DAS is ready for prime time

Why this matters

Today, oil and gas reservoir monitoring relies heavily on ocean bottom node (OBN) and towed streamer surveys. These approaches are proven and highly capable, but not always the most practical fit for every objective . That's where DAS becomes a potential enabler for a more cost-effective , practical monitoring.

By turning existing fibre-optic cables into dense seismic arrays, DAS has the potential to reduce time requirements and logistical complexity while lowering overall costs and environmental impact. Substantial sensing infrastructure is already in place, and we expect that more will be installed in the future.

What we're doing

This project aims to push DAS technology from proof-of-concept to a proven field-ready solution. That means making it work-not just in theory, but in real oil and gas fields, with real data at scale.

Over the coming four years, we'll:

• Benchmark DAS against OBN, using data from Aker BP's Edvard Grieg field.
• Adapt and scale up our high-end elastic Elementi Full Waveform Inversion (FWI) and Reverse Time Migration (RTM) imaging platforms for DAS.
• Quantify uncertainty present in the subsurface models and images used for monitoring, with next-gen machine learning techniques.
• Ensure scalability on GPU Infrastructure.
• Design new monitoring strategies tailored to the specific needs and advantages of surface- and well-based-DAS sensing platforms.

All of this feeds into one goal: to unlock high value subsurface insights at practical affordable costs, and with significantly less CO2 emissions from acquisition.

DAS + OBN = more options, smarter monitoring

We're not setting out to replace OBN-at least not everywhere. But by combining DAS and OBN strategically, we aim to extend monitoring capabilities in ways that weren't possible before. Think lower cost, faster repeat surveys, uncertainty-quantified subsurface information from fewer data, and smarter decision-making.

For projects with tight budgets-like many CCS and geothermal developments, DAS could be the only viable option. And for mature oil fields, it opens up the possibility of more frequent and flexible monitoring strategies.

Built for the future

From day one, this project is designed for impact. We're not just exploring new ideas-we're building tools that will plug directly into Shearwater's Reveal platform including our state-of-the-art Elementi elastic full waveform inversion (FWI) and new Machine Learning frameworks - tested on real data and ready for real-world use. And with Aker BP's field data and expertise baked in, we're making sure this works where it counts.

By 2029, we expect to validate the world's first fully integrated DAS monitoring workflow-delivering fit-for-purpose processing, imaging and uncertainty quantification, ready for oil & gas, CCS, and geothermal applications.

Driving sustainable monitoring

This is about more than new technology. It's about lowering the carbon footprint of offshore operations, reducing HSE exposure, and giving operators the tools they need to monitor subsurface storage safely and reliably.

DAS-based monitoring could reduce survey emissions by up to a third, while doubling the frequency of data collection. That's a real step forward in making offshore energy cleaner, safer, and more efficient.

A project with reach

Funded by RCN and delivered through Reflection Marine Norge-Shearwater's technology and innovation arm-together with Shearwater's Geophysics R&D department, the project is a joint initiative between Shearwater and Aker BP.

It brings together industrial rigour, applied research, and a shared focus on practical outcomes, supported by close collaboration with academia.

Let's rethink how we monitor the subsurface

We're turning legacy fibre cables into high-density seismic arrays. We're training AI to map uncertainty in 3D. And we're doing it all with scale and speed in mind.

It's time to take DAS-based monitoring from experimental to essential.

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