Applied AI Training?

Garranto Academy delivers industry-focused AI training designed specifically for production chemistry professionals in the oil & gas sector. Through practical exercises, real-world case studies, and hands-on implementation, participants learn how to apply AI tools to automate reporting, analyze operational data, improve decision-making, and build AI-powered solutions for production chemistry workflows.

Course Overview:

The Applied AI for Production Chemistry Professionals programme is an intensive 3-day hands-on training designed for Process Chemistry, Analytical Chemistry, Subsurface Chemistry, and Project Chemistry teams. Participants will learn how to leverage Generative AI, Microsoft Copilot, AI-powered analytics, predictive AI techniques, and custom AI assistants to improve efficiency across production chemistry operations. Through practical labs and team-specific use cases, learners will explore real-world applications in flow assurance, laboratory reporting, chemical programme optimization, reservoir souring analysis, and engineering reviews. By the end of the programme, participants will have the skills to implement AI solutions that enhance productivity, automate repetitive tasks, and support data-driven decision-making.

What You'll Learn in Our Applied AI for Production Chemistry Professionals Course?

Course Objectives:

Upon successful completion of this course, learners will be able to:

• ✓Understand Generative AI, Large Language Models (LLMs), and Agentic AI concepts.

• ✓Apply structured prompt engineering techniques for production chemistry workflows.

• ✓Use Microsoft Copilot and AI tools to improve productivity and technical documentation.

• ✓Analyze laboratory and field datasets using AI-powered techniques.

• ✓Automate technical reports and operational documentation.

• ✓Apply predictive AI concepts for chemistry programme optimization.

• ✓Build custom AI assistants for production chemistry teams.

• ✓Evaluate AI ethics, governance, privacy, and compliance considerations.

• ✓Develop practical AI implementation roadmaps for their organizations.

Prerequisites

• ✓No prior AI or programming experience required.

• ✓Basic computer literacy and Microsoft Office proficiency.

• ✓Participants are encouraged to bring real reports, datasets, and workflow examples for hands-on exercises.

Course Outlines:

Module 1.1 — Understanding AI in the Context of Oil & Gas

• ✓Key Concepts:

• ✓Introduction to Generative AI, LLMs, and Agentic AI

• ✓AI applications in upstream oil & gas operations

• ✓Flow assurance and laboratory automation use cases

• ✓Reservoir management applications

• ✓AI limitations and safe usage practices

• ✓Understanding AI in HSSE-critical environments

Module 1.2 — Prompt Engineering Masterclass

• ✓Key Concepts:

• ✓Fundamentals of effective prompting

• ✓Anatomy of a high-quality prompt

• ✓Context, role, objective, style, and response formatting

• ✓CO-STAR Framework

• ✓RAISE Framework

• ✓Role-based prompting techniques

• ✓Chain-of-thought prompting

• ✓Few-shot and zero-shot prompting

• ✓Prompt chaining and iterative refinement

Module 1.3 — Microsoft Copilot for Daily Productivity

• ✓Key Concepts:

• ✓Copilot for Word and technical document creation

• ✓Copilot for Excel data analysis

• ✓Copilot for Outlook communication management

• ✓Copilot for Teams meeting productivity

• ✓AI-assisted workflow optimization

Module 1.4 — AI for Technical Writing & Communication

• ✓Key Concepts:

• ✓AI-powered technical report generation

• ✓Executive summary creation

• ✓Vendor and stakeholder communication

• ✓Presentation content development

• ✓Converting technical data into business insights

Module 2.1 — AI-Powered Data Analysis for Chemistry Professionals

• ✓Key Concepts:

• ✓AI-assisted data workflows

• ✓Working with laboratory and field datasets

• ✓Trend analysis and pattern recognition

• ✓Chemical performance monitoring

• ✓Anomaly detection using AI

• ✓Data-driven operational decision support

Module 2.2 — Automated Lab Reporting & Documentation

• ✓Key Concepts:

• ✓Automated report generation

• ✓AI-based documentation workflows

• ✓Corrosion monitoring reports

• ✓Scale tendency reports

• ✓Produced water quality reports

• ✓Validation of AI-generated outputs

Module 2.3 — Predictive Chemistry & AI-Assisted Decision Making

• ✓Key Concepts:

• ✓Predictive versus reactive chemistry management

• ✓Corrosion forecasting

• ✓Scale tendency prediction

• ✓Hydrate risk assessment

• ✓Chemical injection optimization

• ✓Introduction to machine learning concepts

• ✓AI-assisted decision support

Module 2.4 — Team Breakout: AI Analytics Applied to Your Sub-Team

• ✓Key Concepts:

• ✓Process Chemistry AI dashboards

• ✓Analytical Chemistry QA support

• ✓Subsurface Chemistry risk assessment

• ✓Injection water compatibility analysis

• ✓Project Chemistry design reviews

• ✓Material selection support

Module 3.1 — Building Custom AI Assistants for Production Chemistry Workflows

• ✓Key Concepts:

• ✓Custom GPTs and AI assistants

• ✓Production chemistry knowledge assistants

• ✓Troubleshooting bots

• ✓Lessons learned repositories

• ✓Knowledge management using AI

Module 3.2 — n8n: Hands-On Lab

• ✓Key Concepts:

• ✓AI-assisted material selection

• ✓FEED document reviews

• ✓Chemical injection system sizing

• ✓HAZOP preparation support

• ✓Engineering decision support

Module 3.3 — AI for Subsurface & Flow Assurance

• ✓Key Concepts:

• ✓Reservoir souring prediction

• ✓Injection water compatibility screening

• ✓Hydrate formation prediction

• ✓Flow assurance analytics

• ✓Natural language production data analysis

Module 3.4 — AI Ethics, Governance & Safe Use

• ✓Key Concepts:

• ✓Responsible AI principles

• ✓Data privacy and confidentiality

• ✓AI output verification

• ✓Regulatory compliance

• ✓Governance frameworks

• ✓Risk mitigation strategies

Module 3.5 — AI Action Planning & Capstone

• ✓Key Concepts:

• ✓AI use case identification

• ✓Team presentations

• ✓AI implementation planning

• ✓90-day roadmap development

• ✓Organizational adoption strategies

Course Outcomes:

Upon completing the "Applied AI for Production Chemistry Professionals" course, participants will:

• ✓Understand AI applications across production chemistry operations.

• ✓Apply structured prompt engineering frameworks effectively.

• ✓Use Microsoft Copilot and modern AI tools to improve productivity.

• ✓Perform AI-assisted analysis of laboratory and field datasets.

• ✓Automate reporting and technical documentation processes.

• ✓Build custom AI assistants tailored to production chemistry workflows.

• ✓Apply predictive AI concepts to optimize chemistry programmes.

• ✓Implement responsible AI practices within operational environments.

• ✓Develop practical AI implementation roadmaps for their teams.

Key Benefits of Learning Applied AI for Production Chemistry Professionals

Leverage AI technologies to automate workflows, accelerate analysis, improve operational efficiency, and support smarter decision-making across production chemistry functions.

How AI Can Transform Production Chemistry Operations?

AI enables production chemistry professionals to automate repetitive tasks, uncover insights from complex datasets, predict operational risks, improve reporting accuracy, and build intelligent assistants that enhance productivity across laboratory, field, and engineering workflows.