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Middle East assets face the threat of corrosion. (Image source: Adobe Stock)

CorrosionRADAR has launched its CR:SR sensor solution, a new short-range sensor technology that expands its corrosion under insulation (CUI) intelligence portfolio and helps to transform CUI management from a reactive inspection activity into a proactive intelligence-led approach

The corrosion threat

Corrosion is an ever-present threat to asset integrity in the oil and gas industry, with industry studies estimating the global cost of corrosion exceeds $2.5 trillion annually. In the Middle East, the prevalence of sour gas, the increasing use of corrosive chemicals to enhance production and the push into high pressure, high temperature environments means that the corrosion threat is only intensifying in the region.
CUI, which is a particularly insidious form of corrosion as it is difficult to detect at an early stage, occurs due to moisture build up on the external surface of insulated equipment and structures, and is prevalent in the onshore and offshore oil and gas industries.

The benefits of predictive corrosion monitoring

Predictive corrosion monitoring solutions facilitated by advances in AI and digital technologies can help operators proactively manage their corrosion challenges and protect their assets, allowing them to monitor and predict risk remotely and make data-driven decisions, saving time and money, while enhancing safety and ensuring the longevity of critical infrastructure.

CorrosionRADAR is using this approach to transform CUI management with continuous monitoring and intelligence-based analytics that save time, improve uptime and reduce the risk of catastrophic failures.
Aramco for example is using CorrosionRADAR's CUI monitoring solution at its Ju'aymah NFL fractionation plant to monitor its assets and provide insights into the early and predictive detection of CUI, enabling plant engineers to address CUI issues more rapidly, improving safety and reliability, optimising inspection planning, and reducing the overall costs associated with future maintenance and shutdowns.

Remote sensor-enabled CUI monitoring programs help operators focus resources on the locations that matter most while reducing unnecessary inspection costs and operational disruption.

The new shortwave CR:SR sensor solution has been developed for targeted, localised monitoring without the need to remove insulation. It complements CorrosionRADAR’s existing CR:LR solution, which delivers permanently installed, long-range monitoring across vessels, columns, tanks, and other complex assets.

The sensor passes monitoring data to the AI-informed CR:CLARITY software for consolidation, analysis and reporting.

Together, the CR:LR and CR:SR sensors address the challenges of traditional inspection programmes by providing continuous visibility between inspection campaigns. CUI data is constantly collected and analysed by the CR:CLARITY software, enabling operators to prioritise inspection activity based on changing risk conditions rather than fixed inspection intervals.

Dr. Chiraz Ennaceur, chief executive officer at CorrosionRADAR, said, "At CorrosionRADAR, we recognise that every asset presents a different CUI challenge. Some assets require broad coverage across large areas, while others benefit from targeted monitoring of specific high-risk locations. By expanding our portfolio to include the CR:SR sensor solution and bringing all monitoring data together through CR:CLARITY, operators gain greater flexibility in how they monitor CUI while maintaining a single view of risk across their assets."

By combining multiple monitoring strategies through a single source of CUI intelligence, CorrosionRADAR aims to help operators move towards predictive, prescriptive, and ultimately more autonomous asset integrity management.

Under the contact, Halliburton will deploy intelligent automation solutions for fracturing to optimise performance in real time and support disciplined implementation across multi-well campaigns.

In line with its ambitions to grow gas production by more than 60% by 2030 compared to 2021 levels, Aramco has awarded Halliburton a multi-year contract to deliver integrated stimulation and completion services for unconventional gas development in the Kingdom of Saudi Arabia

This award is part of a broader multi-billion contract, supporting one of the largest unconventional gas development programs globally, at the heart of which is the Jafurah unconventional gas development. The Jafurah field contains 229 trillion scf of gas-in-place and 75 BSTB of condensate-in-place. Production started in December 2025, with an ambition to ramp-up and deliver two billion scfd of sales gas by 2030, along with 420 million scfd of ethane, and around 630,000 barrels per day of gas liquids and condensates.

This award builds on Halliburton’s established portfolio supporting Aramco’s unconventional program. The company delivers a comprehensive suite of drilling and completion solutions across many of the Kingdom’s unconventional plays. This collaboration supports broader regional efforts toward integrated unconventional development programmes.

Operators in unconventional reservoirs and high-pressure environments require precision and speed to lower costs per well and improve production consistency. Halliburton’s hydraulic fracturing services combine reliable surface operations with scalable subsurface solutions that help reduce nonproductive time and support predictable execution.

Under the contact, Halliburton will deploy intelligent automation solutions for fracturing to optimise performance in real time and support disciplined implementation across multi-well campaigns supporting digital integration across operations while advancing efficiency and operational reliability.

OCTIV services are at the core of Halliburton’s intelligent fracturing ecosystem. OCTIV digital fracturing services enable frac automation, digital operations, and remote connectivity across all aspects of Halliburton’s hydraulic fracturing business. The services enable intelligent automation to maximise the performance and efficiency of equipment and operations. OCTIV automates digital workflows, information, and equipment across all aspects of fracture operations, for enhanced safety and efficiency.

While the Sensori fracture monitoring service is an easy to deploy, cost-effective fracture monitoring solution for continuous measurement and visualisation of the subsurface. It combines non-intrusive technologies, advanced data acquisition and processing, and real-time answers into a single, cost-effective solution that empowers operators with unparalleled visibility and control over fracture performance.

"This award highlights our long-standing collaboration with Aramco and builds on more than 80 years in the Kingdom, while advancing unconventional gas development in the Kingdom. Beginning in the third quarter of 2026, Halliburton will deploy the Kingdom’s first fully integrated intelligent fracturing platform through OCTIV Auto Frac and Sensori fracturing monitoring services to contribute to asset value for one of the world’s largest unconventional fields,” said Rami Yassine, president, Eastern Hemisphere, Halliburton.

To support development activities in the Jafurah Basin, Halliburton plans to increase its investment in local manufacturing, improve its supply chain, and expand workforce development programs within the Kingdom, in line with Vision 2030 objectives, aiming to scale operations and sustain high performance as unconventional activity accelerates.

The platform will show how Geoteric’s solutions for AI-based interpretation of seismic data can be connected with simulators from SINTEF. (Image source: Geoteric)

Geoteric and SINTEF have entered into a collaboration to develop a new AI agent platform based on open standards, which will make it possible to connect seismic interpretation directly with reservoir simulation

The platform will show how Geoteric’s solutions for AI-based interpretation of seismic data can be connected with simulators from SINTEF, enabling users to move more quickly from geological interpretation to dynamic reservoir simulation in a single shared workflow. The collaboration combines the expertise of Geoteric in AI-based interpretation of seismic subsurface data, withSINTEF’s experience in reservoir simulation, mathematical models and research-based software for complex physical systems.

The solution represents an important step towards a new generation of integrated workflows, in which AI agents collaborate across disciplines to combine interpretation, modelling, simulation and decision support. The aim is to give geophysicists, geologists and reservoir engineers faster insight, facilitating decision-making and management of uncertainty throughout the workflow.

By automating the interaction between specialised agents, users can obtain more verifiable interpretations and clearer quantification of uncertainty. This makes it easier to assess alternative geological models, compare different scenarios and identify the solutions that provide the strongest basis for decision-making.

“I am convinced that open AI agent platforms will change the way geoscientists work. Based on my experience building the company that delivered Petrel to the oil and gas industry, I see this as an important next step for the industry - where specialised applications can collaborate seamlessly to provide better subsurface insight,” said Jan Grimnes, chair of Geoteric.

“The opportunities lie not only in automating individual tasks, but in enabling specialised tools to work together to test alternatives, reveal uncertainty and give decision-makers a stronger foundation. This is what we want to demonstrate together with SINTEF.”

“This collaboration is an exciting opportunity to operationalise the research we are doing in SINTEF Agent Lab on the use of AI agents as part of expert systems,” added Knut-Andreas Lie, chief scientist at SINTEF.

“For several decades, SINTEF has developed simulation methods and research-based software for reservoirs, CO₂ storage and other geoenergy systems. Much of this work is based on open-source code and has been adopted in collaboration with major international energy companies. In this project, we can combine that experience with new agent technology and show how open tools can be integrated into more automated and verifiable workflows.”

The results of the collaboration will be presented for the first time at the international geoscience conference, IMAGE in Houston in August.

The upstream sector is at the forefront of IIOT adoption. (Image source: Adobe Stock)

The adoption of Industrial Internet of Things (IIOT) is accelerating throughout the value chain in the oil and gas sector, says intelligence platform GlobalData

GlobalData’s Strategic Intelligence report, “Industrial Internet in Oil & Gas,” reveals that artificial intelligence (AI) and digital twins will revolutionise the Industrial Internet in oil and gas, powering smarter connected assets across exploration, drilling, and production. This technology shift enables autonomous operations, predictive maintenance, enhanced efficiency, and the agility crucial for navigating volatile markets.

The upstream segment is at the forefront of Industrial Internet adoption, according to the report. Projects are increasingly capital intensive and geographically remote, facing new subsurface challenges and rising environmental, social, and governance (ESG) scrutiny. As a result, real-time monitoring and modelling can make a big difference to outcomes. Digital twins, AI-driven drilling optimization, and field-wide

IoT networks enable operators to simulate outcomes, remotely manage wells, predict equipment failures, and integrate new production more rapidly.

In the midstream segment, sensors on pipelines and tanks provide real-time data on pressure, flow, and integrity, enabling faster leak detection and improved responses to anomalies.

In the downsteam operations, real-time data collection and advanced process automation now underpin production optimisation, emissions control, and energy management. Digital twins are enabling continuous process modelling, rapid scenario testing, and proactive troubleshooting.

Ravindra Puranik, Oil and Gas Analyst at GlobalData, commented, “The oil and gas industry in 2026 faces unprecedented external pressures: high and volatile prices, supply uncertainty, climate change concerns, rising consumption of cleaner energy, and realigning global energy trade routes. Besides these, companies are facing significant operational challenges driven by factors such as US tariffs, the Iran conflict, sanctions, and protectionist policies. To secure future growth and resilience, operators are embracing the Industrial Internet across their businesses.

Puranik added, “Autonomous operations are rapidly becoming standard in digitally advanced oilfields, particularly in offshore environments such as fixed platforms and FPSOs, where remote and reliable management is both a logistical necessity and a cost imperative. Also, cloud-based analytics and AI systems connect the dots from raw input to final distribution, improving the accuracy of demand forecasting and inventory management even in volatile markets.”

According to Globaldata, the global Industrial Internet market is expanding rapidly, and is forecast to grow at a compound annual growth rate (CAGR) of 16% from 2024 to 2029, to reach US$552.7bn in revenue by 2029, of which the energy sector is expected to generate US$79bn.

The collaboration aims to address the disconnect between how factory operations are designed and how they run in reality. (Image source: IFS)

Siemens and IFS have entered into a partnership involving the creation of a closed-loop Digital Twin to help manufacturers connect design, production and asset performance in a continuous loop, from engineering intelligence to operational outcome, optimising their production assets across the entire product lifecycle with industrial AI

The collaboration combines Siemens' leadership in industrial AI, engineering, automation and manufacturing execution and IFS's strengths in industrial AI, enterprise asset management and field service domains. With manufacturers under pressure to make the most of their existing assets, the two companies aim to help them address the disconnect between how factory operations are designed and how they run in reality, where unplanned downtime, disconnected maintenance schedules, siloed production data and supply chain disruption continue to erode throughput, agility, and margin.

Industrial AI at the core

With Industrial AI at the heart of the collaboration, Siemens and IFS are looking to enhance industrial performance by bringing the physical and digital worlds together to help manufacturers translate design intent into operational reality and connect that operational reality back into better design to accelerate innovation.

Siemens’ comprehensive Digital Twin brings the engineering, simulation and manufacturing context while IFS brings the service history, asset behavior and operational lifecycle data that show how those products and assets perform in the real world. Together, they plan to create a closed loop Digital Twin grounded in both design intent and field performance that is secure, governed and auditable across design, simulation, service records, factory execution and can be trusted to deploy at industrial scale.

Industrial environments demand accuracy, reliability, regulatory compliance and adaptability to drive optimisation and agility, as even small error rates are unacceptable when decisions affect safety, compliance and costly physical assets. The partners’ shared approach to industrial AI is built for this reality.

"Industrial AI only delivers value when it is grounded in both engineering intent and real-world performance," said Tony Hemmelgarn, president and chief executive officer, Siemens Digital Industries Software. "Together with IFS, we are bringing these domains together by connecting design, manufacturing and asset lifecycle data in a secure, contextualised data fabric. By converging our combined strengths in industrial AI, together we will empower our customers with our vision of an executable Digital Twin that will enable them to accelerate innovation with confidence.”

"Manufacturers need their factory floor to behave the way it was designed. This partnership with Siemens brings together two companies that each own a critical piece of the puzzle. Agentic AI is the critical frontier, and industrial leaders need solutions with closed loop models and data, and a rich set of context that will not hallucinate in active operations,” said Mark Moffat, chief executive officer, IFS. “By combining our collective strengths in Industrial AI, we can help manufacturers close the loop between design and reality, and unlock real, measurable performance gains."

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