Halliburton has launched the next-generationTuring electro-hydraulic control system, with bidirectional choking and built-in position sensors for fast and accurate flow control

Part of Halliburton’s of SmartWell intelligent completions technology, this system sets a new standard in reservoir flow control suitable for all completion applications, improving recovery and reducing well count.

The Turing electro-hydraulic control system facilitates fast zonal optimisation through integrated position sensors that help operators manage well performance with speed, precision, and confidence. Its simplified, flexible design reduces rig time, operational risk, and production delays to deliver measurable value to our customers.

Operators can remotely and selectively adjust zonal ICV positions in seconds. Built-in high-resolution sensors increase fidelity and expand choke position options. Fast, precise bidirectional control of the ICVs enables flow control from or into each zone without closing the ICV. This capability supports routine, active well optimisation and supports the adoption of fully automated, data-driven optimization technology.

Paired with the Clariti® digital reservoir management suite, the Turing electro-hydraulic control system provides customers with added insights and real-time advice on opportunities for well production and field optimisation. The system can manage up to 12 zones with three control lines, two hydraulic and one single-wire tubing-encapsulated conductor (TEC). The TEC line communicates with downhole sensors through the DataSphere permanent monitoring suite to eliminate additional lines and reduce subsea infrastructure costs.

“As the pioneer of SmartWell intelligent completions, Halliburton’s advancements in this technology strengthen our industry leadership. Our new Turing electro-hydraulic control system builds on that legacy. It empowers our customers to improve recovery, manage subsurface uncertainty, and achieve lower costs with greater operational efficiency,” said Maxime Coffin, vice president, Halliburton Completion Tools

Hannes Liebe, regional president, APJMEA at IFS, discusses Middle East business prospects and the evolution of industrial AI in advance of IFS Connect Middle East & Africa 2025, the company’s flagship customer and partner event

IFS, a global leader in industrial AI, sees strong prospects for growing its business in the Middle East, as Liebe explains.

“The Middle East right now is at a crossroads, following years of growth. Through AI, I believe we’re entering into a new era – the next industrial revolution. In the context of oil and gas, while the long term forecast for oil is generally downwards, at the same time natural gas and LNG are growing, along with new energies such as renewables and hydrogen.

“So the Middle East, with its appetite and ambition to lead the world in this new industrial era, plus the backdrop of what we see in oil and gas, makes this a very interesting opportunity for a solution provider like IFS, with our domain expertise and a similar level of ambition to lead our customers and industry into the future.”

He notes IFS’s focus on six asset-heavy industrial sectors – energy, utilities and resources; manufacturing; construction and engineering; aerospace and defence; services industries and telecommunications – and has always focused on execution.

“In asset-heavy industries, the software has to do the job. It’s not technology for technology’s sake. That is particularly the case in oil and gas, given the price constraints. It’s about uptime. It’s about the lifespan and serviceability of the assets. So it is a very important topic, and we have market-leading solutions to help customers optimise across their asset lifecycle.”

“It’s similar for the growing gas and LNG sector. Where do you invest the capital? How do you do the capital planning around this? How do you do maintenance for these assets? Predictive maintenance will become the rule, so you need a software platform that does this.”

Turning to the third area of new energies and hydrogen, he stresses that sustainability needs to be looked at from a business rather than a CSR perspective; there has to be a tangible ROI.

“If I invest in these emerging areas, how will they deliver the ROI that I need?

“All this is software related. It’s a big opportunity for IFS, and that’s why we are investing heavily in the Middle East.”

Approach to industrial AI

Discussing the company’s approach to industrial AI, he says “Industrial AI means contextual AI. This is all about AI in business context. We start from the business problem and the business process, and then look at the technological remit to resolve it. AI provides new capabilities that we didn’t have before. It is not about technological gimmicks, but to support the execution, to get the job done. In that way, it’s not about technology, it’s about business process.” It is this approach that has primed companies such as IFS to be very successful in this space where others have fallen, with a recent MIT study finding that 95% of generative AI pilots at companies are failing.

Discussing the challenges to AI adoption, Liebe highlights legacy systems and fragmented data, and the issue of trust. “If I were in oil and gas, I would be sceptical if it were just about the tools, the next tech. Can I really trust what that tool delivers to me? In an industrial context, if your prediction is wrong, it could have catastrophic consequences. The trust element only comes if it is executions and operations related; it cannot be just a tech tool. As with any technological innovation, the legacy will always drive us, but there’s also a mindset issue; the softer part of technological adoption will play a role. And I think we all have a journey to walk, on the supplier side as well as the customer side. We are in this together.

“What makes the difference in AI? The best way to summarise this is ‘dreams and details’. It needs ambition in the dream, and the rigorous focus on details to create the trust.”

Liebe highlights the company’s initiative with Nexus Black, whereby a world-class team of AI engineers are working with the customer to create AI-based solutions that solve real-world problems, in a scalable, reliable and trustworthy way.

A recent report from IFS highlighted that the evolution of industrial AI is creating a shift in business models, changing how businesses are run, automating maintenance, predicting disruptions, optimising supply chains, and facilitating intelligent decision-making across field service, asset management, and manufacturing. Elaborating on this, he comments, “Many companies are shifting their model to outcome-based revenue streams, meaning that predictive maintenance will become the rule. AI will fuel this, so we will see business model transformations and new revenue streams being enabled through the power of AI.”

Giving a specific example from the oil and gas sector, he highlights the company’s partnership with TotalEnergies, which will see all the energy company’s assets, from exploration and production to refineries and chemicals, moved into one platform through IFS Cloud, for streamlined asset management and servicing. When fully implemented, more than 13,500 users globally will be enabled to perform asset maintenance.

“It’s only by bringing all these assets together that you can truly optimise and make full use of AI,” he explains. “You can automate and create scale. This is an example of where IFS can truly help.”

IFS Connect Middle East & Africa

Turning to the IFS Connect event in Riyadh and how IFS will support the Saudi Vision 2030 strategy, he comments, “At its core, Saudi Vision 2030 is an example of ambition, urgency and sustainability. That is fully in line with how we think. We have that sense of urgency, but we want to show a commitment as well by building local talent, local partnerships, local presence. So we have moved our regional headquarters to Riyadh, and are partnering with local companies to strengthen our presence and enhance our capabilities. Moving our regional event for the Middle East and Africa to Riyadh is also testimony to this. The ambition in Saudi is palpable, and we want to be a part of it.”

With the theme “Powering Vision 2030: Industry-Centric Innovation for National Transformation”, IFS Connect will showcase how IFS’s industrial solutions & Industrial AI are enabling organisations in the region achieve tangible business outcomes and accelerate their contribution to national visions.

It will provide a valuable opportunity to share real stories with real customers, Liebe says, highlighting the company’s customer focus. It will also provide actionable value in the industrial context, with breakout sessions for each of its industrial verticals, where customers can share their experiences with their peers.

“Thirdly, it’s about inspiration, coming back to the dreams and details,” he concludes. “We all have to dream together, no-one has it all. And there is no better way of doing this than in an industry event context.”

High impedance contrasts a problem? Never fear. DUG Elastic MP-FWI Imaging is here!

DUG Elastic MP-FWI Imaging is a unique approach to seismic processing and imaging which turns the traditional paradigm on its head. It replaces not only traditional processing and imaging workflows, but also the subsequent inversion workflow for elastic rock properties.

The traditional processing workflow involves the testing and application of dozens of steps such as deghosting, designature, demultiple and regularisation, which are all designed to overcome the limitations of conventional imaging. These workflows are complex, subjective, and very time-consuming due to their serial nature and they rely on many assumptions and simplifications. All of these issues impact the output data quality. The resulting, primary-only data then undergoes a similarly complex model-building workflow to derive an estimate of the subsurface velocity, which is used for depth imaging. Post-migration processing is performed before the pre-stack reflectivity undergoes another workflow to derive rock properties that feed into quantitative interpretation, also relying on simplifications of the actual physics. As a result of these workflows, projects can take many months to years to complete.

Elastic MP-FWI Imaging accounts for both compressional and shear waves, handling variations in seismic wave dynamics as a function of incidence angle, including in the presence of high impedance contrasts and onshore near-surface geological complexity. Multiples and converted waves are now treated as valuable additional signal, increasing sampling, resolution and constraining the inverted parameters.

As well as three-component reflectivity and velocity, DUG Elastic MP-FWI Imaging enables the estimation of fundamental rock properties like P-impedance, density and Vp/Vs from field data, without the need for a secondary amplitude variation with angle (AVA) inversion step. DUG Elastic MP-FWI Imaging simultaneously resolves not only subsurface structural features but also quantitative rock property information while avoiding the need for extensive data pre-processing and (post-imaging!) AVA-inversion workflows.

Here we consider an OBN dataset from the Gulf of America where water depths are approximately 2 km. In the figure at the top we see a comparison of the downgoing mirror RTM using pre-processed data (top), acoustic MP-FWI imaging reflectivity (middle), and elastic MP-FWI imaging reflectivity (bottom). We can immediately see the improvements that the MP-FWI imaging approaches bring over the conventional RTM with respect to resolution and illumination. The elastic MP-FWI imaging result has obviously produced the superior image around the high-impedance contrast caused by the salt, and the structures beneath it.

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