Solution Seeker’s proprietary technology uses big data and machine learning techniques to maximize your oil production in real-time.

Significant value can be gained from optimizing field production in real-time.
Production optimization is a complex task due to the amount of possible settings and production bottlenecks present at an asset. In addition, there is considerable uncertainty regarding the frequently changing operating conditions. Data generated from increasingly instrumented modern oil and gas fields has reached massive amounts and will continue to grow. So the challenge remains; the industry is still struggling to figure out how to effectively utilize all of this data. Solution Seeker is taking on this challenge of turning data into value, and has developed advanced data-driven tools that exploit existing data sources to deliver actionable intelligence. Solution Seeker helps you make operational decisions on a daily basis that make a real impact on your top and bottom lines.

Leverage your data to maximize production


ProductionCompass is a completely data-driven tool providing real-time and actionable advice to production engineers, making sense of your data and supporting your daily pursuit of maximizing production.

Simple models, automatically updated
ProductionCompass is a data funnel that transforms relevant production data into operational advice. Data entering the funnel comprises historical and real-time production data, well tests, and other production metadata such as operator logs. This data is then subjected to big data techniques such as squashing, while still retaining important statistical characteristics. The resulting information is used to build models using regression analysis and machine learning. These models are automatically updated in real time as new data enters the funnel, ensuring frequent calibration to the current operational situation. This approach reduces the need for advanced fluid modeling and human model calibration efforts in a daily production optimization setting.

You can shift focus from data conditioning and model calibration to applying your expertise in analyzing production-increasing opportunities and better balancing your bottlenecks. You can focus on taking actions that maximize production.


Empowering production engineers with real-time machine learning

Shedding light on the elephant in the room; uncertainty
A great advantage of our data-driven technology is that the uncertainties of measurements and models are tracked and quantified. How the field and wells respond to operational change is inherently uncertain, and ignoring this uncertainty will at best be misleading. Our advice are accompanied by e.g. confidence intervals, helping you discriminate between alternative actions and choose the best course. Quantified uncertainty can also be used to design experiments that examine unexplored operational settings with the aim of lowering uncertainty and increasing knowledge. This extends the realm of opportunities that can be discovered, and increases model accuracy. Shedding light on uncertainty enables a novel range of functionality which to a very limited degree exists in technologies and services in the oil and gas industry today.

Uncertainty estimates all the way through


Our Data Aggregator enables a “everything is information” paradigm, which leads to a much higher level of data utilization. So even before introducing data analytics such as machine learning and optimization algorithms, ProductionCompass ensures that the constant stream of refined and processed data holds value on its own. This is achieved by automatically washing, filtering and aggregating the data and enhancing it with statistical information to enable predictive features.

The aggregated data can be post-processed through machine learning algorithms and calibration of data-driven models. This opens up for a broad spectrum of production enhancing applications and use-cases, of which 3 are presented here.


Assessment of production settings gives the engineer quick situational awareness by providing an overview of what actually changed between two different production settings. This makes it possible to reverse adverse actions faster or build confidence in keeping changes that actually lead to higher production.

Further, the system can continuously monitor the quality of current production settings and report on suboptimal performance. To exemplify, underperforming wells may be flagged.


Many petroleum fields have wells that produce without a dedicated test separator available. In this situation, common practice for testing is to shut the well off and compare production rates before and after, also called a “deduction test”. Using statistical uncertainty information, our Deduction test optimizer automates live analysis of such tests giving constant updates on test progress. This facilitates reduced test times, which are directly linked to reduction of production losses.


ProductionCompass provides engineers with a live feed of automatically generated production enhancing opportunities, that would otherwise have gone unnoticed. The system generates explicit advice based on predictive analytics on how valves, pumps or pressures can be changed to utilize production system bottlenecks better, and thereby increase production throughput.


Our Partners


We are developing our technology with a handful of selected partners.

The people behind the technology

At Solution Seeker, we come to work every day because we want to figure out how to turn data into value.

People have used data to make better, more informed decisions throughout history. Our goal and passion at Solution Seeker is better utilization of available data and increased situational awareness in the oil industry. We want to make technology simpler and the data more available to as many users as possible. Today, we provide the most actionable solution for daily production optimization. This makes us proud and we are excited to continue on this journey – will you join us too?

  • Vidar Gunnerud
    Vidar Gunnerud

    Vidar is CEO and co-founder. He previously managed the short-term production optimization project at the Center for Integrated Operations in the Petroleum Industry. Vidar holds a PhD from Engineering Cybernetics NTNU.

  • Sheri Shamlou
    Sheri Shamlou

    Sheri is responsible for business development and strategy. She has previous experience as a management consultant at Arkwright. She holds a MSc from Industrial Economics NTNU with specialization in optimization.

  • Bjarne Foss
    Bjarne Foss

    Bjarne is co-founder and board member at Solution Seeker, and advises on technical development and strategy. As professor at NTNU Cybernetics he holds extensive knowledge on control and optimization theory.

  • Anders Sandnes
    Anders Sandnes

    Anders is responsible for the technical development at Solution Seeker. He holds a MSc from Engineering Cybernetics NTNU with specialization in optimization.

  • Arild Nystad
    Arild Nystad

    As former resource director in OD, Arild has a large international network within the oil and gas industry. He is Solution Seeker’s main advisor on industry relations.

  • Vidar Uglane
    Vidar Uglane

    Vidar is responsible for following up and developing the pilot customers. He has experience as management consultant at McKinsey&Company. Vidar holds a MSc from Industrial Economics NTNU, specialized in optimization.

  • Bjarne Grimstad
    Bjarne Grimstad

    Bjarne is responsible for modeling and state estimation. He has previous experience as a Senior Engineer at FMC Technologies and holds a PhD from NTNU Cybernetics on the topic of optimization.

  • Anders Aune
    Anders Aune

    Anders is board member and advisor on business development and strategy. He has broad experience in managing tech startups, and has been project manager of more than 80 commercialization projects in his time at NTNU TTO.

  • Bjørn-Erik Dale
    Bjørn-Erik Dale

    Bjørn-Erik is board member and advisor on business relations and strategy. As Director at Arkwright Consulting, he has broad experience with strategic advisory for companies within the oil and gas industry.

  • Inge Sandstad Skrondal
    Inge Sandstad Skrondal

    Inge is responsible for data and parameter uncertainty assessment. He has two years experience from ConocoPhillips data analytics. He holds a MSc from Mathematics at UiO.

  • Stine Ursin-Holm
    Stine Ursin-Holm

    Stine is responsible for well test design and data analysis at Solution Seeker. She holds a MSc from Industrial Economics NTNU with specialization in optimization.

  • Anders Wenhaug
    Anders Wenhaug

    Anders works on GPU computing, databases and software performance optimization at Solution Seeker. He holds a MSc. in Computer Science from NTNU.

  • Ole Johnny Borgersen
    Ole Johnny Borgersen
  • Simon Larsen

Solution Seeker background

Solution Seeker is a spin-off company that originates from the Center for Integrated Operations (IO Center) at NTNU. Our technology results from an 8-year collaborative research project between NTNU, SINTEF and numerous industry partners. The methodologies we use are based on solid theoretical foundations as well as an intimate understanding of the oil industry’s challenges in daily production optimization.