Gen AI and LLMs for Geoscientists and Petroleum Engineers

Monday, 17 November 2025 | Kuala Lumpur, Malaysia


**To register your interest, please email to Cammy Chee (cce@eage.org) and/or Vini Jayne Krishna (dsa@eage.org) before 27 October 2025.

Please note: This course will only proceed if the minimum number of participants is reached.

InstructorDr. Malleswar Yenugu (Drake AI)
LanguageEnglish
Duration1-day
FormatBootcamp Format


Course Description

This short course introduces participants to Gen AI and Large Language Models (LLMs) and their applications in the oil & gas industry. It provides a mix of theory, use cases, and hands-on exercises—covering prompt engineering, fine-tuning, and deploying custom LLM-powered assistants tailored to upstream workflows like log interpretation, drilling report summarization, and seismic report tagging.


Learning Objectives

By the end of this course, participants will:

  • Understand the basics and applications of LLMs in Oil & Gas exploration and production.
  • Learn how to fine-tune LLMs for subsurface data, logs, and reports.
  • Gain hands-on experience building and deploying domain-specific LLMs on private datasets.
  • Explore tools and frameworks for secure and efficient LLM training.


Participants' Profile

  • Geoscientists and petroleum engineers interested in applying AI/GenAI/LLMs to upstream workflows.
  • Professionals working with well logs, drilling reports, seismic data, and subsurface documentation.
  • Energy sector technical staff seeking practical skills in AI adoption for exploration & production.


Pre-requisites

  • Basic knowledge of Python.
  • Familiarity with petroleum/geoscience domain (logs, reports, etc.)
  • Laptop with at least 8GB RAM, browser access.


Software & Tools Used

  • Google Colab / Jupyter Notebook
  • Hugging Face Transformers
  • LangChain
  • OpenAI / Ollama / Local LLMs
  • Docker (for deployment)
  • Sample datasets: drilling reports, lithologs, LAS files, core analysis PDFs


Course Materials Provided

  • Slide deck (PDF)
  • Sample notebooks and scripts
  • Dataset samples (well logs, reports)
  • Cheat sheet: Prompt engineering for geoscientists
  • Reference guide for deploying RAG-based apps


About the Instructor

Dr. Malleswar Yenugu, a distinguished Ph.D. in Geophysics from the University of Houston, stands at the forefront of digital transformation in the oil and gas sector. With deep expertise in subsurface data interpretation and reservoir characterization, Dr. Yenugu has become a sought-after guest lecturer at prestigious institutions including Stanford University and IIT Bombay, sharing his profound knowledge and insights. 

As CEO of Drake AI USA and a serial entrepreneur, Dr. Yenugu is pioneering the integration of AI and Generative AI into upstream oil and gas operations. His leadership has driven the development of Drake, a cutting-edge platform designed for predictive maintenance, petrophysical automation, and optimization across exploration and production workflows. He actively champions digital transformation, recently delivering a talk on "AI and Gen AI for Oil and Gas Production Optimization and Artificial Lift Failure Prediction" at the SPE Evangeline Section.

Beyond his contributions to the energy sector, Dr. Yenugu is the visionary founder of Kalpra Tech Solutions, overseeing the strategic development of AI-first products such as Moe Chatbot, Keppler, and PraiseTech. He is a driving force in Generative AI innovation, with hands-on experience building NLP chatbots, diagnostic tools, and AI-driven predictive analytics across diverse sectors. Through Kalpra Academy on YouTube, he extends his passion for education, actively sharing insights and course demos on Generative AI and Machine Learning.

Dr. Yenugu’s unique blend of academic rigor in geophysics and entrepreneurial acumen in AI application makes him an invaluable asset. His deep technical knowledge in petrophysics, reservoir engineering, artificial lift systems, seismic interpretation, and log analytics, coupled with strong leadership and communication skills, effectively bridges the gap between technological innovation and practical industry application. He is actively engaged with professional bodies like the Society of Petroleum Engineers, presenting on productive intelligence and digital transformation, and under his guidance, Drake AI and Kalpra have showcased AI-driven solutions at prominent events such as IMAGE24.


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