Data Assimilation and Optimization
Research Director Data Assimilation and Optimization
- Bergen
rava@norceresearch.no
+47 51 87 56 39
+47 934 40 899
Decision support systems
Making decisions based on incomplete information and uncertain future outcomes
In the Energy & Technology division in NORCE we develop operational decision support systems in collaboration with customers and partners.
Our solutions aim to provide a clear situational overview, automate processes, and enable users to explore details. We focus on problem domains that target underspecified or unstructured issues and combine automatic models with traditional data access methods.
Further we use computer simulations and ensemble-based methodology for data assimilation, uncertainty prediction, optimization, and decision making. Our Data Assimilation and Optimization group is known for its expertise in ensemble-based methods for decision support, particularly in petroleum reservoir management, and are involved in projects related to CO2 sequestration, geothermal energy, hydropower, and medicine.
Contact
Randi Valestrand
The challenge of any corporation or government is to maximize the creation of some (commercial or social) value. The only way to create value is by making decisions. The decisions target an uncertain future and are almost always based on incomplete information. Proper methods for decision support are therefore essential. New sensor technologies are emerging within many areas, and an increasing amount of data is now available to industrial companies and societal authorities, but without proper methods for decision support, they are of little value.
The Energy & Technology division in NORCE has been developing operational decision support systems over the last 2 decades. The topics cover a wide range of application areas and problem domains. Our solutions are always developed in very close collaboration with our customers and partners. Our aim is to provide solutions that intuitively
- Give a clear situational overview.
- Automate as much as possible.
- Enable the user to explore the details.
The focus is on problem domains which
- Target underspecified or unstructured problems.
- Combine automatic models with traditional forms of data access.
Combining computer simulations with the ensemble-based methodology for data assimilation
Recent trends within artificial intelligence and machine learning suggest that one could base decisions on observed data alone, that is, without reference to an underlying theory. When such a theory is available, however, sound decision support should take mutually into account theoretical process understanding, observed data, uncertainties in the process model and uncertainties in the data. This can be achieved by combining computer simulations with the ensemble-based methodology for data assimilation, uncertainty prediction, optimization, and decision making.
The Data Assimilation and Optimization group in the Energy department of NORCE has world-leading expertise on ensemble-based methods for decision support. The main application in the last two decades has been petroleum reservoir management, where the group currently hosts two major projects, Digires, and 4DSEIS, supported by 10 petroleum companies and the Research Council of Norway. In recent years, the group has also been actively engaged in other applications, such as CO2 sequestration, geothermal energy, hydropower, and medicine.
