Our mission is
to support data-driven decisions

We aim to improve exploration and production success for our customers, by providing our data-driven analytics software, EarthNET, our data platform solution, EarthBANK, and data-driven uncertainty evaluation and decision support in EarthINSIGHT. You deserve products and workflows that maximize the value of your data.

Eirik is cofounder and CEO of Earth Science Analytics. He has 19 years’ experience from the E&P industry. He has held various technical and managerial roles in oil companies including Statoil, and 4 years as Exploration Manager in Rocksource. He has worked with exploration, field development, and production on the Norwegian Continetal Shelf as well as internationally. He holds a MSC in Petroleum Geology and a PhD in sedimentology from the University of Bergen, and is now laser focused on implementation of AI and data-driven analytics in petroleum geoscience.

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What if you could use all your data to make more profitable decisions?

With EarthBANK you can access vast amounts of structured data from national data repositories such as Diskos (Norway) and CDA (UK). Integration with EarthNET also gives users access to inferred properties such as lithology, porosity, permeability, and fluid saturation. Users can query EarthBANK for property distributions that match the geological context of the play, prospect or field that is being evaluated. This access to data-driven rock- and fluid-property distributions enables data-driven uncertainty evaluation and decision support in EarthINSIGHT.
Clients can add their proprietary data to their own copy of EarthBANK, so that they can leverage a comprehensive database of all their geoscience data.

Behzad is cofounder of Earth Science Analytics and serves as Chief Data Officer. He has 25 years’ experience from the E&P industry. He worked in exploration, development, and production projects of different petroleum provinces from the Middle East, NCS, UKCS, and Gulf of Mexico. He holds a PhD in exploration geophysics from the University of Bergen and is focused on data science to optimize key business processes in petroleum geoscience.

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Business impact through user friendly data-science applications

We aim to dramatically improve exploration and production success by applying artificial intelligence technology to petroleum geoscience. Extract insights on the spot with our user-friendly analytics software, EarthNET. Leverage our pre-trained models or build your own with drag-and-drop machine learning.

Dimitris is cofounder and CTO of Earth Science Analytics. Has served as CTO and various management board positions in defense industry for more than 10 years, was R&D team leader and member of strategy committee in Emerson Roxar. He has extensive experience from software development, programming, and machine learning for more than 20 years. Inventor of two patents, one of them internationally registered by Emerson Roxar AS as a sole inventor. He holds a PhD in electromagnetics and has more than 25 publications in peer reviewed international journals.

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Putting robust geological descriptions and interpretations at the core of data-driven analytics software

Chris is cofounder of Earth Science Analytics. He has 3 years’ experience in the E&P industry, having held various subsurface geoscience roles at Statoil. Since 2004, Chris has been Professor of Basin Analysis at Imperial College, focusing on the structural and stratigraphic development of sedimentary basins, with a particular interest in how this research can help improve E&P activities and decision-making. Chris holds a BSc in Geology, and a PhD in rift tectonics and sedimentation from the University of Manchester.

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Unpacking the subsurface Machine Learning Pandora’s Box

In subsurface work we have such a large variety of problems; some of which are computational, some optimization, whilst others are about reasoning, understanding and making decisions. There are many places where ML can be readily and successfully applied in isolation. However, successfully applying ML outside of niches, across subsurface work presents significant challenges; lack of labelled data and ground truth, limited and biased training datasets, data variability and model generalization are all present and can undermine results. In our R&D work we a carefully approaching these problems in order to learn how to successfully apply rapidly evolving ML techniques to broader subsurface problems.

Steve is the R&D director of Earth Science Analytics. He has over 20 years experience overall in research, technology and software development, 15 of which has been in E&P. The majority of that was with GeoTeric Ltd where he focussed on leading development of innovative technology for seismic data analysis and interpretation support. He helding a variety of roles from 2000 until 2013 when he was CTO. Steve has led multiple year R&D programmes with companies such as Norsk Hydro, Statoil and GDF Suez. Steve’s academic background is in signal, image processing and pattern recognition which he has applied to seismic and subsurface problems throughout his career.

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Using machine learning and multi-dimensional data to solve geoscience problems

Arne Klepp Kvalheim has 20 years experience from the Oil and Gas industry, mainly within exploration and research. His main focus has been seismic imaging, processing and seismic data analysis. He holds a Masters degree in Petroleum Geophysics from the University of Bergen. His current interests and professional focus is artificial intelligence, using machine learning and deep learning to solve a broad range of geoscientific problems in ways that better integrate and extract information from big, multi-dimensional datasets. To quote W. Edwards Deming – “Without data, your’re just another person with an opinion”.

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What if you could use all your data to make more profitable decisions?

We aim to improve exploration and production success by providing geoscience-driven data-analytics software, database solutions and workflows.

George is a machine-learning engineer with Earth Science Analytics.

What if you could use all your data to make more profitable decisions?

We aim to improve exploration and production success by providing geoscience-driven data-analytics software, database solutions and workflows.

Sokratis is a front-end software developer with Earth Science Analytics.

Data, and data management is the foundation of successful data analytics

Our data management approach ensures access to dynamically updated machine-readable structured data and models

Armin is a data manager with Earth Science Analytics.

Data, and data management is the foundation of successful data analytics

We are integrating data-management, and analytics for data-driven petroleum-geoscience workflows

Sjur is a data manager with Earth Science Analytics.

Leaving no gravel unturned

Not so long ago, it used to be common practice to decimate seismic datasets. Both because machines could not handle the amount of data in reasonable time, but also because human resources were lacking to evaluate the entirety of vast datasets. Today, modern workstations are able to deal with big data. Decimation became a thing of the past. But the most important caveat remains: do you have sufficient human resources to thoroughly analyse a full seismic dataset, with rigor, accuracy and within a constrained time frame? Earth Science Analyics' solutions empower geoscientists by revealing knowledge from every point of your dataset. Not only are you leaving no stone unturned, you are now flipping every gravel.

JB serves as Geo/Data Scientist. He has 12 years’ experience from the E&P industry, having worked as Geophysicist and Geostatistician, on a variety of petroleum projects over most Offshore provinces in Europe. He holds an MSc in Exploration Geophysics from the University of Pau and an MSc in Geotechnics from the University of Grenoble. Data Science is now his preferred precision tool for petroleum geoscience decisions.

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