The system monitors cementing equipment in real-time, prepares for upcoming jobs, and provides direct insight into equipment operation and performance. (Image source: Halliburton)

Halliburton has launched LOGIX unit vitality, an AI-powered platform that delivers actionable insights that improve equipment readiness, reduce downtime, and optimise operational efficiency

The system monitors cementing equipment in real-time, prepares for upcoming jobs, and provides direct insight into equipment operation and performance.

The platform uses real-time data and AI-driven models to provide actionable insights into equipment readiness that help increase reliability, efficiency, and barrier execution consistency. The system connects critical cement unit components to intelligent controllers and monitors more than 400 real-time parameters to ensure optimal performance. Data flows into a secure cloud, where machine learning models immediately process and analyse it to deliver constant insight into equipment health, operational readiness, operator performance, and preventive maintenance recommendations.

In high-demand cementing environments, equipment reliability is essential. Traditional maintenance methods, such as manual inspections and scheduled tests, often miss early signs of wear. This approach can lead to failures between inspections, unplanned downtime, and fails to provide real-time insights into equipment health.

LOGIX unit vitality combines the power of AI with human expertise to operate smarter, respond faster, and execute with confidence. This system supports Halliburton's land-based Elite and the new Elite Prime cement units. Offshore equipment deployment will begin in 2026.

“LOGIX unit vitality delivers unprecedented visibility into equipment health and operator performance. Artificial intelligence (AI) and real-time data transform equipment maintenance from reactive to predictive to help customers gain greater insight into their operations and reduce non-productive time,” said Daniel Casale, vice president, Cementing, Halliburton.

The LOGIX automation and remote operations family of solutions includes analytics and visualisation services that deliver reliability, consistency, and efficiency. This enables smarter decisions, improved performance, safer operations, and lower total cost of ownership. LOGIX™ automation and remote operations helps provide the insights and solutions that operators need to maximize their asset value. With real-time adaptability from machine learning algorithms and dynamic adjustment of drilling parameters, LOGIX™ automation and remote operations helps ensure optimal operations even in difficult geological formations.

Tela leverages agentic AI to automate processes, transform workflows and drive better business outcomes. (Image source: SLB)

SLB has launched Tela, an agentic AI assistant for the upstream energy sector

Tela leverages agentic AI to not only automate processes but transform workflows and drive better business outcomes. Tela will be embedded in SLB’s portfolio of applications and platforms, and users will interact through a simple conversational interface, enabling agentic AI to act as a proactive collaborator.

Tela, which is deployable on cloud or on premises, follows a common five-step agentic AI loop: observe, plan, generate, act and learn. This allows agents within Tela to proactively interact with their environment, adapt to new data, and continuously improve outcomes. Whether interpreting well logs, predicting drilling issues, or optimising equipment performance, Tela agents can work in collaboration with humans or autonomously to deliver faster, smarter decisions.

Powered by SLB’s Lumi data and AI platform, Tela uses agentic AI – leveraging large language models (LLMs) and domain foundation models (DFMs) – to understand domain-specific contexts, generate insights and adapt workflows in real time based on observed outcomes. Lumi’s agentic framework allows customers to build and manage their own Tela agents, integrate partner-developed solutions, and tailor capabilities to their operational priorities.

“Technology like Tela marks a paradigm shift in how AI supports the energy industry, from subsurface to operations,” said Rakesh Jaggi, president, Digital and Integration, SLB. “Today, the industry faces a dual challenge: a leaner workforce and increased technical complexity, and Tela can address both. Tela doesn’t just automate tasks – it can understand goals, make decisions and take action. It’s the convergence of 100 years of domain science and cutting-edge digital technology, amplifying human ingenuity and redefining how work gets done.

“The real promise of agentic AI isn’t just faster workflows – it’s the ability to see the whole system, anticipate what’s next, and act with confidence, learning through the process and transforming workflows for better enterprise-level outcomes. For oil and gas, that means leading the way in energy innovation, driving smarter decisions, and actively shaping the future of the industry.”

Digital has been SLB’s fastest-growing business in recent years, with 2025 third-quarter revenues for this division rising 11% over the second quarter and 3% year-on-year.

“By leveraging software, AI, data analytics, automation and IoT, we are unlocking productivity for geoscientists and engineers, driving a step change in efficiency and safety in operations, and supporting our customers to deliver better wells and higher-producing assets,” said Olivier Le Peuch, SLB’s CEO, announcing the third quarter results. “As such, SLB Digital solutions are increasingly mission critical for our customers to stay ahead on innovation, efficiency and AI deployment.

“This high-margin and growing business is a true differentiator and reflects our industry leadership in this domain.”

Coinciding with the launch of Tela, ADNOC and SLB announced the launch of an artificial intelligence (AI)-powered Production System Optimization (AiPSO) platform with initial deployment across eight fields.

See also: https://oilreviewmiddleeast.com/technical-focus/slb-and-aiq-to-deploy-agentic-ai-across-adnocs-subsurface-operations

Autonomous operations are increasingly seen as a strategic enabler across industries.

Middle East energy leaders are reflecting strong ambitions toward autonomous operations if energy tech company, Schneider Electric's new report is to be believed

The company's survey has found that nearly 80% of energy executives from the region display advanced operational readiness. According to Schneider Electric’s Autonomous Maturity research many organisations are claiming to operate at Level 4 of the ARC Autonomous Operations Maturity Model. This implies selective autonomy, systems functioning independently in specific scenarios with limited human intervention -- a sharp contrast when compared to the global energy sector.

This major shift towards autonomy adoption is largely being driven by cost efficiency. Safety and leadership prioritisation ranked lowest, indicating a shift toward business-led innovation rather than compliance-driven transformation.

“Autonomous operations are increasingly seen as a strategic enabler across industries, driving gains in efficiency, scalability, and resilience,” said Devan Pillay, President Heavy Industries at Schneider Electric. “In the energy sector, where safety, reliability, and sustainability are critical, autonomous systems can monitor and respond in real time, reduce manual intervention in hazardous environments, and support smarter, data-driven decision-making. Crucially, they also support both onshore and remote operations, reducing offsite travel and improving work-life balance.”

Independent Energy Market Analyst, Gaurav Sharma, who provided insights to the research, said, “As global energy systems evolve, autonomy is key to optimizing resources, minimizing downtime, and advancing environmental goals. Schneider Electric's research reinforces that organizations and regions embracing higher autonomy levels are better positioned to innovate, cut costs, and stay competitive. Crucially, the report signals a strategic shift: autonomous solutions that boost efficiency and reduce emissions are now a priority for one of the world's most prominent energy hubs.”

“The convergence of electrification, automation, and digitalisation is accelerating the shift toward autonomous operations across the Middle East and Africa,” said Walid Sheta, Middle East & Africa President at Schneider Electric. “With electricity demand projected to rise by 50% and cooling alone driving over 500 TWh by 2035, according to the IEA, autonomous technologies are no longer optional - they’re essential. From AI-powered data centers to digital twins and self-healing grids, these intelligent systems are enabling safer, more resilient, and cost-efficient operations across the region’s energy infrastructure.”

The report highlights the accelerated pace of the AI transformation. (Image source: Adobe Stock)

The AI transformation is well and truly underway, with interest and pilots shifting to actual deployments, according to the second edition of the Powering Possible report released by ADNOC and Microsoft

More than 850 global experts across energy, technology, AI, academia and finance – including leaders from OpenAI, TotalEnergies and the International Energy Agency – contributed to the report, which highlights the opportunities and challenges of AI adoption in the energy sector.

With 88% of companies surveyed agreeing that scaling AI is essential to achieving energy transformation, the 2025 report data shows that the energy sector is both powering AI and being transformed by it. AI is expected to have its greatest impact on energy distribution and emerging energy solutions, with applications ranging from predictive maintenance and smart grid management to real-time demand forecasting and energy optimisation. AI is helping to optimise grids, reduce energy usage and emissions, and unlock new efficiencies across the energy value chain.

Nearly nine in ten companies surveyed have increased investment in AI and digital infrastructure since 2024, with 73% of companies deploying AI across multiple business functions. One in five are already using agentic AI to automate complex decision-making. At the same time there is a widespread view that investments in grid modernization (55%) are key to keeping up with AI’s growing demands, followed by energy storage (38%) and advanced materials like high-efficiency conductors (33%).

However, realising AI’s full potential is not without challenges. Cybersecurity has overtaken cost as the top consideration for adoption (49%), followed closely by data quality and consistency (45%) and a shortage of skilled talent (39%). These challenges are compounded by the sector’s slower innovation cycles and the complexity of integrating AI into legacy systems.

As AI adoption continues to scale, access to reliable and sustainable energy is becoming a strategic priority. The challenge, and opportunity, is to align AI for energy and energy for AI so that each accelerates the other, delivering a more sustainable, secure, and inclusive energy future.

His Excellency Dr. Sultan Ahmed Al Jaber, Minister of Industry and Advanced Technology, and ADNOC managing director and Group CEO said: “AI is no longer a future promise for the energy sector; it’s delivering real impact today from predictive maintenance to AI-optimised grids. At ADNOC, we’re embedding AI as a core capability across our operations, driving transformation at scale with measurable gains in reliability, efficiency, and sustainability. This report reflects the sector’s progress and provides a roadmap for what comes next — investing in talent, scaling proven solutions, and aligning policy with innovation. The next step is clear: move faster, together.”

Brad Smith, vice chair and president, Microsoft said, “Meeting the demands of both the AI era and energy transition will require more than ambition — it will take strong partnerships and innovation. That’s why Microsoft is working closely with energy leaders to reimagine power systems, develop talent, and build responsible AI practices.”

The report is available for download here.