From manual reports to real-time insight: Rig performance monitoring with Intelie Live

Every minute a drilling problem goes unnoticed is a minute it gets more expensive to fix. Across the industry, non-productive time still eats up twenty to thirty percent of total drilling time on a conventional well, and much of it traces back to the same root cause: information that existed in the data long before it reached the people who needed to act on it. Intelie Live's Drilling & Performance application closes that gap. Built to reduce invisible lost time (ILT) at the source, it turns raw rig data into rig performance monitoring that works continuously, not on the schedule of the next data field update.

Automatic detection: the key to catching drilling issues early

‍
Manual data field reporting depends on someone noticing a problem, describing it accurately, and passing it up the chain before anyone off-site can respond. That process was built for recordkeeping, not for speed, and every handoff inside it adds delay. Drilling & Performance removes the handoff. Automatic Rig State Detection uses machine learning to classify what the rig is doing in real time, tripping, drilling, circulating, connecting, and flags the moments where behavior drifts from what that state should look like.

Real-time rig performance and rigfloor KPI Classification runs alongside it, tracking rate of penetration, slip-to-slip time, connection duration, and the other metrics drilling engineers already use to judge performance, and updating them continuously instead of at shift change. A torque anomaly that signals early stages of a stuck pipe event, a pressure trend consistent with poor hole cleaning, a kick indicator building over several connections: these surface as soon as the pattern appears in the data, not after they show up as a problem the rig floor has to react to.  

Take a tripping operation as an example. A crew pulling out of hole expects a predictable pattern of hookload and torque through each stand. When drag starts climbing outside that expected range, Automatic Rig State Detection and physical models have already classified the activity and Real-time KPI Classification has already flagged the deviation, putting the anomaly in front of the drilling engineer while there is still time to slow down, circulate, or adjust rather than after the string is stuck.  

None of this replaces the people running the rig. It removes the lag between what the data already shows and what the person managing the well actually sees, so the response happens in minutes instead of at the next scheduled report.  

Historical Performance Analysis adds the layer that a single well's data cannot provide on its own. Once an anomaly is flagged in real time, drilling engineers can immediately check it against how similar wells, rigs, or crews handled the same situation, so the response draws on pattern recognition across a fleet instead of one person's memory of what usually works. Most drilling operations software stops at showing the current well. Rig performance monitoring that includes that historical context turns a flagged anomaly into a decision drilling engineers can make with confidence, in the moment, instead of a guess made under pressure.

‍From the rig floor to the operations center

‍
Catching an issue early only matters if the right person sees it without delay, which is why Drilling & Performance is built to move insight from the wellsite to the operations center on the same platform, not across a chain of calls and separate reports. Benchmarking and RPI, the Rig Performance Index, gives operations managers a consistent way to compare rigs, crews, and wells against each other, so a rig that quietly starts underperforming is visible against the fleet, not just against its own history.  

Annotation and QA/QC tools keep that comparison honest. A KPI is only useful if the data underneath it can be trusted, so values are validated and normalized before they ever reach a dashboard, which is what makes cross-rig and cross-crew benchmarking mean something instead of comparing numbers calculated five different ways. Automated Performance Reports then turn that validated data into daily and weekly summaries, generated on schedule rather than assembled by hand, freeing drilling engineers from the transcription work that used to consume hours better spent on the well itself.  

This is digital oilfield analytics working the way operations managers actually need it to: one continuous view running from the rig floor to the operations center, not a stack of drilling operations software that each stop at their own piece of the picture. Today that view runs across more than 3,000 wells drilled with real-time optimization, 50+ offshore rigs connected globally, and over 55 million feet of drilling operations monitored continuously, with field engineering resource requirements cut by 35 percent on deployments where the manual workload it replaces was measured directly.

Looking ahead

Rig performance monitoring built this way changes what a status update is for. Instead of a call to establish what already happened, drilling engineers and operations managers start from a shared, validated view of the well and spend their time on what to do next. That shift, from reconstructing the past to acting on the present, is where the real value of real-time monitoring lives.  

As more of the drilling lifecycle runs through the same connected view, from planning through execution to reporting, the gap between an issue forming and a person acting on it keeps closing. That is the direction rig performance monitoring is heading, and it is the problem Intelie Live's Drilling & Performance application was built to solve.  

The same logic extends past drilling. Completions crews face the same relay of manual updates on a frac pad, and the same platform that classifies rig states and flags drilling anomalies applies the same continuous approach to stage detection and completions performance. The application changes, but the principle holds: the well and the pad generate the signal constantly, and digital oilfield analytics only earns its place when it watches that signal continuously instead of waiting for someone to write it down.  

Intelie Live's Drilling & Performance application gives drilling engineers and operations managers continuous, real-time visibility into rig performance, catching issues as they form instead of after a manual report describes them. To learn more, visit intelie.com.

FAQs

1. What is rig performance monitoring?

It tracks rig activity, KPIs, and drilling data in real time, helping teams identify performance issues and take action before they cause costly delays.

2. How does real-time monitoring help?

Real-time monitoring helps drilling teams spot unusual trends early, respond faster, reduce non-productive time, and improve overall rig performance.

3. What is Automatic Rig State Detection?

Automatic Rig State Detection uses machine learning to identify rig activities such as drilling, tripping, circulating, and connecting in real time.

4. Why is historical performance analysis useful?

It lets drilling teams compare current operations with previous wells, rigs, and crews, helping them make faster and more informed drilling decisions.

5. How does Intelie Live improve rig performance?

Intelie Live provides real-time visibility, KPI tracking, benchmarking, anomaly detection, and automated reports to support better drilling performance and decisions.

‍