Commentary: Drilling automation can now integrate predictive intelligence for faster decision making

Morten Welmer, Sekal AS

Norway’s energy sector has a storied legacy of pioneering drilling innovations, and 2025 was no exception. Proving that a new era of digital drilling is here, Equinor advanced the world’s first automated on-bottom drilling system on the Norwegian Continental Shelf (NCS)—a technological success being replicated in exploration hot spots and frontier areas.

Drilling automation tools with dynamic and adaptive control not only detect early warning signs but also help drillers visualize what comes next by continuously adjusting operational parameters based on actual wellbore conditions. Actively managing processes with a digital twin and real-time data helps crews prevent costly issues such as stuck pipe, lost circulation, borehole instability, formation damage and underground blowouts. Such safety and efficiency gains are vital in complex well sections where the costs and risk are magnified.  

Real-time forecasting

As drillers aim to crush rock faster in challenging formations, they require rate of penetration (ROP) improvements that are both predictable and sustainable. They also depend on subsurface teams’ real-time assessments of well stability, pressure windows and other key safety data to continue course while protecting the bottomhole assembly (BHA) and downhole equipment.

However, the industry’s traditional manual processes and technology silos create inefficiencies that prevent sharing wellbore insights in real time. As a result, most drilling operations still encounter unforeseen problems, with unnecessary sidetracks that set back success and lead to lost or delayed production.  

These fragmented drilling and subsurface workflows have challenged the industry's pursuit of a truly integrated automation system—until now. Advanced analytics powered by real-time models are resolving these historic challenges by increasing wellbore visibility and rig control, and shifting operations from passive to predictive.

Drilling automation tools also use real-time forecasting to detect early symptoms and prevent drilling dysfunctions. This increases situational awareness so that drillers can minimize operational risks and safeguard critical equipment.

Dynamic, adaptive control

A drilling automation control system is required to effectively oversee the wellbore, protect it and safeguard equipment while also optimizing operational parameters. This sits above the machine control, which serves as the foundational layer for advanced automation systems. The machine control enables remote control of individual or multiple machines, such as from the driller’s cabin, to unify the process by not exceeding the limits of the machinery.

The drilling control system enables static automation of predefined tasks, such as executing planned tripping schedules. These steps are carried out repeatedly without consideration of real-time changing wellbore conditions or overall progress. Unlike static automation, a dynamic and adaptive control system uses built-in physical models (integrating hydraulic, thermodynamic and mechanical models) to automatically adjust these envelopes in response to changing conditions. This helps ensure that safeguard and protection functions are continuously updated with accurate limits.

If any parameter exceeds a defined threshold and before it breaches a wellbore limit, such as surpassing the pressure window, the drilling automation system’s safeguard and protection function is automatically activated.

To optimize tripping and drilling processes, the dynamic and adaptive control system adjusts the necessary parameters to bring them as close as possible to the operational limits without exceeding them.

Orchestrated automation

Achieving closed-loop drilling automation requires an amalgamation of integrated well engineering, integrated well delivery solutions and advanced rig automation.

In 2025, drilling and subsurface teams put emerging technologies to the test in Equinor’s NCS campaign by combining Halliburton’s automation and remote operations software with Sekal’s real-time simulation modeling capabilities. Risk mitigation in well construction was the cornerstone of this collaboration.

One of the main objectives of the integrated automation solution was achieving consistency and predictability in drilling operations. This was demonstrated successfully during the NCS campaign through dynamic automated rig control, supported by a remote operations team who stay in the loop and remain vigilant about what is happening at all times.

Some solutions can have conflicting objectives that must be harmonized to provide a consistent set of actions, such as advisory drilling parameters for automating operations. Examples are ROP that is typically to be maximized while not exceeding a technical threshold from a hole cleaning point of view; or drilling parameter targets and limits derived from directional, mechanical, or hydraulic objectives that can conflict as they seek to optimize different aspects of the drilling process.

For this collaboration, the oilfield service companies developed an orchestrator control system to centralize smart tech such as automated geo-steering with digital twin and advisory screen solutions. External constraints and driller-defined limits also were integrated. The orchestrator works by linking the dynamic and adaptive rig control with an automation platform to automatically adjust and optimize the campaign’s safe operating envelopes. Autonomous directional drilling was deployed, further optimizing control while monitoring mud properties.

This orchestrated automation incorporates integrated front-end engineering with automated real-time anomaly recognition and dynamic safeguards. These features work together to eliminate invisible lost time and non-productive time, significantly reducing the risks associated with drilling operations.

Collaboration among service companies brings forward continuous improvement and learning. This is vital to the industry as a whole. By capturing field-specific domain knowledge and applying best practices from well to well, this new approach ensures that each operation can benefit from the lessons learned in previous ones. From a drilling automation perspective, this approach leverages field-proven real-time optimization and safeguarding, applied directly to rig machinery controls. Further, this creates a scalable framework that unifies multiple independent — sometimes conflicting — recommendations related to separate aspects of drilling for better performance, especially in difficult scenarios.

Proactive problem solving

Predictive intelligence depends on real-time dynamic models that together simulate the borehole conditions and physical processes during drilling operations. Using advanced drilling automation, these models are continuously calibrated with real-time data, such as depth, temperature, flow rates, rotation and string velocities, to ensure that they are aligned with actual conditions.

The system fills the data gap behind the bit to include the often little-understood processes that influence the rest of the borehole. This virtual well is rich with data so operators can assess crucial factors such as fluid volumes, fluid velocity, cuttings proportions, pressure, temperature, equivalent circulating density (ECD) and friction along the complete drill string from bit to surface. This holistic view makes it easier to detect anomalies and helps operators make proactive adjustments to ensure optimal conditions for each section of drilling. It means no more guesswork but reliable outcomes, underpinned by data.

Such a step change goes beyond real-time monitoring. The tool can be applied to legacy well programs to uncover embedded clues in drilling records, helping to reshape understanding of the subsurface, inform planning for future wells and avoid past mistakes.

A smart upgrade

Offshore drilling continues to increase in complexity, cost, and risk. Success hinges not only on monitoring what’s happening but predicting what’s about to happen and making the right intervention at the right time as the well progresses. 

Infield experience shows that real-time forecasting models can make meaningful impacts to ROP, hole cleaning and managing narrow pressure margin, to name a few scenarios. These predictive monitoring tools bring drilling roadmaps to life, so crews can automatically detect and respond to changes in parameters during drilling and make the best decisions for every well section.

In wells where there’s a narrow pressure margin, accurate real-time data is more important than ever. Mud weight and ECD are critical metrics that need to be confined to a narrow window, which is much easier when the crew has regular updates on the situation. Experience shows that wells can tolerate occasional ECD peaks, but repeated instances of exceeding the peak lead to deterioration. Real-time analytics give crews a safer buffer to optimize drilling while managing pressure constraints.

Three recent case studies highlighted the efficiencies that drilling automation tools can bring. 

Case study 1

This case study involved running liner through a collapsed formation. The Hordaland/Rogaland formation in the Norwegian North Sea is known to become unstable over time. Time-sensitive breakouts can be expected when running liner string. While drilling this formation, the hole collapsed while running the liner in hole. After several attempts to run the liner through the collapsed area, the driller decided to pull out of the hole.

In a last attempt, the driller utilized real-time hydraulics visualization with the advisory screen. Bringing the drilling roadmap to life, the dynamic advisory tool guided the driller during a stressful situation by gradually ramping up the pumps without fracking the formation until eventually establishing flow again to clean the area. The driller was able to control parameters while successfully landing the liner to total depth (TD) and cementing in place, avoiding a cleanout run. Importantly, this advanced drilling automation solution generates velocity limitations continuously that are tailored to the current well conditions and parameters (dynamic limits).

Case study 2

In this case, Sekal assisted Equinor with the world’s longest well drilled from a floating rig and helped the operator reduce cost by delivering a record in trip time. In this case, drilling automation with real-time predictive monitoring provided safe, cost-efficient drilling for a long horizontal well in complex offshore conditions at the Troll field. The operator was advised on limits for tripping speed and automated, dynamic and safeguarded control of the tripping schedules. The actual speed utilized was at 96% of the modelled limits. Such automated guidance on trip speed allowed for an average speed of 830 m/h, resulting in an all-time record trip time in open hole.

Case study 3

Highly deviated wells can be challenging to clean. While drilling a highly deviated section offshore Norway, a steady increase in annular pressure loss was observed over several hours, suggestive of hole cleaning issues. Stable torque, drag and pump pressure indicated manageable cuttings bed formation. The issues were discussed and a new cleaning strategy implemented – increase RPM for 15-20 minutes – which the simulation suggested would suspend the cuttings and clear the hole. The rig crew followed the procedure, resulting in a significant reduction in ECD, confirming the strategy’s effectiveness.

The transient hole cleaning model correlated with the following independent observations illustrated within the dynamic model:

• Modeled and actual ECD trends slowly reduced to a stable minimum from 1.482 specific gravity (sg) to 1.466 sg.
• Rotational friction (torque) and free-rotating weight trends were stable during reciprocation at TD.
• SPP (standpipe pressure) trend decreased from an initial 285 bars to 276 bars and remained stable thereafter.

Unlocking the full potential

The full potential of drilling automation integrating physics-based models with predictive intelligence is only now being realized.

By marrying real-time downhole data with powerful algorithms, teams can monitor highly complex processes and accelerate decision-making. Drilling automation brings forward preventative actions that eliminate invisible lost time while empowering teams to drill faster with consistent, repeatable performance.

The industry has the advanced capabilities to transition confidently into a new way of drilling that improves productivity, economics and safety.