Ask Your Oil & Gas Data Anything: Natural Language Queries for Reservoir Engineers

Most production questions start simple.

Which Wolfcamp B wells in Reeves County had the highest 6-month cumulative oil after 2020? What’s Diamondback’s average IP30 in the Delaware compared to Pioneer? Which operators are running the longest laterals in the Bakken this year?

The answers exist in the data. The problem is getting there.

The traditional path involves navigating a state portal, downloading a bulk CSV, opening it in Excel, filtering by county, joining it to a completion table, pivoting on operator name, cleaning up the fact that one operator appears under six different name variations, and finally — thirty minutes later — having something resembling an answer. That’s before you realize the state’s bulk export lags by 45 days.

This is the problem WellStrata’s AI Query interface is designed to solve.

How it works

The AI Query interface is a chat-style input. You type a question in plain English, press enter, and the system returns a structured answer: a natural language summary, a ranked table of wells or operators, or a production chart — depending on what you asked.

Under the hood, the query is interpreted by a language model that understands the domain: it knows what IP30 means, that “Wolfcamp” refers to a formation, that “Reeves County” is in the Permian Basin, that “cumulative oil” is different from “monthly production,” and that you probably want results sorted by the metric you mentioned.

The system then queries the underlying database — 3,300,000+ QC-scored wells across every state we cover — and returns results in the format that makes the most sense for your question.

What it handles well

The interface is built around the kinds of questions reservoir engineers and land analysts actually ask day-to-day:

Formation comparisons: “Compare Wolfcamp A and Wolfcamp B IP30 averages in Lea County over the last three years.” The system understands you want a side-by-side breakdown, not a single merged number.

Operator rankings: “Which operators have the most active wells in the Niobrara right now?” Returns a ranked list with well counts and the formation filtering already applied.

Completion benchmarks: “What’s the average lateral length for Bakken wells completed in 2023 versus 2022?” The system handles the year filtering and comparison logic.

QC-filtered results: “Show me Bone Spring wells with a QC score above 80 in Eddy County.” Because every record in WellStrata carries a data quality score, you can ask the AI to filter on it directly.

State-level rollups: “How many Powder River Basin wells produced more than 50,000 barrels in their first 90 days?” Cross-county aggregation with a production threshold applied at the well level.

Token usage and the trial

Every AI query consumes tokens — the currency of language model compute. WellStrata tracks your monthly token usage transparently in the interface, so you can see how much runway you have left and what each query costs. The trial plan includes 50,000 tokens. The Standard plan provides 200,000 per month, Professional scales to 1 million, and Enterprise to 10 million with overage billing for high-volume workflows.

In practice, a well-formed question typically uses between 500 and 2,000 tokens depending on the size of the result set. The vast majority of day-to-day queries fall well within the Standard plan’s monthly budget.

What it doesn’t replace

The AI query interface is not a substitute for careful reservoir modeling or peer analysis. It is a fast path to the first layer of understanding: figuring out what the data actually says before you decide where to spend three hours.

When you get an answer you want to explore further — say, the top operators come back and you want to see their full production history, or drill into their formation mix — that’s when you move into Benchmarking, Formations Analytics, or the Wells Explorer. The tools are designed to hand off to each other.

The practical upside

The biggest shift for most users isn’t the speed. It’s the reduction in question abandonment. Engineers routinely skip analysis that would take too long relative to the value they expect to get from it. When the barrier to asking a question drops to typing a sentence, questions that used to get skipped get asked — and sometimes those are the most useful ones.

If you’ve ever typed a question into a Slack channel hoping a colleague knows the answer because going to find it yourself wasn’t worth the time, the AI Query interface was built for exactly that moment.

WellStrata covers 18+ US states plus the offshore Gulf of Mexico, with monthly data refreshes from state and federal regulators. The 14-day trial includes full AI Query access with 50,000 tokens — no credit card required.