If you’re a petroleum engineer, you know what it’s like to stare at a screen full of well data and have to turn it into a coherent report before the 9 o’clock meeting. Or explain the same thing to a geology team, a reserves team and management — each expecting a different kind of language.
Artificial intelligence isn’t going to drill wells for you. But it can take away the most tedious part of your job: initial data processing, report drafting, cross-team communication.
What AI can do with your well data
Most petroleum engineers work with large volumes of data: well logs, production data, core analysis, completion reports. AI can help you:
- Summarize datasets and find trends you’d spend hours identifying manually
- Draft technical reports from tables or software exports
- Compare results from two wells or production periods and flag key differences
- Translate technical terminology into more accessible language for non-technical audiences
- Search and organize technical literature (SPE papers, for example) in minutes
It’s not that AI understands subsurface physics the way you do. It’s that it can process text and structured data very quickly and give you a first draft you then refine with your judgment.
A real workflow: from data to report
Imagine you have the last three months of production performance in a CSV file. The flow can look like this:
- Load the data. Paste or upload it to Claude or ChatGPT.
- Ask for the analysis. “Summarize production by well, identify the 3 with the steepest decline and explain possible causes based on the data.”
- Get the draft. The AI returns a structured text with its observations.
- You review and adjust. You add context only you have: field conditions, intervention history, operational constraints.
- You send it. With your signature and your judgment.
What used to take half a day now takes an hour.
Communication with multidisciplinary teams
One of the biggest pain points for a petroleum engineer is cross-discipline communication. You talk differently to the geologist, the reserves manager, the operations team and the executive suite. AI can help you adapt the same message:
“I have this technical report. Rewrite it in executive language for a 5-minute presentation with management. No engineering jargon.”
Or the other way around:
“I have this executive summary. Give me the technical points I need to dig into for the meeting with the geology team.”
AI doesn’t do this by magic: it does it because you give it the right information and context.
Presentations and bid documents
Another practical use is drafting technical documents for bids, reserves updates or regulatory presentations. AI can:
- Organize and structure your notes into a cohesive document
- Adapt the tone of the document to the audience (technical, regulatory, financial)
- Generate the table of contents, executive summary and conclusions from your data
You bring the technical knowledge. AI brings the drafting speed.
Modeling and calculations: with caution
This is where you need to pump the brakes. AI can help you understand equations, review the logic of your calculations or spot errors in a spreadsheet. But it’s not a simulator. It doesn’t replace specialized reservoir software or well log interpretation tools.
Use it to:
- Review a model’s logic before passing it to the simulator
- Interpret results in plain language for a non-technical audience
- Generate macro or script code to automate repetitive steps in Excel or Python
Never use it to make drilling, intervention or abandonment decisions without rigorous validation on your part. The technical responsibility is yours. Always verify results with your specialized tools.
Start with the report you dread the most
You don’t have to change your entire workflow at once. Take the monthly production report you hate drafting the most and try using AI to assist you this week. Just that.
If I can build complex things with AI without knowing anything about reservoirs or drilling, you with your technical expertise can achieve far more. The first step is starting.
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