Virtual CO2 Laboratory
Climit-finansiering67 % from the Research Council, 17 % from industrial partners, 16 % own funding.
PartnereChristian Michelsen Research (CMR), CGGVeritas Services (Norway) AS, Institutt for Energiteknikk (IFE), Statoil Petroleum AS, Universitetssenteret på Svalbard
Prosjektperiode2012 – 2015
The overall vision of the Virtual CO2 Laboratory project (VIRCOLA) is to develop a data platform and methodology that can facilitate better data utilization and work processes, and lead to better understanding of the storage capacity, injectivity and long-term confinement of CO2. The project is closely affiliated with the National Centre for Environment-friendly Energy SUCCESS. The primary objective of VIRCOLA is to develop a Virtual CO2 Laboratory for sharing and co-visualizing multi-disciplinary data from SUCCESS. VIRCOLA will be available to all the partners in the centre.
Longyearbyen CO2 Lab (LYB) has been selected as a case for the VIRCOLA project as several SUCCESS partners work with data from LYB. We have evaluated professional 2D and 3D geological modelling/visualization tools. The evaluation has identified Petrel and SKUA as appropriate tools for the VIRCOLA visualization platform. Finally, we have tested sharing the visualizations in remote collaboration sessions.
Through our work on the LYB data and discussions with the project partners, we have identified challenges that must be solved for improving data utilization and multidisciplinary work processes. These include among others:
• Different data types. The data from the LYB are multidisciplinary, and include geological, geophysical, petrophysical and geomechanical data, each of which encompasses a large variety of properties.
• Overlapping data. When data for the same area has been collected by different parties, the data might be of different resolution, use different gridding and can have conflicting values.
• Big data. While simple 2D-geological cross-section images take little storage space, other data (e.g. 3D reservoir models with small cell sizes or DEM datasets) can be very large.
• Multi-scale data. Data from LYB and surrounding areas embrace a large variation in scales, from km to mm.
We have used the VIRCOLA visualization platform to produce visualizations combining different data types from LYB. Based on these visualizations, we are currently discussing with SUCCESS scientist how VIRCOLA can facilitate their research. The researchers express that comparing their data with data from other research activities would be very useful, but doing this has so far been hindered by lack of tools and resources.
We have developed a workflow for how the VIRCOLA project interacts with SUCCESS. In activity 1 we collect data from SUCCESS members. When new data has been collected, we will in activity 2 introduce software for exploring this data. In particular, we focus on the ability to co-visualize data from different partners for gaining increased knowledge. We will make new and use existing software for data exploration, integrate data into the software and investigate solutions that enable remote collaboration. When exploration software has been established we will in activity 3 disseminate our visualizations of the data and collect feedback. This includes holding demonstrations, having presentations such as talks, posters and abstracts and performing questionnaires. The feedback will then be analyzed and appropriate action will be taken in activity 1 or 2.
In activity 1 we have created a database which describes all the data we have received with information such as where the data resides, who owns the data, what are the rights of use for the data and publications that describe the data more in depth. Recent interesting data from Svalbard that we have collected is CT scans from NGI, microbiology and geochemical data from UIB, magnetotelluric data from UiT and reservoir models from UNIS and CIPR.
For activity 2 we have integrated the microbiology and geochemical data, the magnetotelluric data and the reservoir models into the common visualization platform.
Finally, for activity 3 we have demonstrated the common visualization platform to SUCCESS members and we have performed an online survey which is about to be analyzed for mapping out how SUCCESS members currently collaborate across institution borders and what their needs are for increasing interdisciplinary collaboration. We have started experimenting with remote collaboration to allow the project partners to communicate with each other using our visualization platform.