From Our Team
Insights
Practitioner-level articles on AI, agentic systems, and digital transformation for the upstream oil and gas industry.
Agentic AI for Upstream Oil & Gas: What It Is, What It Isn't, and Why 2026 Is the Inflection Point
A practical guide to agentic AI in upstream oil and gas. What it actually means for production engineers, where it works today, five specific use cases, and how to evaluate whether your operation is ready.
Feb 28, 2026
Dr. Mehrdad Shirangi
How to Deploy an AI Agent for Daily Production Reporting: A Practical Guide for E&P Operators
A step-by-step guide to deploying an AI agent that automates daily production reporting. Covers data requirements, architecture, implementation timeline, ROI measurement, and common failure modes.
Feb 21, 2026
Dr. Mehrdad Shirangi
Why Your Decline Curve AI Keeps Getting It Wrong: Physics-Informed vs. Pure ML Approaches
Pure machine learning models for decline curve analysis fail more often than engineers expect. Learn why physics-informed ML approaches outperform black-box models for production forecasting.
Feb 14, 2026
Dr. Mehrdad Shirangi
MCP Servers for Oilfield Data: Connecting LLMs to Well Logs, Production Data, and Reservoir Models
The Model Context Protocol is transforming how AI connects to data sources -- but nothing exists for petroleum engineering. Here's what an oilfield MCP server looks like and why it matters.
Feb 7, 2026
Dr. Mehrdad Shirangi
The Mid-Size Operator's Guide to AI: What Works When You Have 500 Wells, Not 50,000
A practical AI guide for mid-size E&P operators with 500-5,000 wells. Five projects that deliver ROI without enterprise budgets, plus how to evaluate vendors and avoid costly mistakes.
Jan 31, 2026
Dr. Mehrdad Shirangi