AI-Driven Energy Data Integration and Prospect Evaluation with Sashi Gunturu

No Cost for class, breakfast provided!  

High-Level Course Overview

This curriculum is designed to empower energy professionals through the  PIEScale  (Petrabytes Intelligence for Enterprise at Scale) ecosystem. By integrating the OSDU Data Repo, comprehensive energy databases, and real-time OSI PI sensor data, this course facilitates  Accelerated Scientific Discovery  and  Rapid, Low-Cost Improved Modeling . Students will master a verticalized framework for energy data management, transitioning from manual workflows to AI-driven environments where  Agentic AI  assists and accelerates tasks across data ingestion, subsurface interpretation, and predictive modeling.

Learning Objectives

By the end of this course, students will be able to:

1. Implement  Agentic AI frameworks utilizing the core formula: Agent = AI Models + Tools + Memory.
2. Apply  the Medallion Design Pattern in a Lakehouse Architecture, specifically managing the transition from Raw Data to Silver Layer auto-mapping.
3. Execute  automated parsing of unstructured headers and numerical sections into JSON and Dataframes using LLMs to generate Python code.
4. Integrate  real-time edge sensor data (BHP/BHT) from OSI PI using protocols like OPC UA, Kafka, and MQTT.
5. Classify  subsurface intervals using a specific 6-tier lithology scheme: Shale, Silty Shale, Siltstone, Sandy Shale, Sandstone, and Clean Sand.
6. Analyze  geomechanical stability by evaluating wellbore failure "what-if" scenarios across varying Tectonic and Stress Regimes.
7. Optimize  drilling plans by calculating the Safe Mud Window and analyzing formation pressure.
8. Model  rock-mechanical data through 3D core analysis and volume strain simulations.
9. Simulate  reservoir performance via iPerf workflows, emphasizing the "Compare & Calibrate" logic between logs and seismic data.
10. Evaluate  prospect suitability by ranking targets on a 1-10 scale using the RankMyLand and AcuGridz indices

Sashi Gunturu is the founder of Petrabytes and a technology leader in digital energy solutions, with nearly two decades of experience in the upstream oil and gas industry. His expertise includes geomechanics, subsurface data workflows, data modeling, data ingestion, and data integration, with a strong focus on transforming complex oilfield datasets into actionable business and technical insight. At Petrabytes, he has led development of cloud- and edge-enabled analytics platforms that support subsurface modeling, fiber-optic sensing, and integrated visualization for energy operations. He holds M.S. degrees from The University of Tulsa in Petroleum Engineering and Computer Science, and a B.Tech. in Chemical Engineering from Andhra University. Gunturu is a frequent speaker on OSDU, energy data standards, and AI-enabled workflows for the oilfield