The past year has marked a real step change in generative AI’s ability to handle math, statistics, and day-to-day analytics. Work that once demanded manual effort or niche tools is now within reach with the right data foundation and thoughtful guardrails. The oil and gas industry is taking notice, and Well Data Labs was recently featured in the November issue of The American Oil and Gas Reporter (AOGR) for its role in pushing this shift forward.
“A year ago, generative AI models struggled with statistics and math. That is not the case anymore. Today, models can perform everyday analytics if they have the right data presented to them and the appropriate guardrails in place,” said Josh Churlik, CEO of Well Data Labs, in the AOGR article.
This rapid progress is opening the door for practical, high-value use cases across engineering and operations. AI agents are beginning to take on work that historically consumed hours of human analysis—allowing teams to focus on decisions rather than data hunting.
Josh describes one example that’s becoming increasingly achievable with modern models:
“As an industry, we are still figuring out the best ways to leverage generative AI. However, it can automate complex and time-intensive tasks. For example, an engineer could tell it what the company considers a problematic stage, then ask what stages meet those criteria. The agent could then look through the company’s data for thousands of stages and list the problematic ones quickly.”
This is the future operators are moving toward: AI that works alongside engineers, accelerates routine analysis, and surfaces insights hidden in massive datasets.
At Well Data Labs, we’re excited to help teams make that shift—turning powerful models into practical tools that improve real-world operations. Learn more about ChatWDL here.
👉 Check out the full AOGR article titled, “New Tools Turn Data Into Knowledge,” by Colter Cookson in the November issue.
