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A comparison of DUG Elastic MP-FWI Imaging with traditional workflows. (Image source: DUG)

DUG shows how you can leap entire workflows in a single bound with DUG Elastic MP-FWI Imaging

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.

Workflow 1

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.

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DUG Elastic MP-FWI Imaging leaps entire workflows in a single bound, delivering unsurpassed imaging and high-resolution rock properties from field-data input. Superior outputs, in a flash!

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Key energy industry use cases enabled by IoT Nano include pipeline monitoring. (Image source: Adobe Stock)

Viasat a global leader in satellite communications, has launched its next generation IoT Nano connectivity service to deliver powerful, two-way messaging connectivity even in the most remote and challenging environments

IoT Nano is designed to meet growing global demand for cost-effective, low-data, low-power, Internet of Things (IoT) services across remote and challenging environments where mobile connectivity is often required. It enables organisations to effectively monitor and control fixed and mobile assets with ultra-reliable satellite coverage, especially in geographically dispersed, isolated, or hard-to-reach areas where terrestrial networks are limited or non-existent, through Viasat’s global L-band network.

Powered by ORBCOMM’s next-generation satellite IoT service, OGx, IoT Nano offers faster message delivery speeds, larger message sizes, and new hardware options, unlocking near real-time visibility and situational awareness and richer, more actionable data for energy operations even in remote locations.

Use cases

Key energy industry use cases enabled by IoT Nano include:

Asset tracking: Monitoring the location and movement of valuable equipment and vehicles across vast operational areas (e.g., pipelines, machinery, fleets).
Pipeline monitoring: Detecting anomalies, leaks, and ensuring the integrity of critical oil, gas, and water pipelines.
Security: Enhancing surveillance and access control for remote utility and oil & gas sites, including wellheads, substations, and pumping stations.
Tank level monitoring: Managing levels in storage tanks for oil, gas, and water, optimising supply chain and preventing overflows.
Telemetry: Collecting and transmitting vital operational data from remote sensors and devices for real-time insights and predictive maintenance.
Remote site monitoring: Gaining visibility into the status of pumps, generators, and other critical infrastructure in isolated locations.


Andy Kessler, vice president, Enterprise and Land Mobile, Viasat, said, "The IoT Nano service represents a significant advancement in providing flexible, scalable, and energy-efficient IoT connectivity to businesses operating in the most remote corners of the world. By leveraging the enhanced capabilities of the ORBCOMM OGx service and equipping our partner ecosystem with new low-cost modules and service capabilities, we are empowering customers with access to smarter data, more frequently, in more places, at a lower cost."

“OGx delivers faster speeds, larger messages, and lower power usage, all backed by ORBCOMM’s proven terminals, network, and field support,” said Dave Roscoe, president of Satellite IoT at ORBCOMM. “By lowering the cost and increasing the effectiveness of satellite connectivity, OGx makes it possible for our partners to enter new markets, expand use cases, and drive incremental growth.”

The BRUTE Armor packer. (Image source: Expro)

Expro has launched the BRUTE Armor Packer, a high-pressure, high tensile packer system, designed for the extreme conditions of deepwater wells and the highest differential pressures

The new technology gives operators the flexibility to set higher in the wellbore – saving rig time, reducing operational risk, and simplifying regulatory compliance.

According to the company, when deployed with the BRUTE 2 Storm Valve, it forms the industry’s highest-rated storm/service packer and valve combination currently available.

Following the release and successful deployment of the 12,850 psid-rated 12.15” BRUTE Armor Packer System under extreme downhole conditions, Expro has also introduced a new 20”/22” Packer System addressing the challenges of 20” and 22” retrievable mechanical packer systems, often constrained by internal diameter (ID) limitations, such as subsea high-pressure wellhead housings and supplemental casing adapters. Offering twice the element expansion capability of traditional mechanical packers, the new system delivers efficient, reliable performance for casing testing, suspension, and squeeze applications, all without compromising operational effectiveness.

The first deployment of the 20”/22” Packer System took place in June 2025, during an offshore campaign for a super-major operator in the Gulf of America. The packer passed through restrictions in the high-pressure wellhead housing and supplemental casing adapter before being installed in a larger ID below both components. It achieved full element expansion and pressure integrity on the first attempt, validating the tool’s enhanced expansion capability, enabling efficient casing isolation while reducing rig time and operational risk.

Jeremy Angelle, vice president of Well Construction commented, “This launch firmly establishes Expro’s BRUTE Packers as the industry benchmark for deepwater storm and test packers in terms of pressure and tensile strength. The modular toolset provides unparalleled flexibility, making it the most adaptable solution on the market and positions Expro as the partner of choice for next-generation 20k deepwater developments.”

The collaboration will enable TotalEnergies to extract more value from its data. (Image source: Adobe Stock)

TotalEnergies and Emerson’s Aspen Technology business are collaborating to deploy Emerson’s AspenTech Inmation across TotalEnergies’ industrial sites worldwide for the continuous, real-time collection of data

The data will be centralised and accessible securely across the organisation. It will be used to enhance decision-making, specifically through the use of artificial intelligence (AI), and to optimise operational efficiency, energy use and environmental performance at TotalEnergies sites worldwide.

The digital infrastructure, which also includes Emerson’s advanced process control solutions, will subsequently allow TotalEnergies to deploy AI use cases to improve industrial performance.

This rollout is planned over a two-year period and will ultimately enable TotalEnergies to extract more value from its data by accelerating the detection of anomalies and performance degradation; optimising energy consumption; enhancing operational safety; and speeding up the integration of AI into industrial processes.

“At TotalEnergies, digital technology is a key enabler of our transformation toward a more sustainable and efficient energy future. Our collaboration with Emerson demonstrates how advanced technologies such as Inmation help us optimise operations, reduce emissions, and generate long-term value. This collaboration is a sign of our intention to turn data and digital tech into the hallmarks of our facilities’ industrial excellence,” said Namita Shah, president of OneTech at TotalEnergies.

“Emerson’s Aspen Technology business has worked with TotalEnergies for almost 30 years, and we’re excited to continue our collaboration by supporting their operational and sustainability objectives with our digital technologies. The powerful combination of AI and our industrial data fabric solution will serve to accelerate TotalEnergies’ mission,” said Vincent Servello, president of Emerson’s Aspen Technology business.

Mohamed Zouari, general manager for the Middle East, Africa, and Turkey at Snowflake.

Mohamed Zouari, general manager for the Middle East, Africa, and Turkey at global AI and data cloud company Snowflake, argues that the future of oil and gas hinges on integrating AI and data throughout the value chain

Energy, the driver of the global economy, is undergoing one of the largest shifts of our time, propelled by hundreds of trillions of dollars in global investment over the next 25 years. The Middle East, home to the world's lowest-cost producers and the largest reserves, is positioned at the heart of this transformation. According to OPEC, the region is forecast to provide nearly 60% of global oil exports by 2050.

Against this backdrop, Middle Eastern nations are embedding digital transformation in their national strategies. The UAE’s forward-thinking initiatives, like Masdar City, alongside Saudi Arabia’s giga projects under Vision 2030, illustrate the regional ambition to lead in innovation. With oil exports comprising about 30% of the UAE’s GDP alone, the stakes are high. Data and AI are emerging as vital tools in this evolution, enabling companies to modernise infrastructure, generate real-time insights, and align operational decisions with long-term business objectives. As energy companies navigate this landscape, data and AI are becoming critical enablers for growth, operational excellence, long-term resilience and informed strategy across the oil and gas value chain.

Navigating the digital age

While the opportunity is immense, oil and gas companies face several critical challenges on the path to transformation.

One major obstacle is the need to digitise ageing infrastructure. Decades-old grids and oil wells must now integrate with millions of IoT-enabled assets like wind turbines and solar panels, creating an influx of zettabytes of operational and information technology data that requires efficient ingestion, cleaning, and analysis to drive smarter, faster decision-making.

Extreme weather, geopolitical dynamics, and the variability of renewable energy sources are contributing to more volatile commodity markets. Stable long-term contracts signed with countries like China, Japan, and India offer some security, but sophisticated data analytics are crucial to managing financial exposure and mitigating risks. Enhanced by AI and ML, predictive models can now draw on both internal and external data sources to forecast price fluctuations and demand trends more accurately, helping companies navigate volatile markets with greater confidence.

Corporations now demand rigorous environmental, social, and governance (ESG) reporting, while consumers seek intuitive, tech-driven home energy systems. Energy service providers – from utilities to oil and gas firms – must be agile, transparent, and responsive or risk falling behind.

Compounding these challenges is the overwhelming volume of unstructured data, which now represents 90% of all data according to Snowflake’s Data Trends Report. Without a centralised, secure, and scalable data infrastructure, energy companies will struggle to extract actionable insights.

AI and data strategies in practice

Modern AI and data strategies are offering new pathways to navigate this complex environment. Organisations are moving beyond traditional data management toward platforms that can unify siloed information, enable seamless collaboration across ecosystems, and deliver near real-time insights at scale.

At the core of this transformation is the ability to bring together operational, financial, and customer data into a unified environment. By doing so, oil and gas companies gain a single source of truth that supports more informed decision-making across their entire value chain – from field operations to trading desks to customer-facing platforms.

AI is also fundamentally reshaping how companies approach forecasting, maintenance, and customer engagement. Machine learning models are increasingly used to detect anomalies in equipment performance, allowing for predictive maintenance that minimises costly downtime. In trading operations, AI-driven models help forecast commodity prices with greater accuracy, enabling companies to optimise their portfolios and manage risk proactively.

For personalised customer engagement, companies can leverage real-time customer data and generative AI capabilities to deliver tailored recommendations and intuitive energy management solutions, improving satisfaction and loyalty in a highly competitive market.

Organisations that focus on building robust data foundations are better positioned to drive tangible outcomes, from optimising asset utilisation to accelerating sustainability initiatives. Snowflake’s research shows that 92% of early adopters have already realised a return on their AI investments, and 98% plan to increase AI spending in 2025.

With AI’s contribution to regional economies forecast to grow between 20% and 34%, AI is becoming a blueprint for the next generation of energy operations. The ability to seamlessly integrate and analyse vast, diverse data sets in real time is becoming a decisive competitive advantage.

The next chapter

By embracing AI and modern data strategies, oil and gas companies can digitise operations, manage volatility, anticipate customer needs, and chart a course for long-term resilience and growth – a necessary shift as fragmented data infrastructures and talent shortages remain real hurdles.

In a world increasingly defined by energy transition, those who invest early in scalable data and AI capabilities will not just survive – they will lead. The region’s commitment to digital innovation positions it well to remain a global energy powerhouse well into the future.

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