Category: Uncategorized

Title: Data‑Integrated Modelling and Image‑Based Analysis of Multiphase Flow in Porous Media.

Speaker: Jakub W. Both is an applied mathematician with great interest in interdisciplinary porous media research, working at the intersection of multiphysics simulations, data integrated modeling, and image based model validation. His research combines advanced numerical methods with high resolution experimental data, with key contributions to the FluidFlower universe and the development of the DarSIA toolbox for multi scale image analysis. He focuses on bridging experimental physics with mathematical modelling to enhance understanding and simulation capabilities of flow and transport in porous media. Jakub received the 2025 SIAM Activity Group on Geosciences Early Career Prize and has been awarded an RCN FRIPRO Young Researcher Talent grant for his project TIME4CO₂. He serves as deputy leader of WP 4/5 of the Centre for Sustainable Subsurface Resources (CSSR).

Date : 06 March 2026

Below are the key highlights from the webinar, including a short summary designed for our non‑technical audience.

CSSR webinar: Integrating experiments, data analysis and simulation for improved understanding of CO₂ storage.

In this webinar, Dr Jakub Wiktor Both presented recent advances in bridging the gap between laboratory experiments and computational modelling to improve our understanding of CO₂ storage processes. His work focuses on creating a robust interface between experimental observations, quantitative data extraction and physics based simulations — a key ambition for CSSR as the Centre moves into its next phase.

The role of interdisciplinary integration in CSSR

Dr Both opened by highlighting CSSR’s core objective: enabling zero emission reservoir operations through improved subsurface understanding and advanced digital methods. Achieving this requires close interaction between experimental research, data driven analysis and simulation. The work presented addresses this integration directly.

From laboratory images to quantitative data

A central theme of the webinar was DarSIA, a Python based toolbox designed to convert experimental images — such as tracer flow sand tank experiments and PET scans — into physically meaningful datasets.

Key capabilities include:

• extraction of CO₂ concentrations and saturations from colour based images
• calibration procedures that incorporate experimental metadata
• detection and removal of sand grain effects
• production of spatial concentration maps suitable for direct comparison with simulations
• support for multiple data formats (photographs, PET, VTK, MRI/DICOM)

These tools allow researchers to move beyond qualitative visual interpretation and perform reproducible, physics aware data analysis.

Analysing variability and similarity across experiments

Dr Both demonstrated how DarSIA enables:

• comparison of repeated laboratory experiments
• quantification of physical variability in multiphase flow
• grouping of experiments using hierarchical clustering
• application of advanced metrics such as the Wasserstein distance, which better capture spatial differences than simple integral measures

These methods have been successfully applied to CO₂ dissolution experiments, fracture flow studies and the SPE11 simulation benchmark.

Connecting experiments and simulations

The webinar showcased several initiatives that rely on this experimental–digital interface:

• FluidFlower benchmark studies, including double blind comparisons between experiments and independent simulation groups
• history matching efforts using DarSIA processed data
• the newly started FRIPRO project TIME4CO2, which aims to improve dispersion modelling and match experiments more reliably
• the PoroTwin digital twin project, where laboratory experiments feed into real time analysis pipelines and hybrid modelling

Commitment to FAIR research

Dr Both concluded by emphasising the importance of FAIR (Findable, Accessible, Interoperable, Reusable) principles in multidisciplinary science.

The team’s ongoing work on open data, reusable workflows and JupyterHub based analysis pipelines supports transparent and auditable research practices across CSSR and the broader porous media community.

For Everyone: What Does This Mean?

CSSR webinar: Integrating experiments, data analysis and simulation for improved understanding of CO₂ storage.

This webinar showed how researchers combine physical experiments with modern computer models to better understand how CO₂ moves and dissolves underground.

A new tool called DarSIA can turn simple images from laboratory experiments into usable scientific data. This makes it possible to compare experiments, measure differences, and check whether computer simulations behave like real physical systems.

The work helps scientists develop safer and more reliable methods for storing CO₂ underground — an important step in reducing emissions and supporting the energy transition.

Title: Digital Rock Methods for Multiphase Fluid Flows

On 30 January, CSSR hosted the first webinar of the 2026 Open Webinar Series, titled “Digital rock methods for multiphase fluid flows”, presented by Espen Jettestuen. He is a senior researcher at NORCE’s Energy and Technology division and leader of Work Package 1 in CSSR. He holds a PhD in solid-state physics from the University of Oslo.

The recording is now available for those who were unable to attend or would like to revisit the presentation.

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Webinar Summary

CSSR Open Webinar Series 2026‑1 featured a presentation by Espen Jettestuen on a digital rock workflow developed within Work Package 1 of the CSSR project. The aim of the workflow is to compute relative permeability and capillary pressure curves from high‑resolution digital rock images, with particular focus on systems subjected to fluctuating flow conditions.

The talk began with an overview of Work Package 1, which studies how time‑varying injections affect reservoir behaviour, spanning scales from pore‑scale simulations to geological characterization. The core of the webinar detailed a workflow that:

• Takes 3D digital rock geometries,
• Performs capillary displacement simulations using a level‑set method,
• Generates two‑phase fluid configurations, and
• Computes flow functions using single‑phase fluid simulation.

Jettestuen compared this approach with direct multiphase lattice‑Boltzmann simulations, noting the latter’s high computational cost and numerical stability issues. The specialized workflow, in contrast, is highly efficient, avoids numerical diffusion, and handles hysteresis more robustly.

A complete example using a high‑porosity sandstone sample illustrated the drainage/imbibition cycles, hysteresis loops, and the resulting flow functions. The team also explored boundary conditions and found that zero‑velocity boundaries performed sufficiently well.

To prepare the results for reservoir‑scale simulators, the group applies an artificial neural network to smooth and generalize the flow functions, including multiple reversal points. The outlook includes validating the method against core‑scale experiments, extending models to three‑phase systems, and improving the treatment of heterogeneity and sample‑size effects—particularly relevant for CO₂ storage, gas production, and hydrogen storage.

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For Everyone: What Does This Mean?

In this webinar, Espen presented a new digital method for understanding how fluids flow through rocks deep underground. By using detailed 3D images of real rock samples, the team can simulate how water, gas, or CO₂ move through tiny pores inside the rock. This helps them predict how reservoirs behave when conditions change, such as during CO₂ storage or energy production. The method is faster and more flexible than traditional laboratory experiments and offers new possibilities for studying complex behaviour that is otherwise difficult to observe directly.

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International recognition from SIAM

We are pleased to share excellent news from the international research community. In 2025, our colleague Jakub W. Both and long‑standing collaborator Rainer Helmig were selected as recipients of prestigious awards from the SIAM Activity Group on Geosciences. The awards recognised their outstanding scientific contributions and long‑term impact on geoscience research related to energy, environment, and subsurface processes.

🏅 Jakub W. Both – Early Career Prize (2025)

Jakub W. Both, CSSR, University of Bergen, CSSR, received the 2025 SIAM Activity Group on Geosciences Early Career Prize for his broad and innovative contributions to mathematical problems in the geosciences. His work advanced optimisation methodologies for non‑smooth and non‑convex problems, with key applications in poroelasticity, geological CO₂ storage, and geothermal energy.

In the interview published by SIAM, Both described the prize as a particularly meaningful recognition at this stage of his career and emphasised the importance of the SIAM geosciences community in shaping his scientific identity. He highlighted how his research leveraged energy‑based formulations and alternating minimisation approaches to design robust and efficient solvers for coupled multiphysics problems, enabling improved prediction and simulation of complex subsurface systems relevant to climate and energy applications.

At the time of the award, Both was and continues to be a permanent researcher at the University of Bergen, with a background spanning mathematics, computational engineering, and applied mathematics. He also served as Chair of the Norwegian Chapter of InterPore and led an interdisciplinary early‑career project on CO₂ storage.

🏅 Rainer Helmig – Career Prize (2025)

Rainer Helmig, Professor Emeritus at the University of Stuttgart and a close collaborator of our research community, was awarded the 2025 SIAM Activity Group on Geosciences Career Prize. The award recognised his groundbreaking contributions to the mathematical and numerical modelling of multiphysics surface and subsurface flow processes, as well as his influential leadership and mentorship over several decades.

In his interview, Helmig underlined the collective nature of his achievements, crediting students, postdoctoral researchers, and collaborators. His research addressed complex coupled flow, transport, deformation, and interface‑driven processes in porous media, with applications ranging from CO₂ storage and geothermal energy to groundwater protection, environmental remediation, and biomedical systems. His work played a central role in advancing interdisciplinary modelling across applied mathematics, engineering, and geosciences.

Helmig’s career included leading major international research initiatives, co‑founding InterPore, and contributing extensively to the scientific community through service, collaboration, and education.

Award presentation and source

Both awards were presented in October 2025 in connection with the SIAM Conference on Mathematical & Computational Issues in the Geosciences (GS25).

Source:
SIAM News – 2025 October Prize Spotlight
SIAM Activity Group on Geosciences

(Full interviews and award citations are published by SIAM.)

Vestland CCUS 2025 – a platform for knowledge and collaboration 

On November 27, Vestland CCUS 2025 brought together around 100 participants for a full day of knowledge sharing and networking in Bergen. The event was organized by NORCE and the University of Bergen, in collaboration with Energiomstilling Vest, the Centre for Sustainable Subsurface Resources, and with support from CLIMIT. The goal is to maintain a regional meeting place for stakeholders in carbon capture, utilization, and storage (CCUS), and to strengthen dialogue between research, industry, and public authorities. The program was diverse and engaging, featuring presentations, panel discussions, and demonstrations that highlighted technological, political, and legal aspects of CCS. 

NORCE played a key role with several presentations on CO₂ transport and storage and moderated the industry panel discussion. Representatives from Equinor, Northern Lights, Aker BP, and the Norwegian Offshore Directorate shared their perspectives on how to accelerate CO₂ storage in Norway and Europe. The discussion also addressed challenges that need to be solved, including better coordination between capture and storage projects, cost reduction through standardization and scaling, and the fact that financing remains a major bottleneck for faster progress. 

The University of Bergen contributed important insights, including a presentation on legal frameworks for cross-border CCS fields and shared aquifers. One of the day’s highlights was “From Lab to World: The Traveling FluidFlower Experience” by Martin Fernø. FluidFlower is not only a research tool but also an educational concept that makes carbon storage understandable for both children and adults. During lunch, participants experienced a live demonstration of CO₂ injection in Northern Lights geometry, illustrating how storage actually takes place beneath the seabed. This helps build public understanding and engagement around solutions that are essential for achieving climate goals. 

The second panel discussion, “What is the way forward for CCS?”, explored political and industrial perspectives on the future. The conversation emphasized that Mongstad, Norway’s largest single source of CO₂ emissions, together with planned new facilities, could provide a basis for further development of storage infrastructure. The panel also highlighted that the cost of inaction must be part of the equation and that CCS is both climate policy and industrial policy. Knowledge about CCS remains low, even among politicians, and research communities need to work more actively on outreach. Collaboration between different actors was identified as key to success, and strong interest from international delegations shows that Vestland CCUS plays an important role in putting Norway on the map.  Politicians Linda Monsen Merkesdal (Labour Party) and Tom Georg Indrevik (Conservative Party) participated in this discussion alongside representatives from industry and the waste sector. 

Participants at the conference.

Date & Time: 28th November 2025. 09:00-10:00

Title: Efficient Nonlinear Preconditioning for Reservoir Simulation History Matching Using Random Features Learning

Speaker: Antoine Lechevallier holds a French engineering degree in Geosciences with a major in Numerical Geosciences and a specialization in AI and Big Data. He completed a PhD in Applied Mathematics between Sorbonne Université and IFP Energies Nouvelles, focusing on Scientific Machine Learning for improving reservoir simulations. His postdoctoral work at NORCE continues this line of research, emphasizing the practical integration of ML into industrial workflows to robustly accelerate simulations and enhance real-world performance.

Read below the highlights from the webinar

Smarter Reservoir Simulation: Combining Physics and Machine Learning

Reservoir simulation is a critical tool in energy production, helping engineers predict how oil, gas, and water move underground. These simulations guide decisions on field development and resource management, but they are computationally demanding and often slowed down by nonlinear solver failures.

Our latest research based on Hybrid Newton, a machine learning–enhanced approach that accelerates reservoir simulations without replacing the underlying physics. This method acts as a “smart assistant” to traditional solvers, learning from previous runs and predicting better starting points for complex calculations. The result: fewer nonlinear solver failures at desired point in time, and improved efficiency in workflows such as history matching, where models are adjusted to match observed production data.

Key Innovations

• Data-Driven Preconditioning: Neural networks improve solver performance while preserving physical accuracy.
• Extreme Learning Machines: A lightweight training technique based on Random Features Learning that reduces model training time from minutes to seconds.
• Operational Integration: Now available in OPM Flow, an open-source reservoir simulator widely used in industry.

Why It Matters

• Efficiency: Reduced CPU time and fewer failures mean faster results.
• Scalability: Works seamlessly in history matching workflows requiring thousands of simulations.
• Future-Ready: Opens the door for broader applications in complex fields and other physical systems.

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For Everyone: What Does This Mean?

Imagine trying to predict how water, oil, and gas move underground—it’s like solving a giant puzzle with millions of pieces. Traditionally, computers do this by running heavy calculations, which can sometimes get stuck and waste time. Our new method adds a “smart helper” powered by machine learning. It learns from past runs and gives the computer better hints, so the process is faster and less error-prone. This means quicker results, smarter decisions, and more efficient energy production, all without changing the science behind it.

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Next Steps: This breakthrough is now integrated into OPM Flow and ready for operational testing. Future work will focus on scaling the method to complex fields and automating detection of nonlinear issues.

CSSR Celebrates Its First PhD Graduate!

We are very proud to announce a major milestone for the Centre for Sustainable Subsurface Resources (CSSR): on 10 November, Mathias Methlie Nilsen successfully defended his PhD thesis, “Optimization Methodology for Sustainable Reservoir Management,” becoming our very first PhD candidate funded by the centre.

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About the Thesis

The research focuses on developing optimization methodologies for operational strategies in reservoir management and robust approaches for integrating offshore wind as an energy source in production. A key challenge addressed is the variability and uncertainty of wind power, requiring new optimization routines for production control. The work demonstrates how to balance emissions and economic gains for a reservoir field, both with and without access to offshore wind power.

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“Mathias has proven to be an exceptionally productive and self-driven researcher. During his PhD, he contributed to several key areas within optimization and the use of renewable energy on the Norwegian continental shelf. He was a student who was easy to supervise, and collaborating with him has been highly rewarding. At the defense, there was strong support from colleagues and family, and Mathias presented his work in a clear and well-structured manner. He received excellent feedback from the opponents”, Rolf Lorentzen (WP3 leader)

About Mathias

Mathias holds a bachelor’s degree in physics and a master’s degree in theoretical nuclear and particle physics from UiB. He began his PhD in applied mathematics at NORCE Research As , supervised by Rolf J. Lorentzen (NORCE), Jakub W. Both (UiB), and Olwijn Leeuwenburgh (TNO, Netherlands). At CSSR, Mathias contributed significantly to Work Package 3.

Defense Committee

• Opponents: Anahita Abadpour (TotalEnergies), Prof. Carl Fredrik Berg (NTNU)
• Chair: Prof. Kundan Kumar | Leader: Prof. Henrik Kalisch

Caption from left: Carl Fredrik Berg (NTNU), Rolf Johan Lorentzen(NORCE), Mathias Methlie Nilsen(NORCE), Olwijn Leeuwenburgh (TNO), Jakub Wiktor Both(UiB)

📸 Photo courtesy of UiB administration

A big thank you to everyone who supported this journey! Congratulations, Mathias, and best of luck in your future career at NORCE!

Date & Time: 24th October 2025. 09:00-10:00

Title: Underground hydrogen storage in porous media: Microbial controls and multiphase flow

Speaker: Raymond Mushabe has completed the research component of his PhD on underground hydrogen storage at the University of Bergen, in collaboration with Equinor laboratories at Sandsli. He holds an MSc in Petroleum Engineering from NTNU, specializing in reservoir engineering and petrophysics, and a BSc in Petroleum Geoscience and Production from Makerere University, Uganda. He plans to defend his dissertation later this year and is currently exploring opportunities in industry or academia.

Exploring clean energy storage beneath the surface.
Hydrogen is a clean energy source that can be stored underground to help balance energy supply from renewable sources such as wind and solar. In this webinar, Raymond Mushabe presented how microbes living in saline water within reservoir rocks may influence hydrogen storage and recovery. His research combines laboratory experiments, imaging techniques, and computational models to improve underground hydrogen storage efficiency and support the development of reliable clean energy systems.

Raymond’s work spans core-scale experiments to reservoir-scale simulations, integrating MRI and PET imaging with machine learning models to predict hydrogen storage performance. His research addresses key challenges in subsurface hydrogen storage, including:
• Microbial hydrogen consumption and its impact on storage efficiency.
• Design and use of custom anaerobic setups for cyclic injection and storage experiments.
• In situ imaging to visualize pore and core-scale dynamics and microbial activity.
• Machine learning applications for fast and accurate reservoir predictions and design of laboratory experiments.

Key findings include:
• Microbial hydrogen losses are significantly higher in porous media than in traditional batch tests. One to two orders of magnitude higher but lasting for shorter intervals.
• Consumption rates decline over repeated storage cycles, suggesting potential for stable and efficient long-term storage.
• MRI imaging reveals distinct flow patterns and saturation dynamics between sterile and non-sterile environments.
• Machine learning models can effectively complement reservoir simulations, reducing computational costs and aiding experimental design.

Raymond’s interdisciplinary approach combines reservoir engineering, petrophysics, biogeochemistry, and data science, offering valuable insights for the future of low-carbon energy storage.

Date & Time:  September 12th 0900-1000 CET

Speaker: Mathias Methlie Nilsen is one of the PhD students in CSSR employed at NORCE. He is in his final year of the CSSR PhD program and delivered his dissertation in August. Before beginning his PhD at CSSR, he completed a master’s degree in theoretical atomic, nuclear, and particle physics at the University of Bergen.

Mathias has published the paper Closed-loop Workflow for Short-term Optimization of Wind-powered Reservoir Management at European Association of Geoscientists & Engineers (EAGE).

This webinar presents a collaborative study conducted by Mathias M. Nilsen, Rolf Lorentzen and Andreas Størksen Stordal from NORCE, together with Olwijn Leeuwenburgh and Eduardo Barros from TNO. Below are the key points from the Webinar.

Context and Motivation

The Norwegian continental shelf faces significant CO2 emissions, primarily due to gas turbines used in the petroleum sector. These turbines burn gas to generate electricity, contributing heavily to greenhouse gas emissions. The proposed solution is to integrate nearby offshore wind farms to power production, despite the inherent variability and uncertainty of wind power compared to gas turbines.

Test Case: Drogon Reservoir

Developed by Equinor, the Drogon Reservoir entails:

• Reservoir Grid: 2 Injection wells (A5 & A6) and 5 Production wells (A1 to A4 and OP5).
• Objective: Optimize injection rates in the injectors and target oil production rates in the producers.

Power Demand and Emissions

The power system includes:

• Gas compression
• Water pumping for injection
• Energy cost of treating produced water
• A constant base load power demand The power sources involve two 8 MW wind power turbines alongside traditional gas turbines.

Methodology

1. Model Components:
   • Efficiency curves for injection pumps and gas compressors
   • Emission rate model for gas turbines
   • Power output model for wind turbines based on wind speed
2. Workflow Goal: Using wind power forecasts to vary daily operational strategies, aimed at reducing emissions while maintaining the long-term operational goal of maximizing lifecycle net present value (NPV).
3. Optimization Process:
   • Time is divided into intervals (e.g., one month).
   • Short-term optimization is performed using wind power forecasts, focusing on minimizing emissions and penalizing deviations in production and injection volumes.
4. Recalibration and Coarsened Model: A coarsened model is used for faster optimization, recalibrated before each optimization to match the full model’s simulation results.

Workflow Results

The workflow involves:

1. Target Strategy: Developed based on NPV optimization, focusing on target oil and injection rates.
2. Performance: Successful intervals showed significant CO2 reduction with minimal NPV compromise, e.g., a 27% emission reduction and a 0.6% NPV decrease. However, certain intervals exhibited issues due to ineffective coarse model calibration.

Conclusion and Future Work The study demonstrates the potential of using wind farm power forecasts in reservoir management. Future improvements are necessary for better model accuracy, considering alternatives such as machine learning or statistical models.

For Everyone: What Does This Mean?

This webinar explained how offshore operations can shift more of their energy use to wind power by using wind forecasts in their planning. Mathias demonstrated a workflow that adjusts pumping and production schedules depending on how much wind power is expected each day. The results showed that emissions can be noticeably reduced, even when the wind varies, and production can still be maintained at stable levels. The session made clear that better forecasting and planning can allow offshore platforms to use cleaner energy without introducing operational problems.

Title: CO₂ Storage Potential on the Norwegian Continental Shelf

In this inaugural CSSR webinar, researcher Trine Mykkeltvedt presents a powerful new screening tool designed to evaluate the CO₂ storage potential of depleted hydrocarbon fields on the Norwegian Continental Shelf (NCS). Built on publicly available data, the tool offers an interactive way to assess indicators for properties like storage capacity, injectivity, and field expected lifetimeacross 134 hydrocarbon fields. With open access to the data and code, this tool enables researchers, policymakers, and industry stakeholders to do an early stage screening for CO₂ storage candidates on the NCS.

Summary: Trine Mykkeltvedt presented a screening tool developed within the Local Net Zero focus area of the CSSR (Center for Sustainable Subsurface Resources). The tool is mainly developed by senior researcher Alexey Khrulenko, and uses publicly available data to evaluate the CO₂ storage potential in depleted hydrocarbon fields on the NCS.

Key points from her talk:

• the tool uses data from the Norwegian Offshore Directorate FactPages and DISKOS to estimate indicators and visualize them in a web-based application,
• indicators for storage capacity, injectivity, field expected lifetime, and more,
• can identify promising fields for CO₂ storage based on user-defined criteria,
• valuable first-stage screening method for researchers, policymakers, and industry stakeholders.
• the underlying data and code are open access, encouraging further development and collaboration.

For Everyone: What Does This Mean?

The talk introduced a new screening tool designed to identify which depleted offshore oil and gas fields on the Norwegian Continental Shelf could be suitable for long‑term CO₂ storage. Using openly available geological and production data for 134 hydrocarbon fields, the tool calculates key indicators such as estimated storage capacity, how easily CO₂ can be injected, and how long a field is expected to remain viable. These indicators are presented in an interactive web‑based interface that allows users to filter, compare, and explore fields based on criteria relevant to their needs. The tool provides a practical first step for evaluating potential CO₂ storage sites and is intended to support researchers, policymakers, and industry decision‑makers. Because both the underlying data and the code are openly accessible, the approach encourages collaboration and further development across the CO₂ storage community.

CSSR#1/2025: CO₂ Storage Potential on the Norwegian Continental Shelf

Biography: Trine Mykkeltvedt is a senior researcher at NORCE and leader of work package 6. She holds a PhD in applied Mathematics from the University of Bergen, and her research interests include computational methods and modelling of multiphase flow in porous media with a speciality in CO₂ storage and underground energy storage

Sarah Gasda highlighted the importance of collaboration at the Joint National Petrocentre Energy Conference- https://jnpc.no/ , saying, “CSSR is really proud to have joined forces with LowEmission and NCS2030. Together we make a strong case for the importance of long-term petroleum research to solve the grand challenges in climate and energy security. Besides collaboration and deeper insights into the three centres, it was also an opportunity for the masters and PhD students to build their networks and showcase their work.” 

Day 1: Strategic Partnerships & Innovation 

The first day focused on strategic partnerships and maximizing the impact of innovations from the three petroleum research centres. Rune Volla (The Research Council of Norway) and Ann-Cathrin Vaage (Offshore Norge) kicked off by highlighting the role of research in low-emission technologies. Volla emphasized their strong academic and industrial contributions, while Vaage pointed to Norway’s potential to boost EU energy security. Ola Elvestuen (Venstre) stressed the urgency of faster emission cuts and aligning with EU climate efforts. 

Leaders from the host institutions—Alexandra Bech Gjørv (SINTEF), Camilla Stoltenberg (NORCE Norwegian Research Centre), and Merete Vadla Madland (Universitetet i Stavanger (UiS)—shared insights into research collaboration.  

Centre directors Stefania Osk Gardarsdottir( LowEmission), Sarah Gasda(CSSR), and Alejandro Escalona(NCS2030) – provided overviews of their centres’ achievements. Elisabeth Sæther (Energidepartementet (Norge)) discussed the historical and future roles of petroleum research in Norway. The day ended with a panel discussion featuring key NCS stakeholders: 

Nick Ashton (Equinor) 
Linda Vigdel (SLB) 
Arne T Jacobsen (Sokkeldirektoratet) 
Kjell Morisbak Lund (Petoro) 

Thanks to Karoline Ski for moderating Day 1. In the evening, we enjoyed a delicious dinner at the Hotel Opera. 

Day 2: Technical Deep Dive 

Day 2 focused on technical details. It started with a PhD poster presentation breakfast and a keynote by Asgeir Tomasgard (NTNU). Researchers presented their ongoing work across five sessions: 

• Energy efficiency and CO₂ emissions from surface facilities 

• Reservoir management strategies for reducing CO₂ emissions 

• Digitalisation for optimized energy solutions 

• Alternative energy sources and holistic NCS transformation 

• Offshore carbon capture, utilization, and storage (CCUS) 

Conclusion 

The event showcased the power of collaboration in addressing climate and energy security challenges.  

CSSR presentation:  

Reinjection of produced water: Filter cake build up and energy usage-Ketil Djurhuus (NORCE)

A tool for screening thr CO2 storage potential of petroleum reservoirs on the NCS-Alexey Khrulenko (NORCE)

Underground hydrogen storage and microbial challenges  –Verena Nikeleit (NORCE)

Closed-loop Workflow for Short term Optimization of Wind-powered Reservoir Management- Mathias Methlie Nilsen (UiB/NORCE)

Accelerated data assimilation using machine learning- Antoine Lechevallier (NORCE)

Photos by Kjersti Riiber of University of Stavanger

Thanks to The Research Council of Norway for hosting and thanks to  Universitetet i Stavanger (UiS) – NORCE Norwegian Research Centre – SINTEF