Welcome to the Agentic Oilfield
I've been working in oil and gas IT for almost 30 years, and I love this industry. I love its grit, its problem-solving culture, and the people who keep it running around the clock in places most of the world never sees.
It's also the only industry I know where you can pull off amazing feats of engineering, backed by enormous capital investment, while the business around them runs on spreadsheets and paper. For much of my career, my job was trying to change that. A few years ago, I stopped trying to change it from the inside and started building the thing I wished existed.
An Industry of Brilliant Tools and Manual Processes
Walk through a typical day in operations and the pattern is hard to miss.
A production engineer starts the morning by pulling data from the historian, the production accounting system, and a spreadsheet someone maintains by hand, then reconciling them because the numbers don't quite match. A pumper drives a route that was planned the same way it was planned ten years ago. A field ticket gets written on paper, photographed, emailed, rekeyed into one system, then disputed and reconciled by someone in another company rekeying it into theirs. A workover request moves from an engineer to a superintendent to a rig contractor through a chain of calls and texts. Critical knowledge about why a well behaves the way it does lives in the head of someone who is five years from retirement.
None of this is because oilfield people lack sophistication. It's because the industry invested its innovation where the value was most obvious: in the physical work of finding and producing hydrocarbons. The processes and IT systems around that work grew up piecemeal, one acquisition, one vendor, and one workaround at a time. The result is a landscape of disconnected systems held together by people.
People are the integration layer of the oilfield. That's the problem.
Why Past Fixes Didn't Stick
This isn't the first attempt to change that. The "digital oilfield" movement gathered real momentum in the 2000s, promising integrated operations, real-time decision-making, and a fundamentally new way of working. Major operators invested heavily in it.
What it mostly delivered was better visibility: remote monitoring centers, more sensors, better dashboards. Those were real gains. But the way work actually got done changed far less than promised. The reason is instructive. The traditional path to process change ran through systems integration: standardize the data, connect the platforms, rebuild the workflows on top. In an industry this fragmented, that path was long, expensive, and often abandoned partway through as priorities, prices, and ownership changed.
The lesson wasn't that the vision was wrong. It was that the route to it was too long.
A Different Kind of Operating Model
The agentic oilfield takes a different route.
In an agentic operating model, AI agents do work rather than just display information. They monitor operations continuously, reason across systems, carry out defined tasks, and bring people in when judgment or approval is needed. An agent can watch daily production across a field, notice a well running below its normal rate, check the latest measurement data and well test, pull the pumper's recent notes, and put that well at the top of tomorrow's route with a likely cause attached. That's not the future; it's the kind of workflow we run today.
What makes this different from past waves is how agents interact with the messy reality of oilfield systems. Traditional integration demanded that data be clean, structured, and connected before anything useful could happen. Agents can work with systems as they are. They can read a PDF well file, parse an email from a vendor, query a historian, and reconcile what they find, much as a capable person does today, but continuously and at scale.
That's why the agentic model has a real chance to leapfrog the industry's process problems rather than solve them the slow way. Just as some regions skipped landlines and went straight to mobile, operators may be able to skip the decade-long integration projects and go straight to a model where agents become the connective tissue between systems and people.
Looking Ahead: Agent-to-Agent Workflows
The biggest opportunity comes into view when agents start working with each other.
Start inside a single company, where we're already doing this. A surveillance agent spots an underperforming well and hands the case to a diagnostics agent. The diagnostics agent identifies a likely cause and passes a recommended intervention to a planning agent, which checks crew schedules and equipment and slots the job into the week. A person approves the plan. What used to take days of meetings and handoffs happens in hours, with a full record of how each decision was reached.
Now extend that across company lines, where the oilfield's most manual processes live. The oilfield isn't one organization; it's a web of operators, service companies, midstream partners, and suppliers. Much of the friction sits in the handoffs between them: requesting services, confirming availability, reconciling field tickets, settling invoices. Picture an operator's agent requesting a rig from a contractor's agent, agreeing on timing, and later reconciling the ticket automatically against what was actually performed.
We should be honest that this second stage is the furthest out. Agent-to-agent work between companies requires trust, clear permissions, audit trails, and commercial agreements that are still being worked out. But it's the destination worth building toward, because it attacks the part of the industry that past technology waves never reached.
What It Will Take
The leapfrog is real, but it isn't automatic. I know because we've hit every one of these walls building it. Three things separate organizations that will benefit from those that won't.
Redesign the work, don't just automate it. An agent pointed at a broken process produces a broken process that runs faster. The organizations that win will use agents as the occasion to ask how work should flow, not just how to speed up the way it flows now.
Take data quality seriously. Agents are far more forgiving of messy data than traditional integration, but they aren't magic. Inconsistent well names and gaps in historical data still limit what agents can do reliably. The good news is that agents can help clean up the very data they depend on.
Govern it like an operating model. Deciding what agents can see, what they can do on their own, and when they must ask a person is a leadership decision, not an IT setting. Start with well-scoped workflows, earn trust, and expand autonomy deliberately.
What It Means for the People Doing the Work
For operators, the agentic oilfield means scaling attention without scaling headcount, shrinking the gap between when a problem appears and when someone acts on it, and capturing hard-won expertise in how the operation actually runs before it retires.
For engineers, it means spending the day on engineering instead of data wrangling. For field teams, it means priorities that already reflect production impact and equipment status. For everyone, it means working alongside a new kind of colleague, one you delegate to rather than operate, and whose work you review rather than redo.
It also means new skills. Knowing how to frame a task for an agent, check its work, and set the right boundaries will matter as much as spreadsheet fluency did a generation ago.
Closing the Gap
The oilfield has always been willing to adopt radical technology when it could see the value. What it hasn't had is a practical way to bring that same innovation to how the business runs. The agentic operating model offers one, not by asking the industry to finish the integration projects it never could, but by meeting its systems and people where they are.
The industry that mastered the subsurface can now modernize everything above it.
Get Started
That's why I built Wellsite. Here's the hard truth I kept running into: the operators who can most easily afford to start on this are the ones who least need the help. The largest players are already building agentic capabilities in-house. The independents and the small and midsize operators, the backbone of this industry, don't have the teams or the budgets to do that on their own.
Wellsite is how they participate anyway. It brings the agentic oilfield to operators large and small, without the decade-long integration projects or the in-house AI team. If you've felt like this future was being built for someone else, it wasn't.