In January, JPT explored how the drilling sector is increasingly adopting automated and autonomous systems—and why it’s important to understand the distinction. That discussion was centered on a paper from last year’s SPE/IADC International Drilling Conference and Exhibition.
At this year’s conference in Stavanger, these two sides of the same coin were highlighted across several new papers, showing the industry what automation and autonomy look like in practice—particularly in directional drilling.
In SPE/IADC 223649, global service provider SLB outlined an artificial intelligence (AI) system that was used to drill “the most autonomous” section of an offshore well as of 2023. Building on its success, SLB deployed the AI technology again in 2024 for autonomous directional drilling in high‑dogleg severity well sections as part of a 12‑well campaign.
After the first two wells in the campaign were drilled with 85% autonomy, human operators were challenged to outperform the AI-driven system. The results, SLB authors noted, were “astonishing.”
The autonomous system resulted in a 25% increase in rate of penetration (ROP) compared with advisory mode, and a 48% increase in ROP over the average manual-mode operations.
According to SLB, the autonomous directional drilling system not only maintained greater accuracy in following the well plan but also required far fewer interventions compared to human-driven operations.
SLB noted in the paper that advancing the technology from advisory status to full control required overcoming several challenges.
One involved achieving accurate rig-state awareness through sensor fusion which integrates data from multiple sources to provide a clearer picture of downhole conditions. Additionally, SLB developed a new software engine capable of generating trajectory plots for the rotary steerable system (RSS) at each decision point.
Beyond this, the AI-drilling technology needed enhanced resilience to unexpected disruptions in measurement-while-drilling telemetry or downlink. To address this, SLB said the system’s surface deviation controller continuously monitors real-time data and adjusts accordingly, helping the AI-enabled software make corrective actions but “without overreacting” to unplanned situations.
Halliburton is also investing in autonomous RSS technology and detailed its journey in SPE/IADC 223824. The paper highlighted the company’s autonomous drilling platform that seeks to automate various aspects of the operation. Halliburton said the system reduces manual intervention, enabling more staff to oversee remote drilling operations while allowing human drillers to focus on tasks that require their expertise.
Halliburton reported significant performance gains from the platform’s use in the Permian Basin. According to the study, the overall drilling performance improved by more than 80%, with an average increase in ROP of 20% compared with human-led operations.
Halliburton, along with Equinor, presented another conference paper, SPE/IADC 223800, which takes a broader overview of its advancements in automation rather than focusing solely on directional drilling. The paper highlighted what many consider the biggest challenge in this space—not the technology itself, but the incompatible business model, particularly the constraints of service contracts and day-rate drilling agreements.
To overcome this, the paper authors emphasized the need for stronger collaboration with service providers. But it’s not only about financial alignment—it’s about ensuring that previously disparate systems integrate seamlessly to maximize consistency, performance, and risk mitigation.
This is achieved by integrating surface and downhole automation through shared workflows. Real-time monitoring of hydraulics, well placement, and drilling equipment limits help optimize operations and reduce casing-to-casing time. Automated safeguards, anomaly detection, and field-specific learning further enhance efficiency while minimizing nonproductive time.
Halliburton and Equinor stressed that another critical element of its approach is the data exchange and orchestration between service company automation systems. This is done by using OPCUA (OPC Unified Architecture) and MQTT (Message Queue Telemetry Transport).
With this framework, Equinor can connect real-time advisory tools, digital twin simulations, and rig controls, enabling better coordination. The company said this integration also helps balance competing operational goals, such as optimizing well placement while reducing vibration.
The Halliburton-developed system, which Equinor uses offshore, is described in the paper as a “new standard in the industry,” highlighting its platform-agnostic nature, high security, and scalability—able to support everything from small-scale operations to large industrial networks.
In sum, the Norwegian oil company stated that the new framework has overcome a longstanding challenge by achieving seamless interoperability and integration across a wide range of devices and systems.
Piece by piece, the drilling sector seems to be demonstrating that the barriers to greater automation are not insurmountable.
In closing, I’d like to share that a change is coming to JPT. This will be the final monthly issue to include a digital edition and print-ready PDF. Beginning in May, our monthly issues will be available exclusively online as web articles, providing easier access with just one click. Same great content, simplified access.
We will continue to deliver technical content, SPE news, and technology features regularly in our monthly issues, on our homepage, in our newsletters, and JPT LinkedIn page, keeping you updated with the latest industry news. This shift also enhances our ability to serve our global membership more efficiently, providing timely and accessible content wherever you are.
Just as rigs and drilling operations are becoming more digital and streamlined, so are we. This change is part of our continued shift toward a digital-first approach and will not affect JPT’s ability to deliver high-quality content across all our platforms and channels—always prioritizing the needs of our members.
For Further Reading
SPE/IADC 223649 AI Solution Provides the Most Autonomous Framework of Directional Well Sections in High-DLS Well Plans by BA Samba, H. Sahli, R. Loubassou Oumba, et al., SLB.
SPE/IADC 223824 Autonomous Drilling Platform—An Enabler for Automated Steering Control and Remote Operations in the Permian by D. Gonçalves, F. Ferreira, and V.N. Nair, Halliburton.
SPE/IADC 223800 The Automation Advantage: Efficiency Improvements in Offshore Drilling by B. Millward, B. Kabi, and J. Marck, Halliburton, et al.
