Commentary: The next frontier in offshore drilling will be led by people, but powered by data

Mobolaji Adediran, SLB

Across the energy industry, automation and data-driven decision-making are transforming the design, drilling, and completion of wells. What once depended primarily on experience and instinct is now augmented by a powerful ecosystem of real-time analytics, advanced formation evaluation tools, and machine learning. Yet even as technology transforms the process, one truth remains constant: human judgment determines whether innovation translates into operational success.

In one of the North Sea offshore drilling projects led by this author, while drilling in the reservoir section, the Measurements While Drilling (MWD) tool in the BHA (Bottom Hole Assembly) that sends formation evaluation data to the surface, suddenly started sending back error/incorrect data, which was decoded as a possible tool failure. Drawing on offset data and experience, the drilling team identified that intense shocks from drilling through a hard Anhydrite layer were causing the issue. With this information, the drilling team then adjusted the weight on the bit and rotary speed to reduce vibration, which restored accurate readings and ensured the formation evaluation could continue without non-productive time.

Over the past decade, digitalization in well construction has accelerated from isolated experiments to an integrated standard of operation. Automation now streamlines routine tasks such as tripping, mud circulation, and directional control, freeing engineers to focus on interpreting data and optimizing performance. Meanwhile, high-frequency sensor data, transmitted in real time from downhole tools, provides unprecedented visibility into wellbore conditions. The result is faster decision cycles, reduced non-productive time, and safer operations in environments that demand precision and discipline.

The key to unlocking these benefits, however, lies not in replacing people with machines but in redesigning workflows that align technology with human expertise. Automation performs best when guided by clearly defined objectives and an understanding of geological complexity. Engineers who can interpret automated insights and integrate them with field experience are the ones driving meaningful performance gains.

Safer and smarter operations

The integration of real-time data across drilling and formation evaluation has created a fundamental shift in how decisions are made at the rig site. Instead of reacting to problems after they occur, engineers can now predict and prevent them from happening. Pressure anomalies, tool vibrations, and formation changes are monitored continuously, triggering automatic alerts and corrective actions before conditions escalate.

These capabilities have dramatically improved safety and efficiency. Automated control systems, informed by continuous data streams, can adjust drilling parameters in milliseconds to maintain stability and reduce the risk of kicks or losses. Predictive analytics can forecast bit wear, optimize drilling trajectories, and detect early signs of wellbore instability, minimizing downtime and environmental impact.

These beneficial dynamics recently played out on a project in Norway. In this case, real-time formation data showed a higher-than-expected equivalent circulating density, indicating an influx of formation fluids. Recognizing that we were entering a high-pressure zone, we quickly advised increasing the mud weight and reducing the rate of penetration. Continuous monitoring confirmed that the adjustments were effective, preventing the influx from escalating into a kick or blowout.

As illustrated above, even as automation improves consistency, human oversight remains essential. The most advanced algorithms cannot always account for contextual factors such as operational constraints, local geology, or stakeholder priorities. Real-time data can indicate a deviation, but experienced engineers must judge whether it represents an acceptable risk or a necessary adjustment.

Successful implementation of digital technologies depends on creating a feedback loop between the rig and the control center. Engineers and data scientists must work closely together to ensure that models evolve in line with field realities. When human experience informs data interpretation, and data insights enhance human understanding, efficiency and safety both advance in tandem.

Building the right culture

The future of well construction will depend not only on technical innovation but on how organizations integrate it into their operational culture. Training engineers to interpret and act on automated insights is just as critical as deploying the technology itself. The next generation of drilling professionals must be fluent in both domains: understanding the physics of drilling and the logic of algorithms.

Global training initiatives that combine simulation-based learning with live data analysis are already producing that blend of skills. Engineers now learn how to manage autonomous systems, evaluate data quality, and identify when to intervene manually. The ability to discern when automation should be trusted and when it should be questioned is becoming the hallmark of operational excellence.

Leadership plays a pivotal role in maintaining that balance. As technology advances, the temptation to over-automate grows stronger. Leaders must ensure that systems are designed not just for technical efficiency but for human usability. Clear visualization tools, intuitive interfaces, and transparent analytics allow engineers to engage with data rather than be overwhelmed by it. Incorporating field team feedback into system design is another critical step. The best innovations emerge when the people who use the tools have a voice in shaping them. A drilling automation framework that respects human judgment and operational context will consistently outperform one that assumes technology knows best.

The industry’s most forward-thinking leaders now view automation as its collaborator, not a replacement for human skill. They see technology as an amplifier of experience, a means to transform instinct into insight, and insight into repeatable performance.