Agentic AI Applications in Upstream Oil & Gas Operations – Transforming Upstream Operations through Autonomous Intelligent Agents – Virtual Instructor Led Training (VILT)

Upon completion of this VILT course, participants will be able to:

• Distinguish agentic AI from generative AI and conventional machine learning by understanding how autonomous agents use planning, reasoning, tools, memory, retrieval, reflection, and agent-to-agent collaboration to perform multi-step engineering workflows.
• Design multi-agent workflows for upstream engineering applications by defining specialised agents, their responsibilities, decision rights, handoffs, arbitration mechanisms, escalation rules, and human approval points.
• Apply agentic AI to practical upstream use cases including exploration, drilling optimisation, reservoir surveillance, production optimisation, well diagnostics, artificial lift, workover prioritisation, and integrated asset management.
• Design the data, retrieval, integration, and governance foundations for agentic systems including RAG, engineering data management, MCP-based tool integration, digital twins, explainability, uncertainty reporting, audit trails, cybersecurity, and model monitoring.
• Develop a practical implementation roadmap for agentic AI in an upstream organisation by evaluating use-case value, data readiness, organisational difficulty, governance requirements, KPIs, pilot selection, and the conditions required for scaling towards greater levels of autonomy.

This course is designed for oil and gas professionals who have a working knowledge of upstream operations and engineering data and want to understand how agentic AI can be applied to real engineering workflows. It is particularly relevant for professionals involved in technical decision-making, engineering analysis, digital transformation, advanced analytics, and the development or implementation of AI-enabled solutions across the upstream value chain.

• Geologist
• Geophysicist
• Petrophysicist
• Data Scientist
• Drilling Engineer
• Petroleum Engineer
• Reservoir Engineer
• Production Engineer
• Completion Engineer
• Technical Manager
• Engineering Manager
• Digitalisation Manager
• Advanced Analytics Specialist
• Drilling Optimisation Specialist
• Production Optimisation Specialist
• AI/ Machine Learning Engineer
• Digital Transformation Manager
• Asset Management Professional
• Integrated Operations Professional
• Reservoir Characterisation Specialist
• Technical Data / Engineering Data Specialist
• Digital Oilfield/ Digital Operation Specialist

• Intermediate

The course uses a practical, application-focused learning approach combining instructor-led sessions, live demonstrations, realistic upstream case studies, browser-based hands-on labs, group exercises, technical discussions, and a final capstone exercise. Each half-day includes a combination of technical modules, a live demonstration, and a worked case study or hands-on activity. Participants work with supplied datasets and case materials through a browser-based Streamlit exercise environment, allowing them to explore agentic workflows without requiring local software installation or programming.

Your expert VILT instructor brings extensive experience across oil and gas, geophysics, reservoir engineering, software development, advanced analytics, and artificial intelligence. He has 14 years of experience in the Oil and Gas industry as a geophysicist and reservoir engineer, more than 11 years of middle-tier software development experience with SAS Institute Inc., and 18 years of upstream Oil and Gas data-driven model building across Exploration and Production. His professional interests include developing AI analytical workflows and data-driven Machine Learning and Deep Learning predictive and prescriptive models across the upstream Exploration and Production value chain, as well as applying AI and soft-computing technologies to Digital Oilfield and IIoT workflows.

He has founded his own consultancy firm, where he provides global O&G Artificial Intelligence training courses for operators. His work includes developing AI training courses for Petronas, Shell, BP, Chevron, Petrobras, YPF, ONGC, PSO, and PDO. His product development work covers Agentic AI, Generative AI, Machine Learning, Deep Learning, and Reinforcement Learning, with applications including bypassed pay solutions, reservoir management, drilling optimisation, seismic analysis, petrophysics, geochemistry, and geophysics. This work directly relates to the application-oriented focus of agentic AI across upstream operations covered in this programme.

He also has extensive experience with SAS Institute Inc., where he held several roles. From 2020 to 2025, he served as an R&D Advanced Analytical Algorithms Product Manager, advising on and developing SAS IoT R&D algorithms for real-time event-stream processing of sensor data. Since 2012, he has also served as an Advisory Industry Consultant, contributing to innovative oil and gas solutions based on advanced analytical methodologies, developing specialised tools and applications based on data-driven models, supporting access to historian and upstream data, advising operators on Centres of Excellence, and educating oil and gas operators and service companies in Machine and Deep Learning methodologies. Earlier, he was a Principal Solutions Architect and Principal Software Developer at SAS, working on advanced analytics, predictive models, reservoir characterisation, drilling and production optimisation, software development, data modelling, graphics, and visualisation.

His earlier oil and gas career includes positions as Senior Geophysicist with PGS Tensor, Senior Geophysicist with Petroleum Development Oman, and Geophysicist consultant to ARCO and BP. At PGS Tensor, he worked in seismic processing and velocity analysis and generated seismic attributes for soft-computing workflows including multivariate analysis, principal component analysis, neural networks, fuzzy logic, and genetic algorithms. At Petroleum Development Oman, he processed and interpreted seismic land and marine 2D and 3D data and worked on reservoir characterisation and rock-property analysis. His work with ARCO and BP included seismic interpretation, reservoir-property analysis, uncertainty and risk assessment, and analytical workflows across the E&P value chain.

He has also contributed to the oil and gas industry through patents, publications, technical papers, conference presentations, and professional committees. His issued patents include Control Variable Determination to Maximize a Drilling Rate of Penetration and Fluid Flow Back Prediction, while another application addresses machine learning methodology for geological tops identification automation. He authored Harness Oil and Gas BIG DATA with Analytics: Optimize Exploration and Production with Data-Driven Models and co-authored Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models. He has presented technical papers covering digital oilfields, reservoir characterisation, drilling optimisation, predictive analytics, unconventional reservoirs, well performance monitoring, and data-driven models. He is a Fellow of the Geological Society of London and a member of SPE, SEG, and EAGE, and has held several SPE committee and chairperson roles related to petroleum data-driven analytics, advanced analytics, and upstream digitalisation.

Unlock the potential of your workforce with customized in-house training programs designed specifically for the energy sector. Our tailored, in-house courses not only enhance employee skills and engagement but also offer significant cost savings by eliminating travel expenses. Invest in your team’s success and achieve specific outcomes aligned with your organization’s goals through our expert training solutions. Request for further information regarding our on-site or in-house training opportunities.

In our ongoing commitment to sustainability and environmental responsibility, we will no longer providing hard copy training materials. Instead, all training content and resources will be delivered in digital format. Inspired by the oil and energy industry’s best practices, we are leveraging on digital technologies to reduce waste, lower our carbon emissions, ensuring our training content is always up-to-date and accessible. Click here to learn more.

To further optimise your learning experience from our courses, we also offer individualised coaching support. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It can be delivered virtually through video conference or face to face by one of our senior subject matter experts. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Learn more about our post training coaching services here.